[{"id":1,"name":"Stream function","shortname":"strf","description":"The horizontal wind field can be separated into divergent flow (i.e., flow that is purely divergent, with no swirl or rotation) and rotational flow (i.e., flow that is purely rotational and has no divergence).
The rotational (non-divergent) flow follows lines of constant stream function value (streamlines) and the speed of flow is proportional to the stream function gradient.
So streamlines show patterns of horizontal, rotational, air flow and the paths that particles would follow if the flow did not change with time.","unit_id":1,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":2,"name":"Velocity potential","shortname":"vp","description":"The horizontal wind field can be separated into divergent flow (i.e., flow that is purely divergent, with no swirl or rotation) and rotational flow (i.e., flow that is purely rotational and has no divergence).
This parameter is the scalar quantity whose gradient is the velocity vector of the irrotational flow. It can be used to show areas where the air is diverging (spreading out) or converging, which, depending on the vertical level, relate to ascending or descending air.","unit_id":1,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":3,"name":"Potential temperature","shortname":"pt","description":"","unit_id":2,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":4,"name":"Equivalent potential temperature","shortname":"eqpt","description":null,"unit_id":2,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":5,"name":"Saturated equivalent potential temperature","shortname":"sept","description":null,"unit_id":2,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":6,"name":"Soil sand fraction","shortname":"ssfr","description":null,"unit_id":3,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":7,"name":"Soil clay fraction","shortname":"scfr","description":null,"unit_id":3,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":8,"name":"Surface runoff","shortname":"sro","description":"Some water from rainfall, melting snow, or deep in the soil, stays stored in the soil. Otherwise, the water drains away, either over the surface (surface runoff), or under the ground (sub-surface runoff) and the sum of these two is simply called 'runoff'. This parameter is the total amount of water accumulated over a particular time period which depends on the data extracted.The units of runoff are depth in metres. This is the depth the water would have if it were spread evenly over the grid box. Care should be taken when comparing model parameters with observations, because observations are often local to a particular point rather than averaged over a grid square area. Observations are also often taken in different units, such as mm/day, rather than the accumulated metres produced here.
Runoff is a measure of the availability of water in the soil, and can, for example, be used as an indicator of drought or flood. More information about how runoff is calculated is given in the IFS Physical Processes documentation.\r\n\r\n[NOTE: See 231010 for the equivalent parameter in \"kg m-2\"]","unit_id":4,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":9,"name":"Sub-surface runoff","shortname":"ssro","description":"Some water from rainfall, melting snow, or deep in the soil, stays stored in the soil. Otherwise, the water drains away, either over the surface (surface runoff), or under the ground (sub-surface runoff) and the sum of these two is simply called 'runoff'. This parameter is the total amount of water accumulated over a particular time period which depends on the data extracted.The units of runoff are depth in metres. This is the depth the water would have if it were spread evenly over the grid box. Care should be taken when comparing model parameters with observations, because observations are often local to a particular point rather than averaged over a grid square area. Observations are also often taken in different units, such as mm/day, rather than the accumulated metres produced here.
Runoff is a measure of the availability of water in the soil, and can, for example, be used as an indicator of drought or flood. More information about how runoff is calculated is given in the IFS Physical Processes documentation.\r\n\r\n[NOTE: See 231012 for the equivalent parameter in \"kg m-2\"]","unit_id":4,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":10,"name":"Wind speed","shortname":"ws","description":"
The speed of horizontal air movement in metres per second.
The eastward and northward components of the horizontal wind are also available as parameters.
","unit_id":5,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":11,"name":"U component of divergent wind","shortname":"udvw","description":null,"unit_id":5,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":12,"name":"V component of divergent wind","shortname":"vdvw","description":null,"unit_id":5,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":13,"name":"U component of rotational wind","shortname":"urtw","description":null,"unit_id":5,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":14,"name":"V component of rotational wind","shortname":"vrtw","description":null,"unit_id":5,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":15,"name":"UV visible albedo for direct radiation (climatological)","shortname":"aluvp","description":"Albedo is a measure of the reflectivity of the Earth's surface. This parameter is the fraction of direct solar (shortwave) radiation with wavelengths shorter than 0.7 µm (microns, 1 millionth of a metre) reflected by the Earth's surface (for snow-free land surfaces only). It is one of four components (parameters 15-18) that were used by the ECMWF Integrated Forecasting System (IFS) to represent albedo up to and including Cycle 46R1. Later cycles use instead six components (parameters 210186-210191). See further documentation
Solar radiation at the surface can be direct or diffuse. Solar radiation can be scattered in all directions by particles in the atmosphere, some of which reaches the surface (diffuse solar radiation). Some solar radiation reaches the surface without being scattered (direct solar radiation).
In the IFS, a climatological (observed values averaged over a period of several years) background albedo is used which varies from month to month through the year, modified by the model over water, ice and snow.","unit_id":3,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":16,"name":"UV visible albedo for diffuse radiation (climatological)","shortname":"aluvd","description":"Albedo is a measure of the reflectivity of the Earth's surface. This parameter is the fraction of diffuse solar (shortwave) radiation with wavelengths shorter than 0.7 µm (microns, 1 millionth of a metre) reflected by the Earth's surface (for snow-free land surfaces only). It is one of four components (parameters 15-18) that were used by the ECMWF Integrated Forecasting System (IFS) to represent albedo up to and including Cycle 46R1. Later cycles use instead six components (parameters 210186-210191). See further documentation
Solar radiation at the surface can be direct or diffuse. Solar radiation can be scattered in all directions by particles in the atmosphere, some of which reaches the surface (diffuse solar radiation). Some solar radiation reaches the surface without being scattered (direct solar radiation).
In the IFS, a climatological (observed values averaged over a period of several years) background albedo is used which varies from month to month through the year, modified by the model over water, ice and snow.","unit_id":3,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":17,"name":"Near IR albedo for direct radiation (climatological)","shortname":"alnip","description":"Albedo is a measure of the reflectivity of the Earth's surface. This parameter is the fraction of direct solar (shortwave) radiation with wavelengths longer than 0.7 (microns, 1 millionth of a metre) reflected by the Earth's surface (for snow-free land surfaces only). It is one of four components (parameters 15-18) that were used by the ECMWF Integrated Forecasting System (IFS) to represent albedo up to and including Cycle 46R1. Later cycles use instead six components (parameters 210186-210191). See further documentation
Solar radiation at the surface can be direct or diffuse. Solar radiation can be scattered in all directions by particles in the atmosphere, some of which reaches the surface (diffuse solar radiation). Some solar radiation reaches the surface without being scattered (direct solar radiation).
In the IFS, a climatological (observed values averaged over a period of several years) background albedo is used which varies from month to month through the year, modified by the model over water, ice and snow.","unit_id":3,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":18,"name":"Near IR albedo for diffuse radiation (climatological)","shortname":"alnid","description":"Albedo is a measure of the reflectivity of the Earth's surface. This parameter is the fraction of diffuse solar (shortwave) radiation with wavelengths longer than 0.7 µm (microns, 1 millionth of a metre) reflected by the Earth's surface (for snow-free land surfaces only). It is one of four components (parameters 15-18) that were used by the ECMWF Integrated Forecasting System (IFS) to represent albedo up to and including Cycle 46R1. Later cycles use instead six components (parameters 210186-210191). See further documentation
Solar radiation at the surface can be direct or diffuse. Solar radiation can be scattered in all directions by particles in the atmosphere, some of which reaches the surface (diffuse solar radiation). Some solar radiation reaches the surface without being scattered (direct solar radiation).
In the IFS, a climatological (observed values averaged over a period of several years) background albedo is used which varies from month to month through the year, modified by the model over water, ice and snow.","unit_id":3,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":19,"name":"Clear sky surface UV","shortname":"uvcs","description":"0.20-0.44 um accumulated field","unit_id":6,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":20,"name":"Surface photosynthetically active radiation, clear sky","shortname":"parcs","description":"0.44-0.70 um accumulated field","unit_id":6,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":21,"name":"Unbalanced component of temperature","shortname":"uctp","description":"Residual resulting from subtracting from temperature an approximate 'balanced' value derived from relevant variable(s)","unit_id":2,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":22,"name":"Unbalanced component of logarithm of surface pressure","shortname":"ucln","description":"Residual resulting from subtracting from logarithm of surface pressure an approximate 'balanced' value derived from relevant variable(s).\n Note that this parameter is dimensionless","unit_id":7,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":23,"name":"Unbalanced component of divergence","shortname":"ucdv","description":"Residual resulting from subtracting from divergence an approximate 'balanced' value derived from relevant variable(s)","unit_id":8,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":24,"name":"Reserved for future unbalanced components","shortname":"~","description":null,"unit_id":7,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":25,"name":"Reserved for future unbalanced components","shortname":"~","description":null,"unit_id":7,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":26,"name":"Lake cover","shortname":"cl","description":"
This parameter is the proportion of a grid box covered by inland water bodies (lakes, reservoirs, rivers) and coastal waters. Values vary between 0: no inland or coastal water body, and 1: grid box is fully covered with inland or coastal water body. This field is specified from observations and is constant in time.
ECMWF implemented a lake model in May 2015 to represent the water temperature and lake ice of all the world's major inland water bodies in the Integrated Forecasting System (IFS). The IFS differentiates between (i) ocean water, handled by the ocean model, and (ii) inland water (lakes, reservoirs and rivers) and coastal waters handled by the lake parametrisation. Lake depth and surface area (or fractional cover) are kept constant in time.
","unit_id":3,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":27,"name":"Low vegetation cover","shortname":"cvl","description":"This parameter is the fraction of the grid box (0-1) that is covered with vegetation that is classified as 'low'.
This is one of the parameters in the model that describes land surface vegetation. 'Low vegetation' consists of crops and mixed farming, irrigated crops, short grass, tall grass, tundra, semidesert, bogs and marshes, evergreen shrubs, deciduous shrubs, and water and land mixtures.","unit_id":3,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":28,"name":"High vegetation cover","shortname":"cvh","description":"This parameter is the fraction of the grid box (0-1) that is covered with vegetation that is classified as 'high'.
This is one of the parameters in the model that describes land surface vegetation. 'High vegetation' consists of evergreen trees, deciduous trees, mixed forest/woodland, and interrupted forest.","unit_id":3,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":29,"name":"Type of low vegetation","shortname":"tvl","description":"This parameter indicates the 10 types of low vegetation recognised by the ECMWF Integrated Forecasting System:
1 = Crops, Mixed farming
2 = Grass
7 = Tall grass
9 = Tundra
10 = Irrigated crops
11 = Semidesert
13 = Bogs and marshes
16 = Evergreen shrubs
17 = Deciduous shrubs
20 = Water and land mixtures
They are used to calculate the surface energy balance and the snow albedo.
The other types (3, 4, 5, 6, 18, 19 and 19) are high vegetation, or indicate no land surface vegetation (8 = Desert, 12=Ice caps and Glaciers, 14 = Inland water, 15 =Ocean).","unit_id":112,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":30,"name":"Type of high vegetation","shortname":"tvh","description":"This parameter indicates the 6 types of high vegetation recognised by the ECMWF Integrated Forecasting System:
3 = Evergreen needleleaf trees
4 = Deciduous needleleaf trees
5 = Deciduous broadleaf trees
6 = Evergreen broadleaf trees
18 = Mixed forest/woodland
19 = Interrupted forest
They are used to calculate the surface energy balance and the snow albedo.
The other types (1, 2, 7, 9, 10, 11, 13, 16, 17 and 20) are low vegetation, or indicate no land surface vegetation (8 = Desert, 12=Ice caps and Glaciers, 14 = Inland water, 15 =Ocean).","unit_id":112,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":31,"name":"Sea ice area fraction","shortname":"ci","description":"This parameter is the fraction of a grid box which is covered by sea ice. Sea ice can only occur in a grid box which includes ocean or inland water according to the land sea mask and lake cover, at the resolution being used. This parameter can be known as sea-ice (area) fraction, sea-ice concentration and more generally as sea-ice cover.
Coupled atmosphere ocean simulations of the ECMWF Integrated Forecasting System (IFS) predict the formation and melting of sea ice. Otherwise, in analyses and atmosphere only simulations, sea ice is derived from observations, but the model does take account of the way that sea ice alters the interaction between the atmosphere and ocean.
Sea ice is frozen sea water which floats on the surface of the ocean. Sea ice does not include ice which forms on land such as glaciers, icebergs and ice-sheets. It also excludes ice shelves which are anchored on land, but protrude out over the surface of the ocean. These phenomena are not modelled by the IFS.
Long-term monitoring of sea ice is important for understanding climate change. Sea ice also affects shipping routes through the polar regions.","unit_id":3,"encoding_ids":["grib1","grib2","netcdf"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":32,"name":"Snow albedo","shortname":"asn","description":"This parameter is a measure of the reflectivity of the snow-covered part of the grid box. It is the fraction of solar (shortwave) radiation reflected by snow across the solar spectrum.
This parameter changes with snow age and also depends on vegetation height. For low vegetation, it ranges between 0.52 for old snow and 0.88 for fresh snow. For high vegetation with snow underneath, it depends on vegetation type and has values between 0.27 and 0.38. See further information.\n [NOTE: See 228032 for the equivalent parameter in \"%\"]","unit_id":3,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":33,"name":"Snow density","shortname":"rsn","description":"This parameter is the mass of snow per cubic metre in the snow layer.
The ECMWF Integrated Forecast System (IFS) model represents snow as a single additional layer over the uppermost soil level. The snow may cover all or part of the grid box.
See further information on snow in the IFS.","unit_id":9,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":34,"name":"Sea surface temperature","shortname":"sst","description":"This parameter is the temperature of sea water near the surface.
This parameter is taken from various providers, who process the observational data in different ways. Each provider uses data from several different observational sources. For example, satellites measure sea surface temperature (SST) in a layer a few microns thick in the uppermost mm of the ocean, drifting buoys measure SST at a depth of about 0.2-1.5m, whereas ships sample sea water down to about 10m, while the vessel is underway. Deeper measurements are not affected by changes that occur during a day, due to the rising and setting of the Sun (diurnal variations).
Sometimes this parameter is taken from a forecast made by coupling the NEMO ocean model to the ECMWF Integrated Forecasting System. In this case, the SST is the average temperature of the uppermost metre of the ocean and does exhibit diurnal variations.
This parameter has units of kelvin (K). Temperature measured in kelvin can be converted to degrees Celsius (°C) by subtracting 273.15.","unit_id":2,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":35,"name":"Ice temperature layer 1","shortname":"istl1","description":"This parameter is the sea-ice temperature in layer 1 (0 to 7cm).
The ECMWF Integrated Forecasting System (IFS) has a four-layer sea-ice slab: Layer 1: 0-7cm Layer 2: 7-28cm Layer 3: 28-100cm Layer 4: 100-150cm
The temperature of the sea-ice in each layer changes as heat is transferred between the sea-ice layers and the atmosphere above and ocean below. See further documentation.","unit_id":2,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":36,"name":"Ice temperature layer 2","shortname":"istl2","description":"This parameter is the sea-ice temperature in layer 2 (7 to 28 cm).
The ECMWF Integrated Forecasting System (IFS) has a four-layer sea-ice slab: Layer 1: 0-7cm Layer 2: 7-28cm Layer 3: 28-100cm Layer 4: 100-150cm
The temperature of the sea-ice in each layer changes as heat is transferred between the sea-ice layers and the atmosphere above and ocean below. See further documentation.","unit_id":2,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":37,"name":"Ice temperature layer 3","shortname":"istl3","description":"This parameter is the sea-ice temperature in layer 3 (28 to 100 cm).
The ECMWF Integrated Forecasting System (IFS) has a four-layer sea-ice slab: Layer 1: 0-7cm Layer 2: 7-28cm Layer 3: 28-100cm Layer 4: 100-150cm
The temperature of the sea-ice in each layer changes as heat is transferred between the sea-ice layers and the atmosphere above and ocean below. See further documentation.","unit_id":2,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":38,"name":"Ice temperature layer 4","shortname":"istl4","description":"This parameter is the sea-ice temperature in layer 4 (100 to 150 cm).
The ECMWF Integrated Forecasting System (IFS) has a four-layer sea-ice slab: Layer 1: 0-7cm Layer 2: 7-28cm Layer 3: 28-100cm Layer 4: 100-150cm
The temperature of the sea-ice in each layer changes as heat is transferred between the sea-ice layers and the atmosphere above and ocean below. See further documentation.","unit_id":2,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":39,"name":"Volumetric soil water layer 1","shortname":"swvl1","description":"This parameter is the volume of water in soil layer 1 (0 - 7cm, the surface is at 0cm).
The ECMWF Integrated Forecasting System model has a four-layer representation of soil: Layer 1: 0 - 7cm Layer 2: 7 - 28cm Layer 3: 28 - 100cm Layer 4: 100 - 289cm
The volumetric soil water is associated with the soil texture (or classification), soil depth, and the underlying groundwater level.","unit_id":10,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":40,"name":"Volumetric soil water layer 2","shortname":"swvl2","description":"This parameter is the volume of water in soil layer 2 (7 - 28cm, the surface is at 0cm).
The ECMWF Integrated Forecasting System model has a four-layer representation of soil: Layer 1: 0 - 7cm Layer 2: 7 - 28cm Layer 3: 28 - 100cm Layer 4: 100 - 289cm
The volumetric soil water is associated with the soil texture (or classification), soil depth, and the underlying groundwater level.","unit_id":10,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":41,"name":"Volumetric soil water layer 3","shortname":"swvl3","description":"This parameter is the volume of water in soil layer 3 (28 - 100cm, the surface is at 0cm).
The ECMWF Integrated Forecasting System model has a four-layer representation of soil: Layer 1: 0 - 7cm Layer 2: 7 - 28cm Layer 3: 28 - 100cm Layer 4: 100 - 289cm
The volumetric soil water is associated with the soil texture (or classification), soil depth, and the underlying groundwater level.","unit_id":10,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":42,"name":"Volumetric soil water layer 4","shortname":"swvl4","description":"This parameter is the volume of water in soil layer 4 (100 - 289cm, the surface is at 0cm).
The ECMWF Integrated Forecasting System model has a four-layer representation of soil: Layer 1: 0 - 7cm Layer 2: 7 - 28cm Layer 3: 28 - 100cm Layer 4: 100 - 289cm
The volumetric soil water is associated with the soil texture (or classification), soil depth, and the underlying groundwater level.","unit_id":10,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":43,"name":"Soil type","shortname":"slt","description":"
This parameter is the texture (or classification) of soil used by the land surface scheme of the ECMWF Integrated Forecast System to predict the water holding capacity of soil in soil moisture and runoff calculations. It is derived from the root zone data (30-100 cm below the surface) of the FAO/UNESCO Digital Soil Map of the World, DSMW (FAO, 2003), which exists at a resolution of 5' X 5' (about 10 km).
The seven soil types are:
Coarse
1
Medium
2
Medium fine
3
Fine
4
Very fine
5
Organic
6
Tropical organic
7
","unit_id":231,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":44,"name":"Snow evaporation","shortname":"es","description":"This parameter is the accumulated amount of water that has evaporated from snow from the snow-covered area of a grid box into vapour in the air above.
The ECMWF Integrated Forecast System represents snow as a single additional layer over the uppermost soil level. The snow may cover all or part of the grid box. This parameter is the depth of water there would be if the evaporated snow (from the snow-covered area of a grid box ) were liquid and were spread evenly over the whole grid box.
The ECMWF Integrated Forecasting System convention is that downward fluxes are positive. Therefore, negative values indicate evaporation and positive values indicate deposition.\n [NOTE: See 231003 for the equivalent parameter in \"kg m-2\"]","unit_id":27,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":45,"name":"Snowmelt","shortname":"smlt","description":"This parameter is the accumulated amount of water that has melted from snow in the snow-covered area of a grid box.
The ECMWF Integrated Forecast System represents snow as a single additional layer over the uppermost soil level. The snow may cover all or part of the grid box. This parameter is the depth of water there would be if the melted snow (from the snow-covered area of a grid box ) were spread evenly over the whole grid box. For example, if half the grid box were covered in snow with a water equivalent depth of 0.02m, this parameter would have a value of 0.01m.
This parameter is accumulated over a particular time period which depends on the data extracted.\n[NOTE: See 3099 for the equivalent parameter in \"kg m-2\"]","unit_id":27,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":46,"name":"Solar duration","shortname":"sdur","description":null,"unit_id":12,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":47,"name":"Surface direct normal short-wave (solar) radiation","shortname":"dsrp","description":"
This parameter is the amount of direct radiation from the Sun (also known as solar or shortwave radiation) reaching the surface on a plane perpendicular to the direction of the Sun.
Solar radiation at the surface can be direct or diffuse. Solar radiation can be scattered in all directions by particles in the atmosphere, some of which reaches the surface (diffuse solar radiation). Some solar radiation reaches the surface without being scattered (direct solar radiation). See further documentation.
This parameter is accumulated over a particular time period which depends on the data extracted. The units are joules per square metre (J m-2). To convert to watts per square metre (W m-2), the accumulated values should be divided by the accumulation period expressed in seconds.
The ECMWF convention for vertical fluxes is positive downwards.
","unit_id":6,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":48,"name":"Time-integrated magnitude of turbulent surface stress","shortname":"magss","description":"
Accumulated field
","unit_id":14,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":49,"name":"Maximum 10 metre wind gust since previous post-processing","shortname":"10fg","description":"Maximum 3 second wind at 10 m height as defined by WMO.
\r\nParametrization represents turbulence only before 01102008; thereafter effects of convection are included. The 3 s gust is computed every time step and and the maximum is kept since the last postprocessing.","unit_id":5,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":50,"name":"Large-scale precipitation fraction","shortname":"lspf","description":"This parameter is the accumulation of the fraction of the grid box (0-1) that was covered by large-scale precipitation.
This parameter is accumulated over a particular time period which depends on the data extracted. See further information.","unit_id":12,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":51,"name":"Maximum temperature at 2 metres in the last 24 hours","shortname":"mx2t24","description":"The highest value of 2 metre temperature in the previous 24 hour period.
2m temperature is calculated by interpolating between the lowest model level and the Earth's surface, taking account of the atmospheric conditions. See further information.
This parameter has units of kelvin (K). Temperature measured in kelvin can be converted to degrees Celsius (°C) by subtracting 273.15.","unit_id":2,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":52,"name":"Minimum temperature at 2 metres in the last 24 hours","shortname":"mn2t24","description":"The lowest value of 2 metre temperature in the previous 24 hour period.
2m temperature is calculated by interpolating between the lowest model level and the Earth's surface, taking account of the atmospheric conditions. See further information.
This parameter has units of kelvin (K). Temperature measured in kelvin can be converted to degrees Celsius (°C) by subtracting 273.15.","unit_id":2,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":53,"name":"Montgomery potential","shortname":"mont","description":"Takes the role of geopotential in an isentropic vertical coordinate","unit_id":15,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":54,"name":"Pressure","shortname":"pres","description":null,"unit_id":16,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":55,"name":"Mean temperature at 2 metres in the last 24 hours","shortname":"mean2t24","description":"
The mean value of 2 metre temperature in the previous 24 hour period. The mean is calculated from the temperature at each model time step.
2m temperature is calculated by interpolating between the lowest model level and the Earth's surface, taking account of the atmospheric conditions. See further information.
This parameter has units of kelvin (K). Temperature measured in kelvin can be converted to degrees Celsius (°C) by subtracting 273.15
Please use 228004 for the GRIB2 encoding of this parameter.
","unit_id":2,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":56,"name":"Mean 2 metre dewpoint temperature in the last 24 hours","shortname":"mn2d24","description":"
6-hourly intervals
Please use 235168 for the GRIB2 encoding of this parameter.
This parameter is the amount of ultraviolet (UV) radiation reaching the surface. It is the amount of radiation passing through a horizontal plane, not a plane perpendicular to the direction of the Sun.
UV radiation is part of the electromagnetic spectrum emitted by the Sun that has wavelengths shorter than visible light. In the ECMWF Integrated Forecasting system it is defined as radiation with a wavelength of 0.20-0.44 µm (microns, 1 millionth of a metre).
Small amounts of UV are essential for living organisms, but overexposure may result in cell damage; in humans this includes acute and chronic health effects on the skin, eyes and immune system. UV radiation is absorbed by the ozone layer, but some reaches the surface. The depletion of the ozone layer is causing concern over an increase in the damaging effects of UV.
This parameter is accumulated over a particular time period which depends on the data extracted. The units are joules per square metre (J m-2). To convert to watts per square metre (W m-2), the accumulated values should be divided by the accumulation period expressed in seconds.
The ECMWF convention for vertical fluxes is positive downwards.
","unit_id":6,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":58,"name":"Photosynthetically active radiation at the surface","shortname":"par","description":"0.40-0.70 um. Accumulated field. \nBefore Cycle 43R1, a coding error meant that PAR was computed from the wrong spectral bands and hence was underestimated by around 30%. It should therefore only be used from Cycles 43R1 and later.","unit_id":6,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":59,"name":"Convective available potential energy","shortname":"cape","description":"This is an indication of the instability (or stability) of the atmosphere and can be used to assess the potential for the development of convection, which can lead to heavy rainfall, thunderstorms and other severe weather.
In the ECMWF Integrated Forecasting System (IFS), CAPE is calculated by considering parcels of air departing at different model levels below the 350 hPa level. If a parcel of air is more buoyant (warmer and/or with more moisture) than its surrounding environment, it will continue to rise (cooling as it rises) until it reaches a point where it no longer has positive buoyancy. CAPE is the potential energy represented by the total excess buoyancy. The maximum CAPE produced by the different parcels is the value retained.
Large positive values of CAPE indicate that an air parcel would be much warmer than its surrounding environment and therefore, very buoyant. CAPE is related to the maximum potential vertical velocity of air within an updraft; thus, higher values indicate greater potential for severe weather. Observed values in thunderstorm environments often may exceed 1000 joules per kilogram (J kg-1), and in extreme cases may exceed 5000 J kg-1.
The calculation of this parameter assumes: (i) the parcel of air does not mix with surrounding air; (ii) ascent is pseudo-adiabatic (all condensed water falls out) and (iii) other simplifications related to the mixed-phase condensational heating.","unit_id":17,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":60,"name":"Potential vorticity","shortname":"pv","description":"Potential vorticity is a measure of the capacity for air to rotate in the atmosphere. If we ignore the effects of heating and friction, potential vorticity is conserved following an air parcel. It is used to look for places where large wind storms are likely to originate and develop. Potential vorticity increases strongly above the tropopause and therefore, it can also be used in studies related to the stratosphere and stratosphere-troposphere exchanges.
Large wind storms develop when a column of air in the atmosphere starts to rotate. Potential vorticity is calculated from the wind, temperature and pressure across a column of air in the atmosphere. ","unit_id":18,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":62,"name":"Observation count","shortname":"obct","description":"Count of observations used in calculating value at a gridpoint","unit_id":7,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":63,"name":"Start time for skin temperature difference","shortname":"stsktd","description":"Seconds from reference time","unit_id":12,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":64,"name":"Finish time for skin temperature difference","shortname":"ftsktd","description":"Seconds from reference time","unit_id":12,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":65,"name":"Skin temperature difference","shortname":"sktd","description":"","unit_id":2,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":66,"name":"Leaf area index, low vegetation","shortname":"lai_lv","description":"This parameter is the surface area of one side of all the leaves found over an area of land for vegetation classified as 'low'. This parameter has a value of 0 over bare ground or where there are no leaves. It can be calculated daily from satellite data. It is important for forecasting, for example, how much rainwater will be intercepted by the vegetative canopy, rather than falling to the ground.
This is one of the parameters in the model that describes land surface vegetation. 'Low vegetation' consists of crops and mixed farming, irrigated crops, short grass, tall grass, tundra, semidesert, bogs and marshes, evergreen shrubs, deciduous shrubs, and water and land mixtures.","unit_id":19,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":67,"name":"Leaf area index, high vegetation","shortname":"lai_hv","description":"This parameter is the surface area of one side of all the leaves found over an area of land for vegetation classified as 'high'. This parameter has a value of 0 over bare ground or where there are no leaves. It can be calculated daily from satellite data. It is important for forecasting, for example, how much rainwater will be intercepted by the vegetative canopy, rather than falling to the ground.
This is one of the parameters in the model that describes land surface vegetation. 'High vegetation' consists of evergreen trees, deciduous trees, mixed forest/woodland, and interrupted forest.","unit_id":19,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":68,"name":"Minimum stomatal resistance, low vegetation","shortname":"msr_lv","description":"","unit_id":20,"encoding_ids":["grib1"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":69,"name":"Minimum stomatal resistance, high vegetation","shortname":"msr_hv","description":"","unit_id":20,"encoding_ids":["grib1"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":70,"name":"Biome cover, low vegetation","shortname":"bc_lv","description":"","unit_id":3,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":71,"name":"Biome cover, high vegetation","shortname":"bc_hv","description":"","unit_id":3,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":72,"name":"Instantaneous surface solar radiation downwards","shortname":"issrd","description":"
","unit_id":76,"encoding_ids":["grib1"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":74,"name":"Standard deviation of filtered subgrid orography (climatological)","shortname":"sdfor","description":"Climatological field (scales between approximately 3 and 22 km are included)","unit_id":4,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":75,"name":"Specific rain water content","shortname":"crwc","description":"The mass of water produced from large-scale clouds that is of raindrop size and so can fall to the surface as precipitation.
Large-scale clouds are generated by the cloud scheme in the ECMWF Integrated Forecasting System (IFS). The cloud scheme represents the formation and dissipation of clouds and large-scale precipitation due to changes in atmospheric quantities (such as pressure, temperature and moisture) predicted directly by the IFS at spatial scales of a grid box or larger. See further information.
The quantity is expressed in kilograms per kilogram of the total mass of moist air. The 'total mass of moist air' is the sum of the dry air, water vapour, cloud liquid, cloud ice, rain and falling snow. This parameter represents the average value for a grid box.
Clouds contain a continuum of different sized water droplets and ice particles. The IFS cloud scheme simplifies this to represent a number of discrete cloud droplets/particles including: cloud water droplets, raindrops, ice crystals and snow (aggregated ice crystals). The processes of droplet formation, phase transition and aggregation are also highly simplified in the IFS.","unit_id":21,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":76,"name":"Specific snow water content","shortname":"cswc","description":"The mass of snow (aggregated ice crystals) produced from large-scale clouds that can fall to the surface as precipitation.
Large-scale clouds are generated by the cloud scheme in the ECMWF Integrated Forecasting System (IFS). The cloud scheme represents the formation and dissipation of clouds and large-scale precipitation due to changes in atmospheric quantities (such as pressure, temperature and moisture) predicted directly by the IFS at spatial scales of a grid box or larger. See further information.
The mass is expressed in kilograms per kilogram of the total mass of moist air. The 'total mass of moist air' is the sum of the dry air, water vapour, cloud liquid, cloud ice, rain and falling snow. This parameter represents the average value for a grid box.
Clouds contain a continuum of different sized water droplets and ice particles. The IFS cloud scheme simplifies this to represent a number of discrete cloud droplets/particles including: cloud water droplets, raindrops, ice crystals and snow (aggregated ice crystals). The processes of droplet formation, phase transition and aggregation are also highly simplified in the IFS.","unit_id":21,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":77,"name":"Eta-coordinate vertical velocity","shortname":"etadot","description":"This parameter is the rate of air motion in the upward or downward direction. The ECMWF Integrated Forecasting System (IFS) uses a pressure and terrain-based vertical coordinate system called eta-coordinate. Since pressure in the atmosphere decreases with height, negative values of eta-coordinate vertical velocity indicate upward motion.
This parameter is used in the IFS to calculate the vertical transport, or advection, of atmospheric quantities such as moisture.","unit_id":8,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":78,"name":"Total column cloud liquid water","shortname":"tclw","description":"This parameter is the amount of liquid water contained within cloud droplets in a column extending from the surface of the Earth to the top of the atmosphere. Rain water droplets, which are much larger in size (and mass), are not included in this parameter.
This parameter represents the area averaged value for a model grid box.
Clouds contain a continuum of different- sized water droplets and ice particles. The ECMWF Integrated Forecasting System (IFS) cloud scheme simplifies this to represent a number of discrete cloud droplets/particles including: cloud water droplets, raindrops, ice crystals and snow (aggregated ice crystals). The processes of droplet formation, phase transition and aggregation are also highly simplified in the IFS.","unit_id":22,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":79,"name":"Total column cloud ice water","shortname":"tciw","description":"This parameter is the amount of ice contained within clouds in a column extending from the surface of the Earth to the top of the atmosphere. Snow (aggregated ice crystals) is not included in this parameter.
This parameter represents the area averaged value for a model grid box.
Clouds contain a continuum of different- sized water droplets and ice particles. The ECMWF Integrated Forecasting System (IFS) cloud scheme simplifies this to represent a number of discrete cloud droplets/particles including: cloud water droplets, raindrops, ice crystals and snow (aggregated ice crystals). The processes of droplet formation, phase transition and aggregation are also highly simplified in the IFS.","unit_id":22,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":80,"name":"Experimental product","shortname":"~","description":null,"unit_id":7,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":81,"name":"Experimental product","shortname":"~","description":null,"unit_id":7,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":82,"name":"Experimental product","shortname":"~","description":null,"unit_id":7,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":83,"name":"Experimental product","shortname":"~","description":null,"unit_id":7,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":84,"name":"Experimental product","shortname":"~","description":null,"unit_id":7,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":85,"name":"Experimental product","shortname":"~","description":null,"unit_id":7,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":86,"name":"Experimental product","shortname":"~","description":null,"unit_id":7,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":87,"name":"Experimental product","shortname":"~","description":null,"unit_id":7,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":88,"name":"Experimental product","shortname":"~","description":null,"unit_id":7,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":89,"name":"Experimental product","shortname":"~","description":null,"unit_id":7,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":90,"name":"Experimental product","shortname":"~","description":null,"unit_id":7,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":91,"name":"Experimental product","shortname":"~","description":null,"unit_id":7,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":92,"name":"Experimental product","shortname":"~","description":null,"unit_id":7,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":93,"name":"Experimental product","shortname":"~","description":null,"unit_id":7,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":94,"name":"Experimental product","shortname":"~","description":null,"unit_id":7,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":95,"name":"Experimental product","shortname":"~","description":null,"unit_id":7,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":96,"name":"Experimental product","shortname":"~","description":null,"unit_id":7,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":97,"name":"Experimental product","shortname":"~","description":null,"unit_id":7,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":98,"name":"Experimental product","shortname":"~","description":null,"unit_id":7,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":99,"name":"Experimental product","shortname":"~","description":null,"unit_id":7,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":100,"name":"Experimental product","shortname":"~","description":null,"unit_id":7,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":101,"name":"Experimental product","shortname":"~","description":null,"unit_id":7,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":102,"name":"Experimental product","shortname":"~","description":null,"unit_id":7,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":103,"name":"Experimental product","shortname":"~","description":null,"unit_id":7,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":104,"name":"Experimental product","shortname":"~","description":null,"unit_id":7,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":105,"name":"Experimental product","shortname":"~","description":null,"unit_id":7,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":106,"name":"Experimental product","shortname":"~","description":null,"unit_id":7,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":107,"name":"Experimental product","shortname":"~","description":null,"unit_id":7,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":108,"name":"Experimental product","shortname":"~","description":null,"unit_id":7,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":109,"name":"Experimental product","shortname":"~","description":null,"unit_id":7,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":110,"name":"Experimental product","shortname":"~","description":null,"unit_id":7,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":111,"name":"Experimental product","shortname":"~","description":null,"unit_id":7,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":112,"name":"Experimental product","shortname":"~","description":null,"unit_id":7,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":113,"name":"Experimental product","shortname":"~","description":null,"unit_id":7,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":114,"name":"Experimental product","shortname":"~","description":null,"unit_id":7,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":115,"name":"Experimental product","shortname":"~","description":null,"unit_id":7,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":116,"name":"Experimental product","shortname":"~","description":null,"unit_id":7,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":117,"name":"Experimental product","shortname":"~","description":null,"unit_id":7,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":118,"name":"Experimental product","shortname":"~","description":null,"unit_id":7,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":119,"name":"Experimental product","shortname":"~","description":null,"unit_id":7,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":120,"name":"Experimental product","shortname":"~","description":null,"unit_id":7,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":121,"name":"Maximum temperature at 2 metres in the last 6 hours","shortname":"mx2t6","description":"The highest value of 2 metre temperature in the previous 6 hour period.
2m temperature is calculated by interpolating between the lowest model level and the Earth's surface, taking account of the atmospheric conditions. See further information.
This parameter has units of kelvin (K). Temperature measured in kelvin can be converted to degrees Celsius (°C) by subtracting 273.15.","unit_id":2,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":122,"name":"Minimum temperature at 2 metres in the last 6 hours","shortname":"mn2t6","description":"The lowest value of 2 metre temperature in the previous 6 hour period.
2m temperature is calculated by interpolating between the lowest model level and the Earth's surface, taking account of the atmospheric conditions. See further information.
This parameter has units of kelvin (K). Temperature measured in kelvin can be converted to degrees Celsius (°C) by subtracting 273.15.","unit_id":2,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":123,"name":"Maximum 10 metre wind gust in the last 6 hours","shortname":"10fg6","description":"This parameter is the maximum wind gust in the last 6 hours at a height of ten metres above the surface of the Earth.
The WMO defines a wind gust as the maximum of the wind averaged over 3 second intervals. This duration is shorter than a model time step, and so the ECMWF Integrated Forecasting System deduces the magnitude of a gust within each time step from the time-step-averaged surface stress, surface friction, wind shear and stability. Then, the maximum wind gust is selected from the gusts at each time step during the last 6 hours.
Care should be taken when comparing model parameters with observations, because observations are often local to a particular point in space and time, rather than representing averages over a model grid box and model time step.","unit_id":5,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":124,"name":"Surface emissivity","shortname":"emis","description":null,"unit_id":105,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":125,"name":"Vertically integrated total energy","shortname":"vite","description":"","unit_id":6,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":126,"name":"Generic parameter for sensitive area prediction","shortname":"~","description":"Originating centre dependent","unit_id":25,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":127,"name":"Atmospheric tide","shortname":"at","description":"Not GRIB data (pseudo-GRIB)","unit_id":7,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":128,"name":"Budget values","shortname":"bv","description":"Not GRIB data (pseudo-GRIB)","unit_id":7,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":129,"name":"Geopotential","shortname":"z","description":"
This parameter is the gravitational potential energy of a unit mass, at a particular location, relative to mean sea level. It is also the amount of work that would have to be done, against the force of gravity, to lift a unit mass to that location from mean sea level.
The geopotential height can be calculated by dividing the geopotential by the Earth's gravitational acceleration, g (=9.80665 m s-2). The geopotential height plays an important role in synoptic meteorology (analysis of weather patterns). Charts of geopotential height plotted at constant pressure levels (e.g., 300, 500 or 850 hPa) can be used to identify weather systems such as cyclones, anticyclones, troughs and ridges.
At the surface of the Earth, this parameter shows the variations in geopotential (height) of the surface, and is often referred to as the orography.
This parameter is the temperature in the atmosphere.
It has units of kelvin (K). Temperature measured in kelvin can be converted to degrees Celsius (°C) by subtracting 273.15.
This parameter is available on multiple levels through the atmosphere.
","unit_id":2,"encoding_ids":["grib1","grib2","netcdf"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":131,"name":"U component of wind","shortname":"u","description":"
This parameter is the eastward component of the wind. It is the horizontal speed of air moving towards the east, in metres per second. A negative sign thus indicates air movement towards the west.
This parameter can be combined with the V component of wind to give the speed and direction of the horizontal wind.
","unit_id":5,"encoding_ids":["grib1","grib2","netcdf"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":132,"name":"V component of wind","shortname":"v","description":"
This parameter is the northward component of the wind. It is the horizontal speed of air moving towards the north, in metres per second. A negative sign thus indicates air movement towards the south.
This parameter can be combined with the U component of wind to give the speed and direction of the horizontal wind.
This parameter is the mass of water vapour per kilogram of moist air.
The total mass of moist air is the sum of the dry air, water vapour, cloud liquid, cloud ice, rain and falling snow.
","unit_id":21,"encoding_ids":["grib1","grib2","netcdf"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":134,"name":"Surface pressure","shortname":"sp","description":"This parameter is the pressure (force per unit area) of the atmosphere on the surface of land, sea and in-land water.
It is a measure of the weight of all the air in a column vertically above the area of the Earth's surface represented at a fixed point.
Surface pressure is often used in combination with temperature to calculate air density.
The strong variation of pressure with altitude makes it difficult to see the low and high pressure systems over mountainous areas, so mean sea level pressure, rather than surface pressure, is normally used for this purpose.
The units of this parameter are Pascals (Pa). Surface pressure is often measured in hPa and sometimes is presented in the old units of millibars, mb (1 hPa = 1 mb= 100 Pa).","unit_id":16,"encoding_ids":["grib1","grib2","netcdf"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":135,"name":"Vertical velocity","shortname":"w","description":"This parameter is the speed of air motion in the upward or downward direction. The ECMWF Integrated Forecasting System (IFS) uses a pressure based vertical co-ordinate system and pressure decreases with height, therefore negative values of vertical velocity indicate upward motion.
Vertical velocity can be useful to understand the large-scale dynamics of the atmosphere, including areas of upward motion/ascent (negative values) and downward motion/subsidence (positive values).","unit_id":26,"encoding_ids":["grib1","grib2","netcdf"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":136,"name":"Total column water","shortname":"tcw","description":"This parameter is the sum of water vapour, liquid water, cloud ice, rain and snow in a column extending from the surface of the Earth to the top of the atmosphere. In old versions of the ECMWF model (IFS), rain and snow were not accounted for.","unit_id":22,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":137,"name":"Total column vertically-integrated water vapour","shortname":"tcwv","description":"This parameter is the total amount of water vapour in a column extending from the surface of the Earth to the top of the atmosphere.
This parameter represents the area averaged value for a grid box.","unit_id":22,"encoding_ids":["grib1","grib2","netcdf"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":138,"name":"Vorticity (relative)","shortname":"vo","description":"This parameter is a measure of the rotation of air in the horizontal, around a vertical axis, relative to a fixed point on the surface of the Earth.
On the scale of weather systems, troughs (weather features that can include rain) are associated with anticlockwise rotation (in the northern hemisphere), and ridges (weather features that bring light or still winds) are associated with clockwise rotation.
Adding the rotation of the Earth, the so-called Coriolis parameter, to the relative vorticity produces the absolute vorticity.","unit_id":8,"encoding_ids":["grib1","grib2","netcdf"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":139,"name":"Soil temperature level 1","shortname":"stl1","description":"This parameter is the temperature of the soil at level 1 (in the middle of layer 1).
The ECMWF Integrated Forecasting System (IFS) has a four-layer representation of soil, where the surface is at 0cm:
Soil temperature is set at the middle of each layer, and heat transfer is calculated at the interfaces between them. It is assumed that there is no heat transfer out of the bottom of the lowest layer.
This parameter has units of Kelvin (K). Temperature measured in Kelvin can be converted to degrees Celsius (°C) by subtracting 273.15.
See further information.","unit_id":2,"encoding_ids":["grib1","grib2","netcdf"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":140,"name":"Soil wetness level 1","shortname":"swl1","description":"Old field, layer 1-7 cm (new soil moisture is archived as field 39). Surface soil wetness (SSW) before 19930804","unit_id":27,"encoding_ids":["grib1","grib2","netcdf"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":141,"name":"Snow depth","shortname":"sd","description":"This parameter is the depth of snow from the snow-covered area of a grid box.
Its units are metres of water equivalent, so it is the depth the water would have if the snow melted and was spread evenly over the whole grid box. The ECMWF Integrated Forecast System represents snow as a single additional layer over the uppermost soil level. The snow may cover all or part of the grid box.
See further information.\r\n\r\n[NOTE: See 228141 for the equivalent parameter in \"kg m-2\"]","unit_id":27,"encoding_ids":["grib1","grib2","netcdf"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":142,"name":"Large-scale precipitation","shortname":"lsp","description":"This parameter is the accumulated liquid and frozen water, comprising rain and snow, that falls to the Earth's surface and which is generated by the cloud scheme in the ECMWF Integrated Forecasting System (IFS). The cloud scheme represents the formation and dissipation of clouds and large-scale precipitation due to changes in atmospheric quantities (such as pressure, temperature and moisture) predicted directly by the IFS at spatial scales of the grid box or larger. Precipitation can also be generated by the convection scheme in the IFS, which represents convection at spatial scales smaller than the grid box. See further information. This parameter does not include fog, dew or the precipitation that evaporates in the atmosphere before it lands at the surface of the Earth.
Care should be taken when comparing model parameters with observations, because observations are often local to a particular point in space and time, rather than representing averages over a model grid box.\n [NOTE: See 3062 for the equivalent parameter in \"kg m-2\"]","unit_id":4,"encoding_ids":["grib1","grib2","netcdf"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":143,"name":"Convective precipitation","shortname":"cp","description":"This parameter is the accumulated liquid and frozen water, comprising rain and snow, that falls to the Earth's surface and which is generated by the convection scheme in the ECMWF Integrated Forecasting System (IFS). The convection scheme represents convection at spatial scales smaller than the grid box. Precipitation can also be generated by the cloud scheme in the IFS, which represents the formation and dissipation of clouds and large-scale precipitation due to changes in atmospheric quantities (such as pressure, temperature and moisture) predicted directly at spatial scales of the grid box or larger. See further information. This parameter does not include fog, dew or the precipitation that evaporates in the atmosphere before it lands at the surface of the Earth.
Care should be taken when comparing model parameters with observations, because observations are often local to a particular point in space and time, rather than representing averages over a model grid box.\n [NOTE: See 228143 for the equivalent parameter in \"kg m-2\"]","unit_id":4,"encoding_ids":["grib1","grib2","netcdf"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":144,"name":"Snowfall","shortname":"sf","description":"This parameter is the accumulated snow that falls to the Earth's surface. It is the sum of large-scale snowfall and convective snowfall. Large-scale snowfall is generated by the cloud scheme in the ECMWF Integrated Forecasting System (IFS). The cloud scheme represents the formation and dissipation of clouds and large-scale precipitation due to changes in atmospheric quantities (such as pressure, temperature and moisture) predicted directly by the IFS at spatial scales of the grid box or larger. Convective snowfall is generated by the convection scheme in the IFS, which represents convection at spatial scales smaller than the grid box. See further information.
Care should be taken when comparing model parameters with observations, because observations are often local to a particular point in space and time, rather than representing averages over a model grid box.\n [NOTE: See 228144 for the equivalent parameter in \"kg m-2\"]","unit_id":27,"encoding_ids":["grib1","grib2","netcdf"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":145,"name":"Time-integrated boundary layer dissipation","shortname":"bld","description":"
This parameter is the amount of energy per unit area that is converted from kinetic energy, into heat, due to small-scale motion in the lower levels of the atmosphere. These small-scale motions are called eddies or turbulence. A higher value of this parameter means that more energy is being converted to heat, and so the mean flow is slowing more and the air temperature is rising by a greater amount.
","unit_id":6,"encoding_ids":["grib1","grib2","netcdf"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":146,"name":"Time-integrated surface sensible heat net flux","shortname":"sshf","description":"
This parameter is the transfer of heat between the Earth's surface and the atmosphere through the effects of turbulent air motion (but excluding any heat transfer resulting from condensation or evaporation).
The magnitude of the sensible heat flux is governed by the difference in temperature between the surface and the overlying atmosphere, wind speed and the surface roughness. For example, cold air overlying a warm surface would produce a sensible heat flux from the land (or ocean) into the atmosphere. See further documentation
This is a single level parameter and it is accumulated over a particular time period which depends on the data extracted.The units are joules per square metre (J m-2). To convert to watts per square metre (W m-2), the accumulated values should be divided by the accumulation period expressed in seconds. The ECMWF convention for vertical fluxes is positive downwards.
","unit_id":6,"encoding_ids":["grib1","grib2","netcdf"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":147,"name":"Time-integrated surface latent heat net flux","shortname":"slhf","description":"
This parameter is the transfer of latent heat (resulting from water phase changes, such as evaporation or condensation) between the Earth's surface and the atmosphere through the effects of turbulent air motion. Evaporation from the Earth's surface represents a transfer of energy from the surface to the atmosphere. See further documentation
This parameter is accumulated over a particular time period which depends on the data extracted.The units are joules per square metre (J m-2). To convert to watts per square metre (W m-2), the accumulated values should be divided by the accumulation period expressed in seconds.
The ECMWF convention for vertical fluxes is positive downwards.
","unit_id":6,"encoding_ids":["grib1","grib2","netcdf"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":148,"name":"Charnock","shortname":"chnk","description":"This parameter accounts for increased aerodynamic roughness as wave heights grow due to increasing surface stress. It depends on the wind speed, wave age and other aspects of the sea state and is used to calculate how much the waves slow down the wind.
When the atmospheric model is run without the ocean model, this parameter has a constant value of 0.018. When the atmospheric model is coupled to the ocean model, this parameter is calculated by the ECMWF Wave Model.\r\n ","unit_id":106,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":149,"name":"Surface net radiation (SW and LW)","shortname":"snr","description":"Accumulated field","unit_id":6,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":150,"name":"Top net radiation (SW and LW)","shortname":"tnr","description":"Accumulated field","unit_id":6,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":151,"name":"Mean sea level pressure","shortname":"msl","description":"This parameter is the pressure (force per unit area) of the atmosphere adjusted to the height of mean sea level.
It is a measure of the weight that all the air in a column vertically above the area of Earth's surface would have at that point, if the point were located at the mean sea level. It is calculated over all surfaces - land, sea and in-land water.
Maps of mean sea level pressure are used to identify the locations of low and high pressure systems, often referred to as cyclones and anticyclones. Contours of mean sea level pressure also indicate the strength of the wind. Tightly packed contours show stronger winds.
The units of this parameter are pascals (Pa). Mean sea level pressure is often measured in hPa and sometimes is presented in the old units of millibars, mb (1 hPa = 1 mb = 100 Pa).","unit_id":16,"encoding_ids":["grib1","grib2","netcdf"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":152,"name":"Logarithm of surface pressure","shortname":"lnsp","description":"This parameter is the natural logarithm of pressure (force per unit area) of the atmosphere on the surface of land, sea and inland water. Numerical weather prediction models often utilise the logarithm of surface pressure in their calculations.","unit_id":106,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":153,"name":"Short-wave heating rate","shortname":"swhr","description":"Accumulated field","unit_id":2,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":154,"name":"Long-wave heating rate","shortname":"lwhr","description":"Accumulated field","unit_id":2,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":155,"name":"Divergence","shortname":"d","description":"This parameter is the horizontal divergence of velocity. It is the rate at which air is spreading out horizontally from a point, per square metre. This parameter is positive for air that is spreading out, or diverging, and negative for the opposite, for air that is concentrating, or converging (convergence).","unit_id":8,"encoding_ids":["grib1","grib2","netcdf"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":156,"name":"Geopotential height","shortname":"gh","description":"This parameter is a measure of the height of a point in the atmosphere in relation to its potential energy. It is calculated by dividing the geopotential by the Earth's mean gravitational acceleration, g (=9.80665 m s-2). The geopotential is the gravitational potential energy of a unit mass, at a particular location, relative to mean sea level. Geopotential is also the amount of work that would have to be done, against the force of gravity, to lift a unit mass to that location from mean sea level.
This parameter plays an important role in synoptic meteorology (analysis of weather patterns). Charts of geopotential height plotted at constant pressure levels (e.g., 300, 500 or 850 hPa) can be used to identify weather systems such as cyclones, anticyclones, troughs and ridges. At the surface of the Earth, this parameter shows the variations in geopotential height of the surface, and is often referred to as the orography.
The units of this parameter are geopotential metres. A geopotential metre is approximately 2% shorter than a geometric metre.","unit_id":28,"encoding_ids":["grib1","grib2","netcdf"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":157,"name":"Relative humidity","shortname":"r","description":"This parameter is the water vapour pressure as a percentage of the value at which the air becomes saturated (the point at which water vapour begins to condense into liquid water or deposition into ice).
For temperatures over 0°C (273.15 K) it is calculated for saturation over water. At temperatures below -23°C it is calculated for saturation over ice. Between -23°C and 0°C this parameter is calculated by interpolating between the ice and water values using a quadratic function.
See more information about the model's relative humidity calculation.","unit_id":29,"encoding_ids":["grib1","grib2","netcdf"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":158,"name":"Tendency of surface pressure","shortname":"tsp","description":null,"unit_id":26,"encoding_ids":["grib1","grib2","netcdf"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":159,"name":"Boundary layer height","shortname":"blh","description":"This parameter is the depth of air next to the Earth's surface which is most affected by the resistance to the transfer of momentum, heat or moisture across the surface.
The boundary layer height can be as low as a few tens of metres, such as in cooling air at night, or as high as several kilometres over the desert in the middle of a hot sunny day. When the boundary layer height is low, higher concentrations of pollutants (emitted from the Earth's surface) can develop.
The boundary layer height calculation is based on the bulk Richardson number (a measure of the atmospheric conditions) following the conclusions of a 2012 review. See further information.","unit_id":4,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":160,"name":"Standard deviation of sub-gridscale orography","shortname":"sdor","description":"This parameter is one of four parameters (the others being angle of sub-gridscale orography, slope and anisotropy) that describe the features of the orography that are too small to be resolved by the model grid. These four parameters are calculated for orographic features with horizontal scales comprised between 5 km and the model grid resolution, being derived from the height of valleys, hills and mountains at about 1 km resolution. They are used as input for the sub-grid orography scheme which represents low-level blocking and orographic gravity wave effects.
This parameter represents the standard deviation of the height of the sub-grid valleys, hills and mountains within a grid box.","unit_id":4,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":161,"name":"Anisotropy of sub-gridscale orography","shortname":"isor","description":"This parameter is one of four parameters (the others being standard deviation, slope and angle of sub-gridscale orography) that describe the features of the orography that are too small to be resolved by the model grid. These four parameters are calculated for orographic features with horizontal scales comprised between 5 km and the model grid resolution, being derived from the height of valleys, hills and mountains at about 1 km resolution. They are used as input for the sub-grid orography scheme which represents low-level blocking and orographic gravity wave effects.
This parameter is a measure of how much the shape of the terrain in the horizontal plane (from a bird's-eye view) is distorted from a circle.
A value of one is a circle, less than one an ellipse, and 0 is a ridge. In the case of a ridge, wind blowing parallel to it does not exert any drag on the flow, but wind blowing perpendicular to it exerts the maximum drag.","unit_id":106,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":162,"name":"Angle of sub-gridscale orography","shortname":"anor","description":"This parameter is one of four parameters (the others being standard deviation, slope and anisotropy) that describe the features of the orography that are too small to be resolved by the model grid. These four parameters are calculated for orographic features with horizontal scales comprised between 5 km and the model grid resolution, being derived from the height of valleys, hills and mountains at about 1 km resolution. They are used as input for the sub-grid orography scheme which represents low-level blocking and orographic gravity wave effects.
The angle of the sub-grid scale orography characterises the geographical orientation of the terrain in the horizontal plane (from a bird's-eye view) relative to an eastwards axis.","unit_id":30,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":163,"name":"Slope of sub-gridscale orography","shortname":"slor","description":"This parameter is one of four parameters (the others being standard deviation, angle and anisotropy) that describe the features of the orography that are too small to be resolved by the model grid. These four parameters are calculated for orographic features with horizontal scales comprised between 5 km and the model grid resolution, being derived from the height of valleys, hills and mountains at about 1 km resolution. They are used as input for the sub-grid orography scheme which represents low-level blocking and orographic gravity wave effects.
This parameter represents the slope of the sub-grid valleys, hills and mountains. A flat surface has a value of 0, and a 45 degree slope has a value of 0.5.","unit_id":106,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":164,"name":"Total cloud cover","shortname":"tcc","description":"This parameter is the proportion of a grid box covered by cloud. Total cloud cover is a single level field calculated from the cloud occurring at different model levels through the atmosphere. Assumptions are made about the degree of overlap/randomness between clouds at different heights.
Cloud fractions vary from 0 to 1.\n [NOTE: See 228164 for the equivalent parameter in \"%\"]","unit_id":3,"encoding_ids":["grib1","grib2","netcdf"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":165,"name":"10 metre U wind component","shortname":"10u","description":"This parameter is the eastward component of the 10m wind. It is the horizontal speed of air moving towards the east, at a height of ten metres above the surface of the Earth, in metres per second.
Care should be taken when comparing this parameter with observations, because wind observations vary on small space and time scales and are affected by the local terrain, vegetation and buildings that are represented only on average in the ECMWF Integrated Forecasting System.
This parameter can be combined with the V component of 10m wind to give the speed and direction of the horizontal 10m wind.","unit_id":5,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":166,"name":"10 metre V wind component","shortname":"10v","description":"This parameter is the northward component of the 10m wind. It is the horizontal speed of air moving towards the north, at a height of ten metres above the surface of the Earth, in metres per second.
Care should be taken when comparing this parameter with observations, because wind observations vary on small space and time scales and are affected by the local terrain, vegetation and buildings that are represented only on average in the ECMWF Integrated Forecasting System.
This parameter can be combined with the U component of 10m wind to give the speed and direction of the horizontal 10m wind.","unit_id":5,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":167,"name":"2 metre temperature","shortname":"2t","description":"This parameter is the temperature of air at 2m above the surface of land, sea or in-land waters.
2m temperature is calculated by interpolating between the lowest model level and the Earth's surface, taking account of the atmospheric conditions. See further information .
This parameter has units of kelvin (K). Temperature measured in kelvin can be converted to degrees Celsius (°C) by subtracting 273.15.
Please note that the encodings listed here for s2s & uerra (which includes encodings for carra/cerra) include entries for Mean 2 metre temperature. The specific encoding for Mean 2 metre temperature can be found in 228004.","unit_id":2,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":168,"name":"2 metre dewpoint temperature","shortname":"2d","description":"This parameter is the temperature to which the air, at 2 metres above the surface of the Earth, would have to be cooled for saturation to occur.
It is a measure of the humidity of the air. Combined with temperature and pressure, it can be used to calculate the relative humidity.
2m dew point temperature is calculated by interpolating between the lowest model level and the Earth's surface, taking account of the atmospheric conditions. See further information.This parameter has units of kelvin (K). Temperature measured in kelvin can be converted to degrees Celsius (°C) by subtracting 273.15.","unit_id":2,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":169,"name":"Surface short-wave (solar) radiation downwards","shortname":"ssrd","description":"This parameter is the amount of solar radiation (also known as shortwave radiation) that reaches a horizontal plane at the surface of the Earth. This parameter comprises both direct and diffuse solar radiation.
Radiation from the Sun (solar, or shortwave, radiation) is partly reflected back to space by clouds and particles in the atmosphere (aerosols) and some of it is absorbed. The rest is incident on the Earth's surface (represented by this parameter). See further documentation.
To a reasonably good approximation, this parameter is the model equivalent of what would be measured by a pyranometer (an instrument used for measuring solar radiation) at the surface. However, care should be taken when comparing model parameters with observations, because observations are often local to a particular point in space and time, rather than representing averages over a model grid box.
This parameter is accumulated over a particular time period which depends on the data extracted. The units are joules per square metre (J m-2). To convert to watts per square metre (W m-2), the accumulated values should be divided by the accumulation period expressed in seconds. The ECMWF convention for vertical fluxes is positive downwards.","unit_id":6,"encoding_ids":["grib1","grib2","netcdf"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":170,"name":"Soil temperature level 2","shortname":"stl2","description":"This parameter is the temperature of the soil at level 2 (in the middle of layer 2).
The ECMWF Integrated Forecasting System (IFS) has a four-layer representation of soil, where the surface is at 0cm:
Soil temperature is set at the middle of each layer, and heat transfer is calculated at the interfaces between them. It is assumed that there is no heat transfer out of the bottom of the lowest layer.
This parameter has units of Kelvin (K). Temperature measured in Kelvin can be converted to degrees Celsius (°C) by subtracting 273.15.
See further information.","unit_id":2,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":171,"name":"Soil wetness level 2","shortname":"swl2","description":"Old field Layer 7-28 cm (new soil moisture is archived as field 40). Deep soil wetness (DSW) before 19930804. Water column scaled to depth of surf layer (7 cm).","unit_id":27,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":172,"name":"Land-sea mask","shortname":"lsm","description":"This parameter is the proportion of land, as opposed to ocean or inland waters (lakes, reservoirs, rivers and coastal waters), in a grid box. \nThis parameter has values ranging between zero and one and is dimensionless. \nIn cycles of the ECMWF Integrated Forecasting System (IFS) from CY41R1 (introduced in May 2015) onwards, grid boxes where this parameter has a value above 0.5 can be comprised of a mixture of land and inland water but not ocean. Grid boxes with a value of 0.5 and below can only be comprised of a water surface. In the latter case, the lake cover is used to determine how much of the water surface is ocean or inland water.\n In cycles of the IFS before CY41R1, grid boxes where this parameter has a value above 0.5 can only be comprised of land and those grid boxes with a value of 0.5 and below can only be comprised of ocean. In these older model cycles, there is no differentiation between ocean and inland water.","unit_id":3,"encoding_ids":["grib1","grib2","netcdf"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":173,"name":"Surface roughness (climatological)","shortname":"sr","description":"Aerodynamic roughness length (over land). Climatological field.","unit_id":4,"encoding_ids":["grib1","grib2","netcdf"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":174,"name":"Albedo (climatological)","shortname":"al","description":"This parameter is a measure of the reflectivity of the Earth's surface. It is the fraction of solar (shortwave) radiation reflected by Earth's surface, across the solar spectrum, for both direct and diffuse radiation.
This parameter is a climatological (observed values averaged over a period of several years) background albedo which varies through the year and which excludes values over snow and sea-ice. Over land, values are typically between about 0.1 and 0.4 and the ocean has low values of 0.1 or less.
Note: this parameter is a very old broadband albedo climatology that has since been replaced by a MODIS climatology in two spectral bands (see parameters 210186 to 210191).
Radiation from the Sun (also known as solar, or shortwave, radiation) is partly reflected back to space by clouds and particles in the atmosphere (aerosols) and some of it is absorbed. The rest is incident on the Earth's surface, where some of it is reflected. The portion that is reflected by the Earth's surface depends on the albedo. See further documentation.
This parameter is calculated as a fraction (0 - 1), but albedo is sometimes shown as a percentage (%).","unit_id":3,"encoding_ids":["grib1","grib2","netcdf"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":175,"name":"Surface long-wave (thermal) radiation downwards","shortname":"strd","description":"This parameter is the amount of thermal (also known as longwave or terrestrial) radiation emitted by the atmosphere and clouds that reaches a horizontal plane at the surface of the Earth.
The surface of the Earth emits thermal radiation, some of which is absorbed by the atmosphere and clouds. The atmosphere and clouds likewise emit thermal radiation in all directions, some of which reaches the surface (represented by this parameter). See further documentation.
This parameter is accumulated over a particular time period which depends on the data extracted. The units are joules per square metre (J m-2). To convert to watts per square metre (W m-2), the accumulated values should be divided by the accumulation period expressed in seconds. The ECMWF convention for vertical fluxes is positive downwards.","unit_id":6,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":176,"name":"Surface net short-wave (solar) radiation","shortname":"ssr","description":"This parameter is the amount of solar radiation (also known as shortwave radiation) that reaches a horizontal plane at the surface of the Earth (both direct and diffuse) minus the amount reflected by the Earth's surface (which is governed by the albedo).
Radiation from the Sun (solar, or shortwave, radiation) is partly reflected back to space by clouds and particles in the atmosphere (aerosols) and some of it is absorbed. The remainder is incident on the Earth's surface, where some of it is reflected. See further documentation.
This parameter is accumulated over a particular time period which depends on the data extracted. The units are joules per square metre (J m-2). To convert to watts per square metre (W m-2), the accumulated values should be divided by the accumulation period expressed in seconds. The ECMWF convention for vertical fluxes is positive downwards.","unit_id":6,"encoding_ids":["grib1","grib2","netcdf"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":177,"name":"Surface net long-wave (thermal) radiation","shortname":"str","description":"Thermal radiation (also known as longwave or terrestrial radiation) refers to radiation emitted by the atmosphere, clouds and the surface of the Earth. This parameter is the difference between downward and upward thermal radiation at the surface of the Earth. It the amount passing through a horizontal plane.
The atmosphere and clouds emit thermal radiation in all directions, some of which reaches the surface as downward thermal radiation. The upward thermal radiation at the surface consists of thermal radiation emitted by the surface plus the fraction of downwards thermal radiation reflected upward by the surface. See further documentation.
This parameter is accumulated over a particular time period which depends on the data extracted. The units are joules per square metre (J m-2). To convert to watts per square metre (W m-2), the accumulated values should be divided by the accumulation period expressed in seconds.
The ECMWF convention for vertical fluxes is positive downwards.","unit_id":6,"encoding_ids":["grib1","grib2","netcdf"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":178,"name":"Top net short-wave (solar) radiation","shortname":"tsr","description":"This parameter is the incoming solar radiation (also known as shortwave radiation) minus the outgoing solar radiation at the top of the atmosphere. It is the amount of radiation passing through a horizontal plane. The incoming solar radiation is the amount received from the Sun. The outgoing solar radiation is the amount reflected and scattered by the Earth's atmosphere and surface. See further documentation.
This parameter is accumulated over a particular time period which depends on the data extracted. The units are joules per square metre (J m-2). To convert to watts per square metre (W m-2), the accumulated values should be divided by the accumulation period expressed in seconds.
The ECMWF convention for vertical fluxes is positive downwards.","unit_id":6,"encoding_ids":["grib1","grib2","netcdf"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":179,"name":"Top net long-wave (thermal) radiation","shortname":"ttr","description":"The thermal (also known as terrestrial or longwave) radiation emitted to space at the top of the atmosphere is commonly known as the Outgoing Longwave Radiation (OLR). The top net thermal radiation (this parameter) is equal to the negative of OLR. See further documentation.
This parameter is accumulated over a particular time period which depends on the data extracted. The units are joules per square metre (J m-2). To convert to watts per square metre (W m-2), the accumulated values should be divided by the accumulation period expressed in seconds.The ECMWF convention for vertical fluxes is positive downwards.","unit_id":6,"encoding_ids":["grib1","grib2","netcdf"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":180,"name":"Time-integrated eastward turbulent surface stress","shortname":"ewss","description":"Air flowing over a surface exerts a stress that transfers momentum to the surface and slows the wind. This parameter is the accumulated stress on the Earth's surface in the eastward direction due to both the turbulent interactions between the atmosphere and the surface, and to turbulent orographic form drag. The turbulent interactions between the atmosphere and the surface are due to the roughness of the surface. The turbulent orographic form drag is the stress due to the valleys, hills and mountains on horizontal scales below 5km being derived from land surface data at about 1 km resolution. See further information.
Positive (negative) values denote stress in the eastward (westward) direction.
This parameter is accumulated over a particular time period which depends on the data extracted.","unit_id":14,"encoding_ids":["grib1","grib2","netcdf"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":181,"name":"Time-integrated northward turbulent surface stress","shortname":"nsss","description":"Air flowing over a surface exerts a stress that transfers momentum to the surface and slows the wind. This parameter is the accumulated stress on the Earth's surface in the northward direction due to both the turbulent interactions between the atmosphere and the surface, and to turbulent orographic form drag.
The turbulent interactions between the atmosphere and the surface are due to the roughness of the surface.
The turbulent orographic form drag is the stress due to the valleys, hills and mountains on horizontal scales below 5km being derived from land surface data at about 1 km resolution. See further information.
Positive (negative) values denote stress in the northward (southward) direction.
This parameter is accumulated over a particular time period which depends on the data extracted.","unit_id":14,"encoding_ids":["grib1","grib2","netcdf"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":182,"name":"Evaporation","shortname":"e","description":"This parameter is the accumulated amount of water that has evaporated from the Earth's surface, including a simplified representation of transpiration (from vegetation), into vapour in the air above.
The ECMWF Integrated Forecasting System convention is that downward fluxes are positive. Therefore, negative values indicate evaporation and positive values indicate condensation.\n [NOTE: See 260259 for the equivalent parameter in \"kg m-2\"]","unit_id":27,"encoding_ids":["grib1","grib2","netcdf"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":183,"name":"Soil temperature level 3","shortname":"stl3","description":"This parameter is the temperature of the soil at level 3 (in the middle of layer 3).
The ECMWF Integrated Forecasting System (IFS) has a four-layer representation of soil, where the surface is at 0cm:
Soil temperature is set at the middle of each layer, and heat transfer is calculated at the interfaces between them. It is assumed that there is no heat transfer out of the bottom of the lowest layer.
This parameter has units of Kelvin (K). Temperature measured in Kelvin can be converted to degrees Celsius (°C) by subtracting 273.15.
See further information.","unit_id":2,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":184,"name":"Soil wetness level 3","shortname":"swl3","description":"Old field Layer 28-100 cm (new soil moisture is archived as field 41). Climatological deep soil wetness (CDSW) before 19930804. Water column scaled to depth of surf layer (7 cm).","unit_id":27,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":185,"name":"Convective cloud cover","shortname":"ccc","description":null,"unit_id":3,"encoding_ids":["grib1","grib2","netcdf"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":186,"name":"Low cloud cover","shortname":"lcc","description":"This parameter is the proportion of a grid box covered by cloud occurring in the lower levels of the troposphere. Low cloud is a single level field calculated from cloud occurring on model levels with a pressure greater than 0.8 times the surface pressure. So, if the surface pressure is 1000 hPa (hectopascal), low cloud would be calculated using levels with a pressure greater than 800 hPa (below approximately 2km (assuming a 'standard atmosphere')).
The low cloud cover parameter is calculated from cloud cover for the appropriate model levels as described above. Assumptions are made about the degree of overlap/randomness between clouds in different model levels.
Cloud fractions vary from 0 to 1.\n [NOTE: See 3073 for the equivalent parameter in \"%\"]","unit_id":3,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":187,"name":"Medium cloud cover","shortname":"mcc","description":"This parameter is the proportion of a grid box covered by cloud occurring in the middle levels of the troposphere. Medium cloud is a single level field calculated from cloud occurring on model levels with a pressure between 0.45 and 0.8 times the surface pressure. So, if the surface pressure is 1000 hPa (hectopascal), medium cloud would be calculated using levels with a pressure of less than or equal to 800 hPa and greater than or equal to 450 hPa (between approximately 2km and 6km (assuming a 'standard atmosphere')).
The medium cloud parameter is calculated from cloud cover for the appropriate model levels as described above. Assumptions are made about the degree of overlap/randomness between clouds in different model levels.
Cloud fractions vary from 0 to 1.\n [NOTE: See 3074 for the equivalent parameter in \"%\"]","unit_id":3,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":188,"name":"High cloud cover","shortname":"hcc","description":"The proportion of a grid box covered by cloud occurring in the high levels of the troposphere. High cloud is a single level field calculated from cloud occurring on model levels with a pressure less than 0.45 times the surface pressure. So, if the surface pressure is 1000 hPa (hectopascal), high cloud would be calculated using levels with a pressure of less than 450 hPa (approximately 6km and above ( assuming a `standard atmosphere`)).
The high cloud cover parameter is calculated from cloud for the appropriate model levels as described above. Assumptions are made about the degree of overlap/randomness between clouds in different model levels.
Cloud fractions vary from 0 to 1.\n [NOTE: See 3075 for the equivalent parameter in \"%\"]","unit_id":3,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":189,"name":"Sunshine duration","shortname":"sund","description":"This parameter is the length of time in which the direct solar (shortwave) radiation at the Earth's surface, falling on a plane perpendicular to the direction of the Sun, is greater than or equal to 120 W m-2.
The minimum solar intensity level of 120 W m-2 is defined by the World Meteorological Organisation and is consistent with observed values of sunshine duration from a Campbell-Stokes recorder (sometimes called a Stokes sphere) that can only measure moderately intense sunlight and brighter.
This parameter is accumulated over a particular time period which depends on the data extracted.","unit_id":12,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":190,"name":"East-West component of sub-gridscale orographic variance","shortname":"ewov","description":null,"unit_id":31,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":191,"name":"North-South component of sub-gridscale orographic variance","shortname":"nsov","description":null,"unit_id":31,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":192,"name":"North-West/South-East component of sub-gridscale orographic variance","shortname":"nwov","description":null,"unit_id":31,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":193,"name":"North-East/South-West component of sub-gridscale orographic variance","shortname":"neov","description":null,"unit_id":31,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":194,"name":"Brightness temperature","shortname":"btmp","description":null,"unit_id":2,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":195,"name":"Eastward gravity wave surface stress","shortname":"lgws","description":"Air flowing over a surface exerts a stress that transfers momentum to the surface and slows the wind. This parameter is the component of the surface stress, in an eastward direction, associated with low-level blocking and orographic gravity waves. It is calculated by the ECMWF Integrated Forecasting System sub-grid orography scheme. It represents surface stress due to unresolved valleys, hills and mountains with horizontal scales between 5 km and the model grid. (The surface stress associated with orographic features with horizontal scales smaller than 5 km is accounted for by the turbulent orographic form drag scheme).
Orographic gravity waves are oscillations in the flow maintained by the buoyancy of displaced air parcels, produced when the air is deflected upwards by hills and mountains. Hills and mountains can also block the flow of air at low levels. Together these processes can create a drag or stress on the atmosphere at the Earth's surface (and at other levels in the atmosphere).
This parameter is accumulated over a particular time period which depends on the data extracted.","unit_id":14,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":196,"name":"Northward gravity wave surface stress","shortname":"mgws","description":"Air flowing over a surface exerts a stress that transfers momentum to the surface and slows the wind. This parameter is the component of the surface stress, in a northward direction, associated with low-level blocking and orographic gravity waves. It is calculated by the ECMWF Integrated Forecasting System sub-grid orography scheme. It represents surface stress due to unresolved valleys, hills and mountains with horizontal scales between 5 km and the model grid. (The surface stress associated with orographic features with horizontal scales smaller than 5 km is accounted for by the turbulent orographic form drag scheme). The stress computed in the sub-grid orography scheme is associated with low-level blocking and orographic gravity waves.
Orographic gravity waves are oscillations in the flow maintained by the buoyancy of displaced air parcels, produced when the air is deflected upwards by hills and mountains. Hills and mountains can also block the flow of air at low levels. Together these processes can create a drag or stress on the atmosphere at the Earth's surface (and at other levels in the atmosphere).
This parameter is accumulated over a particular time period which depends on the data extracted.","unit_id":14,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":197,"name":"Gravity wave dissipation","shortname":"gwd","description":"This parameter is the amount of energy per unit area that is converted from kinetic energy in the mean flow, into heat, due to the effects of orographic gravity waves. A higher value of this parameter means that more energy is being converted to heat, and so the mean flow is slowing more and the air temperature is rising by a greater amount.
Orographic gravity waves are oscillations in the flow maintained by the buoyancy of displaced air parcels, produced when the air is deflected upwards by hills and mountains. Hills and mountains can also block the flow of air at low levels. Together these processes can create a drag or stress on the atmosphere at the Earth's surface (and at other levels in the atmosphere).
This parameter is accumulated over a particular time period which depends on the data extracted.","unit_id":6,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":198,"name":"Skin reservoir content","shortname":"src","description":"This parameter is the amount of water in the vegetation canopy and/or in a thin layer on the soil.
It represents the amount of rain intercepted by foliage, and water from dew. The maximum amount of 'skin reservoir content' a grid box can hold depends on the type of vegetation, and may be zero. Water leaves the 'skin reservoir' by evaporation.
See further information.","unit_id":27,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":199,"name":"Vegetation fraction","shortname":"veg","description":null,"unit_id":3,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":200,"name":"Variance of sub-gridscale orography","shortname":"vso","description":null,"unit_id":31,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":201,"name":"Maximum temperature at 2 metres since previous post-processing","shortname":"mx2t","description":"This parameter is the highest temperature of air at 2m above the surface of land, sea or in-land waters since the parameter was last archived in a particular forecast.
2m temperature is calculated by interpolating between the lowest model level and the Earth's surface, taking account of the atmospheric conditions. See further information .
This parameter has units of kelvin (K). Temperature measured in kelvin can be converted to degrees Celsius (°C) by subtracting 273.15.","unit_id":2,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":202,"name":"Minimum temperature at 2 metres since previous post-processing","shortname":"mn2t","description":"This parameter is the lowest temperature of air at 2m above the surface of land, sea or in-land waters since the parameter was last archived in a particular forecast.
2m temperature is calculated by interpolating between the lowest model level and the Earth's surface, taking account of the atmospheric conditions. See further information .
This parameter has units of kelvin (K). Temperature measured in kelvin can be converted to degrees Celsius (°C) by subtracting 273.15.","unit_id":2,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":203,"name":"Ozone mass mixing ratio","shortname":"o3","description":"This parameter is the mass of ozone per kilogram of air.
In the ECMWF Integrated Forecasting System (IFS), there is a simplified representation of ozone chemistry (including representation of the chemistry which has caused the ozone hole). Ozone is also transported around in the atmosphere through the motion of air. See further documentation.
Naturally occurring ozone in the stratosphere helps protect organisms at the surface of the Earth from the harmful effects of ultraviolet (UV) radiation from the Sun. Ozone near the surface, often produced because of pollution, is harmful to organisms.
Most of the IFS chemical species are archived as mass mixing ratios [kg kg-1]. This link explains how to convert to concentration in terms of mass per unit volume.","unit_id":21,"encoding_ids":["grib1","grib2","netcdf"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":204,"name":"Precipitation analysis weights","shortname":"paw","description":null,"unit_id":7,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":205,"name":"Runoff","shortname":"ro","description":"Some water from rainfall, melting snow, or deep in the soil, stays stored in the soil. Otherwise, the water drains away, either over the surface (surface runoff), or under the ground (sub-surface runoff) and the sum of these two is simply called 'runoff'. This parameter is the total amount of water accumulated over a particular time period which depends on the data extracted.The units of runoff are depth in metres. This is the depth the water would have if it were spread evenly over the grid box. Care should be taken when comparing model parameters with observations, because observations are often local to a particular point rather than averaged over a grid square area. Observations are also often taken in different units, such as mm/day, rather than the accumulated metres produced here.
Runoff is a measure of the availability of water in the soil, and can, for example, be used as an indicator of drought or flood. More information about how runoff is calculated is given in the IFS Physical Processes documentation.\n [NOTE: See 231002 for the equivalent parameter in \"kg m-2\"]","unit_id":4,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":206,"name":"Total column ozone","shortname":"tco3","description":"This parameter is the total amount of ozone in a column of air extending from the surface of the Earth to the top of the atmosphere. This parameter can also be referred to as total ozone, or vertically integrated ozone. The values are dominated by ozone within the stratosphere.
In the ECMWF Integrated Forecasting System (IFS), there is a simplified representation of ozone chemistry (including representation of the chemistry which has caused the ozone hole). Ozone is also transported around in the atmosphere through the motion of air. See further documentation .
Naturally occurring ozone in the stratosphere helps protect organisms at the surface of the Earth from the harmful effects of ultraviolet (UV) radiation from the Sun. Ozone near the surface, often produced because of pollution, is harmful to organisms.
In the IFS, the units for total ozone are kilograms per square metre, but before 12/06/2001 dobson units were used. Dobson units (DU) are still used extensively for total column ozone. 1 DU = 2.1415E-5 kg m-2\r\n\r\n[NOTE: See 260132 for the equivalent parameter in 'DU']","unit_id":22,"encoding_ids":["grib1","grib2","netcdf"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":207,"name":"10 metre wind speed","shortname":"10si","description":"This parameter is the horizontal speed of the wind, or movement of air, at a height of ten metres above the surface of the Earth. The units of this parameter are metres per second.
Care should be taken when comparing this parameter with observations, because wind observations vary on small space and time scales and are affected by the local terrain, vegetation and buildings that are represented only on average in the ECMWF Integrated Forecasting System.
The eastward and northward components of the horizontal wind at 10m are also available as parameters.","unit_id":5,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":208,"name":"Top net short-wave (solar) radiation, clear sky","shortname":"tsrc","description":"This parameter is the incoming solar radiation (also known as shortwave radiation) minus the outgoing solar radiation at the top of the atmosphere, assuming clear-sky (cloudless) conditions. It is the amount of radiation passing through a horizontal plane. The incoming solar radiation is the amount received from the Sun. The outgoing solar radiation is the amount reflected and scattered by the Earth's atmosphere and surface, assuming clear-sky (cloudless) conditions. See further documentation.
Clear-sky radiation quantities are computed for exactly the same atmospheric conditions of temperature, humidity, ozone, trace gases and aerosol as the total-sky (clouds included) quantities, but assuming that the clouds are not there.
This parameter is accumulated over a particular time period which depends on the data extracted. The units are joules per square metre (J m-2). To convert to watts per square metre (W m-2), the accumulated values should be divided by the accumulation period expressed in seconds.
The ECMWF convention for vertical fluxes is positive downwards.","unit_id":6,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":209,"name":"Top net long-wave (thermal) radiation, clear sky","shortname":"ttrc","description":"This parameter is the thermal (also known as terrestrial or longwave) radiation emitted to space at the top of the atmosphere, assuming clear-sky (cloudless) conditions. It is the amount passing through a horizontal plane. Note that the ECMWF convention for vertical fluxes is positive downwards, so a flux from the atmosphere to space will be negative. See further documentation.
Clear-sky radiation quantities are computed for exactly the same atmospheric conditions of temperature, humidity, ozone, trace gases and aerosol as total-sky quantities (clouds included), but assuming that the clouds are not there.
The thermal radiation emitted to space at the top of the atmosphere is commonly known as the Outgoing Longwave Radiation (OLR) (i.e., taking a flux from the atmosphere to space as positive). Note that OLR is typically shown in units of watts per square metre (W m-2).
This parameter is accumulated over a particular time period which depends on the data extracted. The units are joules per square metre (J m-2). To convert to watts per square metre (W m-2), the accumulated values should be divided by the accumulation period expressed in seconds.","unit_id":6,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":210,"name":"Surface net short-wave (solar) radiation, clear sky","shortname":"ssrc","description":"This parameter is the amount of solar (shortwave) radiation reaching the surface of the Earth (both direct and diffuse) minus the amount reflected by the Earth's surface (which is governed by the albedo), assuming clear-sky (cloudless) conditions. It is the amount of radiation passing through a horizontal plane, not a plane perpendicular to the direction of the Sun.
Clear-sky radiation quantities are computed for exactly the same atmospheric conditions of temperature, humidity, ozone, trace gases and aerosol as the corresponding total-sky quantities (clouds included), but assuming that the clouds are not there.
Radiation from the Sun (solar, or shortwave, radiation) is partly reflected back to space by clouds and particles in the atmosphere (aerosols) and some of it is absorbed. The rest is incident on the Earth's surface, where some of it is reflected. The difference between downward and reflected solar radiation is the surface net solar radiation. See further documentation.
This parameter is accumulated over a particular time period which depends on the data extracted. The units are joules per square metre (J m-2). To convert to watts per square metre (W m-2), the accumulated values should be divided by the accumulation period expressed in seconds.
The ECMWF convention for vertical fluxes is positive downwards.","unit_id":6,"encoding_ids":["grib1","grib2","netcdf"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":211,"name":"Surface net long-wave (thermal) radiation, clear sky","shortname":"strc","description":"Thermal radiation (also known as longwave or terrestrial radiation) refers to radiation emitted by the atmosphere, clouds and the surface of the Earth. This parameter is the difference between downward and upward thermal radiation at the surface of the Earth, assuming clear-sky (cloudless) conditions. It is the amount of radiation passing through a horizontal plane. See further documentation.
Clear-sky radiation quantities are computed for exactly the same atmospheric conditions of temperature, humidity, ozone, trace gases and aerosol as the corresponding total-sky quantities (clouds included), but assuming that the clouds are not there.
The atmosphere and clouds emit thermal radiation in all directions, some of which reaches the surface as downward thermal radiation. The upward thermal radiation at the surface consists of thermal radiation emitted by the surface plus the fraction of downwards thermal radiation reflected upward by the surface. See further documentation.
This parameter is accumulated over a particular time period which depends on the data extracted. The units are joules per square metre (J m-2). To convert to watts per square metre (W m-2), the accumulated values should be divided by the accumulation period expressed in seconds.
The ECMWF convention for vertical fluxes is positive downwards. ","unit_id":6,"encoding_ids":["grib1","grib2","netcdf"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":212,"name":"TOA incident short-wave (solar) radiation","shortname":"tisr","description":"Accumulated field","unit_id":6,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":213,"name":"Vertically integrated moisture divergence","shortname":"vimd","description":"The vertical integral of the moisture flux is the horizontal rate of flow of moisture (water vapour, cloud liquid and cloud ice), per metre across the flow, for a column of air extending from the surface of the Earth to the top of the atmosphere. Its horizontal divergence is the rate of moisture spreading outward from a point, per square metre.
This parameter is positive for moisture that is spreading out, or diverging, and negative for the opposite, for moisture that is concentrating, or converging (convergence). This parameter thus indicates whether atmospheric motions act to decrease (for divergence) or increase (for convergence) the vertical integral of moisture, over the time period. High negative values of this parameter (i.e. large moisture convergence) can be related to precipitation intensification and floods.
1 kg of water spread over 1 square metre of surface is 1 mm deep (neglecting the effects of temperature on the density of water), therefore the units are equivalent to mm.","unit_id":22,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":214,"name":"Diabatic heating by radiation","shortname":"dhr","description":null,"unit_id":2,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":215,"name":"Diabatic heating by vertical diffusion","shortname":"dhvd","description":null,"unit_id":2,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":216,"name":"Diabatic heating by cumulus convection","shortname":"dhcc","description":null,"unit_id":2,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":217,"name":"Diabatic heating large-scale condensation","shortname":"dhlc","description":null,"unit_id":2,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":218,"name":"Vertical diffusion of zonal wind","shortname":"vdzw","description":null,"unit_id":5,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":219,"name":"Vertical diffusion of meridional wind","shortname":"vdmw","description":null,"unit_id":5,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":220,"name":"East-West gravity wave drag tendency","shortname":"ewgd","description":null,"unit_id":5,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":221,"name":"North-South gravity wave drag tendency","shortname":"nsgd","description":null,"unit_id":5,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":222,"name":"Convective tendency of zonal wind","shortname":"ctzw","description":null,"unit_id":5,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":223,"name":"Convective tendency of meridional wind","shortname":"ctmw","description":null,"unit_id":5,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":224,"name":"Vertical diffusion of humidity","shortname":"vdh","description":null,"unit_id":21,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":225,"name":"Humidity tendency by cumulus convection","shortname":"htcc","description":null,"unit_id":21,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":226,"name":"Humidity tendency by large-scale condensation","shortname":"htlc","description":null,"unit_id":21,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":227,"name":"Tendency due to removal of negative humidity","shortname":"crnh","description":null,"unit_id":21,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":228,"name":"Total precipitation","shortname":"tp","description":"This parameter is the accumulated liquid and frozen water, comprising rain and snow, that falls to the Earth's surface. It is the sum of large-scale precipitation and convective precipitation. Large-scale precipitation is generated by the cloud scheme in the ECMWF Integrated Forecasting System (IFS). The cloud scheme represents the formation and dissipation of clouds and large-scale precipitation due to changes in atmospheric quantities (such as pressure, temperature and moisture) predicted directly by the IFS at spatial scales of the grid box or larger. Convective precipitation is generated by the convection scheme in the IFS, which represents convection at spatial scales smaller than the grid box. See further information. This parameter does not include fog, dew or the precipitation that evaporates in the atmosphere before it lands at the surface of the Earth.
Care should be taken when comparing model parameters with observations, because observations are often local to a particular point in space and time, rather than representing averages over a model grid box.\r\n\r\n[NOTE: See 228228 for the equivalent parameter in \"kg m-2\"]","unit_id":4,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":229,"name":"Instantaneous eastward turbulent surface stress","shortname":"iews","description":"Air flowing over a surface exerts a stress that transfers momentum to the surface and slows the wind. This parameter is the stress on the Earth's surface at the specified time in the eastward direction due to both the turbulent interactions between the atmosphere and the surface, and to turbulent orographic form drag.
The turbulent interactions between the atmosphere and the surface are due to the roughness of the surface.
The turbulent orographic form drag is the stress due to the valleys, hills and mountains on horizontal scales below 5km being derived from land surface data at about 1 km resolution. See further information.
Positive (negative) values denote stress in the eastward (westward) direction.","unit_id":32,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":230,"name":"Instantaneous northward turbulent surface stress","shortname":"inss","description":"Air flowing over a surface exerts a stress that transfers momentum to the surface and slows the wind. This parameter is the stress on the Earth's surface at the specified time in the northward direction due to both the turbulent interactions between the atmosphere and the surface, and to turbulent orographic form drag.
The turbulent interactions between the atmosphere and the surface are due to the roughness of the surface.
The turbulent orographic form drag is the stress due to the valleys, hills and mountains on horizontal scales below 5km being derived from land surface data at about 1 km resolution. See further information.
Positive (negative) values denote stress in the northward (southward) direction.","unit_id":32,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":231,"name":"Instantaneous surface sensible heat net flux","shortname":"ishf","description":"
This parameter is the transfer of heat between the Earth's surface and the atmosphere, at the specified time, through the effects of turbulent air motion (but excluding any heat transfer resulting from condensation or evaporation).
The magnitude of the sensible heat flux is governed by the difference in temperature between the surface and the overlying atmosphere, wind speed and the surface roughness. For example, cold air overlying a warm surface would produce a sensible heat flux from the land (or ocean) into the atmosphere.The ECMWF convention for vertical fluxes is positive downwards. See further documentation.
","unit_id":76,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":232,"name":"Instantaneous moisture flux","shortname":"ie","description":"This parameter is the net rate of moisture exchange between the land/ocean surface and the atmosphere, due to the processes of evaporation (including evapotranspiration) and condensation, at the specified time. By convention, downward fluxes are positive, which means that evaporation is represented by negative values and condensation by positive values.","unit_id":33,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":233,"name":"Apparent surface humidity","shortname":"asq","description":null,"unit_id":21,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":234,"name":"Logarithm of surface roughness length for heat (climatological)","shortname":"lsrh","description":"Represents surface roughness length for heat and moisture over land. Climatological field.","unit_id":106,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":235,"name":"Skin temperature","shortname":"skt","description":"
This parameter is the temperature of the surface of the Earth.
The skin temperature is the theoretical temperature that is required to satisfy the surface energy balance. It represents the temperature of the uppermost surface layer, which has no heat capacity and so can respond instantaneously to changes in surface fluxes. Skin temperature is calculated differently over land and sea.
This parameter has units of kelvin (K). Temperature measured in kelvin can be converted to degrees Celsius (°C) by subtracting 273.15.
See further information about the skin temperature over land and over sea.
Please note that the encodings listed here for s2s & uerra (which includes carra/cerra) include entries for Time-mean skin temperature. The specific encoding for Mean skin temperature can be found in 235079.
","unit_id":2,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":236,"name":"Soil temperature level 4","shortname":"stl4","description":"This parameter is the temperature of the soil at level 4 (in the middle of layer 4).
The ECMWF Integrated Forecasting System (IFS) has a four-layer representation of soil, where the surface is at 0cm:
Soil temperature is set at the middle of each layer, and heat transfer is calculated at the interfaces between them. It is assumed that there is no heat transfer out of the bottom of the lowest layer.
This parameter has units of Kelvin (K). Temperature measured in Kelvin can be converted to degrees Celsius (°C) by subtracting 273.15.
See further information.","unit_id":2,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":237,"name":"Soil wetness level 4","shortname":"swl4","description":"Old field Layer 100-289 cm (soil moisture is archived as field 42). Water column scaled to depth of surf layer (7 cm).","unit_id":4,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":238,"name":"Temperature of snow layer","shortname":"tsn","description":"This parameter gives the temperature of the snow layer from the ground to the snow-air interface.
The ECMWF Integrated Forecast System (IFS) model represents snow as a single additional layer over the uppermost soil level. The snow may cover all or part of the grid box.
This parameter has units of kelvin (K). Temperature measured in kelvin can be converted to degrees Celsius (°C) by subtracting 273.15.","unit_id":2,"encoding_ids":["grib1","grib2","netcdf"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":239,"name":"Convective snowfall","shortname":"csf","description":"Accumulated field","unit_id":27,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":240,"name":"Large-scale snowfall","shortname":"lsf","description":"Accumulated field","unit_id":27,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":241,"name":"Accumulated cloud fraction tendency","shortname":"acf","description":null,"unit_id":34,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":242,"name":"Accumulated liquid water tendency","shortname":"alw","description":null,"unit_id":34,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":243,"name":"Forecast albedo","shortname":"fal","description":"This parameter is a measure of the reflectivity of the Earth's surface. It is the fraction of solar (shortwave) radiation reflected by Earth's surface, across the solar spectrum, for both direct and diffuse radiation. Typically, snow and ice have high reflectivity with albedo values of 0.8 and above, land has intermediate values between about 0.1 and 0.4 and the ocean has low values of 0.1 or less.
Radiation from the Sun (solar, or shortwave, radiation) is partly reflected back to space by clouds and particles in the atmosphere (aerosols) and some of it is absorbed. The rest is incident on the Earth's surface, where some of it is reflected. The portion that is reflected by the Earth's surface depends on the albedo. See further documentation .
In the ECMWF Integrated Forecasting System (IFS), a climatological background albedo (observed values averaged over a period of several years) is used, modified by the model over water, ice and snow.
Albedo is often shown as a percentage (%). \n[NOTE: See 260509 for the equivalent parameter in '%']","unit_id":3,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":244,"name":"Forecast surface roughness","shortname":"fsr","description":"This parameter is the aerodynamic roughness length in metres.
It is a measure of the surface resistance. This parameter is used to determine the air to surface transfer of momentum. For given atmospheric conditions, a higher surface roughness causes a slower near-surface wind speed.
Over the ocean, surface roughness depends on the waves. Over the land, surface roughness is derived from the vegetation type and snow cover.","unit_id":4,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":245,"name":"Forecast logarithm of surface roughness for heat","shortname":"flsr","description":"This parameter is the natural logarithm of the roughness length for heat.
The surface roughness for heat is a measure of the surface resistance to heat transfer. This parameter is used to determine the air to surface transfer of heat. For given atmospheric conditions, a higher surface roughness for heat means that it is more difficult for the air to exchange heat with the surface. A lower surface roughness for heat that it is easier for the air to exchange heat with the surface.
Over the ocean, surface roughness for heat depends on the waves. Over sea-ice, it has a constant value of 0.001 m. Over the land, it is derived from the vegetation type and snow cover. See further information.","unit_id":106,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":246,"name":"Specific cloud liquid water content","shortname":"clwc","description":"This parameter is the mass of cloud liquid water droplets per kilogram of the total mass of moist air. The 'total mass of moist air' is the sum of the dry air, water vapour, cloud liquid, cloud ice, rain and falling snow. This parameter represents the average value for a grid box.
Water within clouds can be liquid or ice, or a combination of the two. See further information about the cloud formulation.","unit_id":21,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":247,"name":"Specific cloud ice water content","shortname":"ciwc","description":"This parameter is the mass of cloud ice particles per kilogram of the total mass of moist air. The 'total mass of moist air' is the sum of the dry air, water vapour, cloud liquid, cloud ice, rain and falling snow. This parameter represents the average value for a grid box.
Water within clouds can be liquid or ice, or a combination of the two. Note that 'cloud frozen water' is the same as 'cloud ice water'.
See further information about the cloud formulation.","unit_id":21,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":248,"name":"Fraction of cloud cover","shortname":"cc","description":"This parameter is the proportion of a grid box covered by cloud (liquid or ice). This parameter is available on multiple levels through the atmosphere.","unit_id":3,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":249,"name":"Accumulated ice water tendency","shortname":"aiw","description":null,"unit_id":34,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":250,"name":"Ice age","shortname":"ice","description":"0 first-year, 1 multi-year","unit_id":3,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":251,"name":"Adiabatic tendency of temperature","shortname":"atte","description":null,"unit_id":2,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":252,"name":"Adiabatic tendency of humidity","shortname":"athe","description":null,"unit_id":21,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":253,"name":"Adiabatic tendency of zonal wind","shortname":"atze","description":null,"unit_id":5,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":254,"name":"Adiabatic tendency of meridional wind","shortname":"atmw","description":"","unit_id":5,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":255,"name":"Indicates a missing value","shortname":"~","description":null,"unit_id":7,"encoding_ids":["grib1"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":3003,"name":"Pressure tendency","shortname":"ptend","description":null,"unit_id":26,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":3005,"name":"ICAO Standard Atmosphere reference height","shortname":"icaht","description":null,"unit_id":4,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":3008,"name":"Geometrical height above ground","shortname":"h","description":"","unit_id":4,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":3009,"name":"Standard deviation of height","shortname":"hstdv","description":null,"unit_id":4,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":3012,"name":"Virtual potential temperature","shortname":"vptmp","description":null,"unit_id":2,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":3014,"name":"Pseudo-adiabatic potential temperature","shortname":"papt","description":"","unit_id":2,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":3015,"name":"Maximum temperature","shortname":"tmax","description":null,"unit_id":2,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":3016,"name":"Minimum temperature","shortname":"tmin","description":null,"unit_id":2,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":3017,"name":"Dew point temperature","shortname":"dpt","description":null,"unit_id":2,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":3018,"name":"Dew point depression (or deficit)","shortname":"depr","description":null,"unit_id":2,"encoding_ids":["grib1"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":3019,"name":"Lapse rate","shortname":"lapr","description":null,"unit_id":190,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":3020,"name":"Visibility","shortname":"vis","description":"A visibility parameter was introduced in the ECMWF Integrated Forecasting System (IFS) from 12 May 2015. It uses model projections of water vapour, cloud, rain and snow, and climatological aerosol fields to estimate the visibility that would be recorded by weather observers. It is calculated in the IFS at 10 m above the surface of the Earth.
Visibility is normally many kilometers, but is reduced by several meteorological factors including water droplets (fog), precipitation, humidity and aerosols.
Historically, visibility observations have been estimated by human observers judging whether they can see distant objects. More recently, visibility sensors measure the length of atmosphere over which a beam of light travels before its luminous flux is reduced to 5% of its original value. ","unit_id":4,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":3021,"name":"Radar spectra (1)","shortname":"rdsp1","description":null,"unit_id":7,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":3022,"name":"Radar spectra (2)","shortname":"rdsp2","description":null,"unit_id":7,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":3023,"name":"Radar spectra (3)","shortname":"rdsp3","description":null,"unit_id":7,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":3024,"name":"Parcel lifted index (to 500 hPa)","shortname":"pli","description":null,"unit_id":2,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":3025,"name":"Temperature 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gradient","shortname":"tsngrd","description":null,"unit_id":2,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":129239,"name":"Convective snowfall gradient","shortname":"csfgrd","description":null,"unit_id":27,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":129240,"name":"Large scale snowfall gradient","shortname":"lsfgrd","description":null,"unit_id":27,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":129241,"name":"Accumulated cloud fraction tendency gradient","shortname":"acfgrd","description":null,"unit_id":34,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":129242,"name":"Accumulated liquid water tendency gradient","shortname":"alwgrd","description":null,"unit_id":34,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":129243,"name":"Forecast albedo gradient","shortname":"falgrd","description":null,"unit_id":3,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":129244,"name":"Forecast surface roughness gradient","shortname":"fsrgrd","description":null,"unit_id":4,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":129245,"name":"Forecast logarithm of surface roughness for heat gradient","shortname":"flsrgrd","description":null,"unit_id":7,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":129246,"name":"Specific cloud liquid water content gradient","shortname":"clwcgrd","description":null,"unit_id":21,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":129247,"name":"Specific cloud ice water content gradient","shortname":"ciwcgrd","description":null,"unit_id":21,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":129248,"name":"Cloud cover gradient","shortname":"ccgrd","description":null,"unit_id":3,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":129249,"name":"Accumulated ice water tendency gradient","shortname":"aiwgrd","description":null,"unit_id":34,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":129250,"name":"Ice age gradient","shortname":"icegrd","description":null,"unit_id":3,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":129251,"name":"Adiabatic tendency of temperature gradient","shortname":"attegrd","description":null,"unit_id":2,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":129252,"name":"Adiabatic tendency of humidity gradient","shortname":"athegrd","description":null,"unit_id":21,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":129253,"name":"Adiabatic tendency of zonal wind gradient","shortname":"atzegrd","description":null,"unit_id":5,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":129254,"name":"Adiabatic tendency of meridional wind gradient","shortname":"atmwgrd","description":null,"unit_id":5,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":129255,"name":"Indicates a missing value","shortname":"~","description":null,"unit_id":7,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":130208,"name":"Top solar radiation upward","shortname":"tsru","description":null,"unit_id":6,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":130209,"name":"Top thermal radiation upward","shortname":"ttru","description":null,"unit_id":6,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":130210,"name":"Top solar radiation upward, clear sky","shortname":"tsuc","description":null,"unit_id":6,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":130211,"name":"Top thermal radiation upward, clear sky","shortname":"ttuc","description":null,"unit_id":6,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":130212,"name":"Cloud liquid water","shortname":"clw","description":null,"unit_id":21,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":130213,"name":"Cloud fraction","shortname":"cf","description":null,"unit_id":3,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":130214,"name":"Diabatic heating by radiation","shortname":"dhr","description":null,"unit_id":37,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":130215,"name":"Diabatic heating by vertical diffusion","shortname":"dhvd","description":null,"unit_id":37,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":130216,"name":"Diabatic heating by cumulus convection","shortname":"dhcc","description":null,"unit_id":37,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":130217,"name":"Diabatic heating by large-scale condensation","shortname":"dhlc","description":null,"unit_id":37,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":130218,"name":"Vertical diffusion of zonal wind","shortname":"vdzw","description":null,"unit_id":38,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":130219,"name":"Vertical diffusion of meridional wind","shortname":"vdmw","description":null,"unit_id":38,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":130220,"name":"East-West gravity wave drag","shortname":"ewgd","description":null,"unit_id":38,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":130221,"name":"North-South gravity wave drag","shortname":"nsgd","description":null,"unit_id":38,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":130224,"name":"Vertical diffusion of humidity","shortname":"vdh","description":null,"unit_id":39,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":130225,"name":"Humidity tendency by cumulus convection","shortname":"htcc","description":null,"unit_id":39,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":130226,"name":"Humidity tendency by large-scale condensation","shortname":"htlc","description":null,"unit_id":39,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":130228,"name":"Adiabatic tendency of temperature","shortname":"att","description":null,"unit_id":37,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":130229,"name":"Adiabatic tendency of humidity","shortname":"ath","description":null,"unit_id":39,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":130230,"name":"Adiabatic tendency of zonal wind","shortname":"atzw","description":null,"unit_id":38,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":130231,"name":"Adiabatic tendency of meridional wind","shortname":"atmwax","description":null,"unit_id":38,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":130232,"name":"Mean vertical velocity","shortname":"mvv","description":"
Please use 235135 for the GRIB2 encoding of this parameter.
","unit_id":26,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":131001,"name":"2m temperature anomaly of at least +2K","shortname":"2tag2","description":"This parameter gives the probability (in %) that the 2m temperature anomaly will be +2K or above. It is derived from the range of possible outcomes as predicted by the ECMWF ensemble forecasting system. A higher probability indicates that more ensemble members are predicting a 2m temperature anomaly of +2K or above.
An anomaly is a difference from a defined long-term average. 2m temperature is calculated by interpolating between the lowest model level and the Earth's surface, taking account of the atmospheric conditions. See further information.","unit_id":29,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":131002,"name":"2m temperature anomaly of at least +1K","shortname":"2tag1","description":"This parameter gives the probability (in %) that the 2m temperature anomaly will be +1K or above. It is derived from the range of possible outcomes as predicted by the ECMWF ensemble forecasting system. A higher probability indicates that more ensemble members are predicting a 2m temperature anomaly of +1K or above.
An anomaly is a difference from a defined long-term average. 2m temperature is calculated by interpolating between the lowest model level and the Earth's surface, taking account of the atmospheric conditions. See further information.","unit_id":29,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":131003,"name":"2m temperature anomaly of at least 0K","shortname":"2tag0","description":"This parameter gives the probability (in %) that the 2m temperature anomaly will be 0K or above. It is derived from the range of possible outcomes as predicted by the ECMWF ensemble forecasting system. A higher probability indicates that more ensemble members are predicting a 2m temperature anomaly of 0K or above.
An anomaly is a difference from a defined long-term average. 2m temperature is calculated by interpolating between the lowest model level and the Earth's surface, taking account of the atmospheric conditions. See further information.","unit_id":29,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":131004,"name":"2m temperature anomaly of at most -1K","shortname":"2talm1","description":"This parameter gives the probability (in %) that the 2m temperature anomaly will be -1K or below. It is derived from the range of possible outcomes as predicted by the ECMWF ensemble forecasting system. A higher probability indicates that more ensemble members are predicting a 2m temperature anomaly of -1K or below.
An anomaly is a difference from a defined long-term average. 2m temperature is calculated by interpolating between the lowest model level and the Earth's surface, taking account of the atmospheric conditions. See further information.","unit_id":29,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":131005,"name":"2m temperature anomaly of at most -2K","shortname":"2talm2","description":"This parameter gives the probability (in %) that the 2m temperature anomaly will be -2K or below. It is derived from the range of possible outcomes as predicted by the ECMWF ensemble forecasting system. A higher probability indicates that more ensemble members are predicting a 2m temperature anomaly of -2K or below.
An anomaly is a difference from a defined long-term average. 2m temperature is calculated by interpolating between the lowest model level and the Earth's surface, taking account of the atmospheric conditions. See further information.","unit_id":29,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":131006,"name":"Total precipitation anomaly of at least 20 mm","shortname":"tpag20","description":"This parameter gives the probability (in %) that the total precipitation anomaly will be 20 mm or above. It is derived from the range of possible outcomes as predicted by the ECMWF ensemble forecasting system. A higher probability indicates that more ensemble members are predicting a total precipitation anomaly of 20mm or above. An anomaly is a difference from a defined long-term average or climate.
In the ECMWF Integrated Forecasting System (IFS), total precipitation is rain and snow that falls to the Earth's surface. It is the sum of large-scale precipitation and convective precipitation. Large-scale precipitation is generated by the cloud scheme in the IFS. The cloud scheme represents the formation and dissipation of clouds and large-scale precipitation due to changes in atmospheric quantities (such as pressure, temperature and moisture) predicted directly by the IFS at spatial scales of a grid box or larger. Convective precipitation is generated by the convection scheme in the IFS. The convection scheme represents convection at spatial scales smaller than the grid box. See further information.
Precipitation parameters do not include fog, dew or the precipitation that evaporates in the atmosphere before it lands at the surface of the Earth.","unit_id":29,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":131007,"name":"Total precipitation anomaly of at least 10 mm","shortname":"tpag10","description":"This parameter gives the probability (in %) that the total precipitation anomaly will be 10 mm or above. It is derived from the range of possible outcomes as predicted by the ECMWF ensemble forecasting system. A higher probability indicates that more ensemble members are predicting a total precipitation anomaly of 10mm or above. An anomaly is a difference from a defined long-term average or climate.
In the ECMWF Integrated Forecasting System (IFS), total precipitation is rain and snow that falls to the Earth's surface. It is the sum of large-scale precipitation and convective precipitation. Large-scale precipitation is generated by the cloud scheme in the IFS. The cloud scheme represents the formation and dissipation of clouds and large-scale precipitation due to changes in atmospheric quantities (such as pressure, temperature and moisture) predicted directly by the IFS at spatial scales of a grid box or larger. Convective precipitation is generated by the convection scheme in the IFS. The convection scheme represents convection at spatial scales smaller than the grid box. See further information.
Precipitation parameters do not include fog, dew or the precipitation that evaporates in the atmosphere before it lands at the surface of the Earth.","unit_id":29,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":131008,"name":"Total precipitation anomaly of at least 0 mm","shortname":"tpag0","description":"This parameter gives the probability (in %) that the total precipitation anomaly will be 0 mm or above. It is derived from the range of possible outcomes as predicted by the ECMWF ensemble forecasting system. A higher probability indicates that more ensemble members are predicting a total precipitation anomaly of 0mm or above. An anomaly is a difference from a defined long-term average or climate.
In the ECMWF Integrated Forecasting System (IFS), total precipitation is rain and snow that falls to the Earth's surface. It is the sum of large-scale precipitation and convective precipitation. Large-scale precipitation is generated by the cloud scheme in the IFS. The cloud scheme represents the formation and dissipation of clouds and large-scale precipitation due to changes in atmospheric quantities (such as pressure, temperature and moisture) predicted directly by the IFS at spatial scales of a grid box or larger. Convective precipitation is generated by the convection scheme in the IFS. The convection scheme represents convection at spatial scales smaller than the grid box. See further information.
Precipitation parameters do not include fog, dew or the precipitation that evaporates in the atmosphere before it lands at the surface of the Earth.","unit_id":29,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":131009,"name":"Surface temperature anomaly of at least 0K","shortname":"stag0","description":null,"unit_id":29,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":131010,"name":"Mean sea level pressure anomaly of at least 0 Pa","shortname":"mslag0","description":null,"unit_id":29,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":131015,"name":"Height of 0 degree isotherm probability","shortname":"h0dip","description":null,"unit_id":29,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":131016,"name":"Height of snowfall limit probability","shortname":"hslp","description":null,"unit_id":29,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":131017,"name":"Showalter index probability","shortname":"saip","description":null,"unit_id":29,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":131018,"name":"Whiting index probability","shortname":"whip","description":null,"unit_id":29,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":131020,"name":"Temperature anomaly less than -2 K","shortname":"talm2","description":"This parameter gives the probability (in %) that the temperature anomaly is below -2 K. It is derived from the range of possible outcomes as predicted by the ECMWF ensemble forecasting system. A higher probability indicates that more ensemble members are predicting a temperature anomaly below -2 K. An anomaly is a difference from a defined long-term average.","unit_id":29,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":131021,"name":"Temperature anomaly of at least +2 K","shortname":"tag2","description":"This parameter gives the probability (in %) that the temperature anomaly is 2 K or above. It is derived from the range of possible outcomes as predicted by the ECMWF ensemble forecasting system. A higher probability indicates that more ensemble members are predicting a temperature anomaly of 2 K or above. An anomaly is a difference from a defined long-term average.","unit_id":29,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":131022,"name":"Temperature anomaly less than -8 K","shortname":"talm8","description":"This parameter gives the probability (in %) that the temperature anomaly is below -8 K. It is derived from the range of possible outcomes as predicted by the ECMWF ensemble forecasting system. A higher probability indicates that more ensemble members are predicting a temperature anomaly below -8 K. An anomaly is a difference from a defined long-term average.","unit_id":29,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":131023,"name":"Temperature anomaly less than -4 K","shortname":"talm4","description":"This parameter gives the probability (in %) that the temperature anomaly is below -4 K. It is derived from the range of possible outcomes as predicted by the ECMWF ensemble forecasting system. A higher probability indicates that more ensemble members are predicting a temperature anomaly below -4 K. An anomaly is a difference from a defined long-term average.","unit_id":29,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":131024,"name":"Temperature anomaly greater than +4 K","shortname":"tag4","description":"This parameter gives the probability (in %) that the temperature anomaly exceeds +4 K. It is derived from the range of possible outcomes as predicted by the ECMWF ensemble forecasting system. A higher probability indicates that more ensemble members are predicting a temperature anomaly above +4 K. An anomaly is a difference from a defined long-term average.","unit_id":29,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":131025,"name":"Temperature anomaly greater than +8 K","shortname":"tag8","description":"This parameter gives the probability (in %) that the temperature anomaly exceeds +8 K. It is derived from the range of possible outcomes as predicted by the ECMWF ensemble forecasting system. A higher probability indicates that more ensemble members are predicting a temperature anomaly above +8 K. An anomaly is a difference from a defined long-term average.","unit_id":29,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":131049,"name":"10 metre wind gust probability","shortname":"10gp","description":null,"unit_id":29,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":131059,"name":"Convective available potential energy probability","shortname":"capep","description":null,"unit_id":29,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":131060,"name":"Total precipitation of at least 1 mm","shortname":"tpg1","description":"This parameter gives the probability (in %) that total precipitation will be 1 mm or above. It is derived from the range of possible outcomes as predicted by the ECMWF ensemble forecasting system. A higher probability indicates that more ensemble members are predicting total precipitation of 1 mm or above.
Total precipitation is the sum of large-scale precipitation and convective precipitation. Large-scale precipitation is generated by the cloud scheme in the IFS. The cloud scheme represents the formation and dissipation of clouds and large-scale precipitation due to changes in atmospheric quantities (such as pressure, temperature and moisture) predicted directly by the IFS at spatial scales of a grid box or larger. Convective precipitation is generated by the convection scheme in the IFS. The convection scheme represents convection at spatial scales smaller than the grid box. See further information. Precipitation parameters do not include fog, dew or the precipitation that evaporates in the atmosphere before it lands at the surface of the Earth.","unit_id":29,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":131061,"name":"Total precipitation of at least 5 mm","shortname":"tpg5","description":"This parameter gives the probability (in %) that total precipitation will be 5 mm or above. It is derived from the range of possible outcomes as predicted by the ECMWF ensemble forecasting system. A higher probability indicates that more ensemble members are predicting total precipitation of 5 mm or above.
Total precipitation is the sum of large-scale precipitation and convective precipitation. Large-scale precipitation is generated by the cloud scheme in the IFS. The cloud scheme represents the formation and dissipation of clouds and large-scale precipitation due to changes in atmospheric quantities (such as pressure, temperature and moisture) predicted directly by the IFS at spatial scales of a grid box or larger. Convective precipitation is generated by the convection scheme in the IFS. The convection scheme represents convection at spatial scales smaller than the grid box. See further information. Precipitation parameters do not include fog, dew or the precipitation that evaporates in the atmosphere before it lands at the surface of the Earth.","unit_id":29,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":131062,"name":"Total precipitation of at least 10 mm","shortname":"tpg10","description":"This parameter gives the probability (in %) that total precipitation will be 10 mm or above. It is derived from the range of possible outcomes as predicted by the ECMWF ensemble forecasting system. A higher probability indicates that more ensemble members are predicting total precipitation of 10 mm or above.
Total precipitation is the sum of large-scale precipitation and convective precipitation. Large-scale precipitation is generated by the cloud scheme in the IFS. The cloud scheme represents the formation and dissipation of clouds and large-scale precipitation due to changes in atmospheric quantities (such as pressure, temperature and moisture) predicted directly by the IFS at spatial scales of a grid box or larger. Convective precipitation is generated by the convection scheme in the IFS. The convection scheme represents convection at spatial scales smaller than the grid box. See further information. Precipitation parameters do not include fog, dew or the precipitation that evaporates in the atmosphere before it lands at the surface of the Earth.","unit_id":29,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":131063,"name":"Total precipitation of at least 20 mm","shortname":"tpg20","description":"This parameter gives the probability (in %) that total precipitation will be 20 mm or above. It is derived from the range of possible outcomes as predicted by the ECMWF ensemble forecasting system. A higher probability indicates that more ensemble members are predicting total precipitation of 20 mm or above.
Total precipitation is the sum of large-scale precipitation and convective precipitation. Large-scale precipitation is generated by the cloud scheme in the IFS. The cloud scheme represents the formation and dissipation of clouds and large-scale precipitation due to changes in atmospheric quantities (such as pressure, temperature and moisture) predicted directly by the IFS at spatial scales of a grid box or larger. Convective precipitation is generated by the convection scheme in the IFS. The convection scheme represents convection at spatial scales smaller than the grid box. See further information. Precipitation parameters do not include fog, dew or the precipitation that evaporates in the atmosphere before it lands at the surface of the Earth.","unit_id":29,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":131064,"name":"Total precipitation less than 0.1 mm","shortname":"tpl01","description":"This parameter gives the probability (in %) that total precipitation will be below 0.1 mm. It is derived from the range of possible outcomes as predicted by the ECMWF ensemble forecasting system. A higher probability indicates that more ensemble members are predicting total precipitation below 0.1 mm.
Total precipitation is the sum of large-scale precipitation and convective precipitation. Large-scale precipitation is generated by the cloud scheme in the IFS. The cloud scheme represents the formation and dissipation of clouds and large-scale precipitation due to changes in atmospheric quantities (such as pressure, temperature and moisture) predicted directly by the IFS at spatial scales of a grid box or larger. Convective precipitation is generated by the convection scheme in the IFS. The convection scheme represents convection at spatial scales smaller than the grid box. See further information. Precipitation parameters do not include fog, dew or the precipitation that evaporates in the atmosphere before it lands at the surface of the Earth.","unit_id":29,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":131065,"name":"Total precipitation rate less than 1 mm/day","shortname":"tprl1","description":"This parameter gives the probability (in %) that the total precipitation rate will be less than 1 mm/day. It is derived from the range of possible outcomes as predicted by the ECMWF ensemble forecasting system. A higher probability indicates that more ensemble members are predicting a total precipitation rate of less than 1 mm/day. An anomaly is a difference from a defined long-term average or climate.
In the ECMWF Integrated Forecasting System (IFS), total precipitation is rain and snow that falls to the Earth's surface. It is the sum of large-scale precipitation and convective precipitation. Large-scale precipitation is generated by the cloud scheme in the IFS. The cloud scheme represents the formation and dissipation of clouds and large-scale precipitation due to changes in atmospheric quantities (such as pressure, temperature and moisture) predicted directly by the IFS at spatial scales of a grid box or larger. Convective precipitation is generated by the convection scheme in the IFS. The convection scheme represents convection at spatial scales smaller than the grid box.See further information. Precipitation parameters do not include fog, dew or the precipitation that evaporates in the atmosphere before it lands at the surface of the Earth.","unit_id":29,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":131066,"name":"Total precipitation rate of at least 3 mm/day","shortname":"tprg3","description":"This parameter gives the probability (in %) that the total precipitation rate will 3 mm/day or above. It is derived from the range of possible outcomes as predicted by the ECMWF ensemble forecasting system. A higher probability indicates that more ensemble members are predicting a total precipitation rate of 3 mm/day or above. An anomaly is a difference from a defined long-term average or climate.
In the ECMWF Integrated Forecasting System (IFS), total precipitation is rain and snow that falls to the Earth's surface. It is the sum of large-scale precipitation and convective precipitation. Large-scale precipitation is generated by the cloud scheme in the IFS. The cloud scheme represents the formation and dissipation of clouds and large-scale precipitation due to changes in atmospheric quantities (such as pressure, temperature and moisture) predicted directly by the IFS at spatial scales of a grid box or larger. Convective precipitation is generated by the convection scheme in the IFS. The convection scheme represents convection at spatial scales smaller than the grid box.See further information. Precipitation parameters do not include fog, dew or the precipitation that evaporates in the atmosphere before it lands at the surface of the Earth.","unit_id":29,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":131067,"name":"Total precipitation rate of at least 5 mm/day","shortname":"tprg5","description":"This parameter gives the probability (in %) that the total precipitation rate will 5 mm/day or above. It is derived from the range of possible outcomes as predicted by the ECMWF ensemble forecasting system. A higher probability indicates that more ensemble members are predicting a total precipitation rate of 5 mm/day or above. An anomaly is a difference from a defined long-term average or climate.
In the ECMWF Integrated Forecasting System (IFS), total precipitation is rain and snow that falls to the Earth's surface. It is the sum of large-scale precipitation and convective precipitation. Large-scale precipitation is generated by the cloud scheme in the IFS. The cloud scheme represents the formation and dissipation of clouds and large-scale precipitation due to changes in atmospheric quantities (such as pressure, temperature and moisture) predicted directly by the IFS at spatial scales of a grid box or larger. Convective precipitation is generated by the convection scheme in the IFS. The convection scheme represents convection at spatial scales smaller than the grid box.See further information. Precipitation parameters do not include fog, dew or the precipitation that evaporates in the atmosphere before it lands at the surface of the Earth.","unit_id":29,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":131068,"name":"10 metre Wind speed of at least 10 m/s","shortname":"10spg10","description":"This parameter gives the probability (in %) that the 10 m wind speed will be 10 m s-1 or above. It is derived from the range of possible outcomes as predicted by the ECMWF ensemble forecasting system. A higher probability indicates that more ensemble members are predicting a 10 m wind speed of 10 m s-1 or above.
10 metre wind speed is the horizontal speed of the wind, or movement of air, at a height of ten metres above the surface of the Earth.","unit_id":29,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":131069,"name":"10 metre Wind speed of at least 15 m/s","shortname":"10spg15","description":"This parameter gives the probability (in %) that the 10 m wind speed will be 15 m s-1 or above. It is derived from the range of possible outcomes as predicted by the ECMWF ensemble forecasting system. A higher probability indicates that more ensemble members are predicting a 10 m wind speed of 15 m s-1 or above.
10 metre wind speed is the horizontal speed of the wind, or movement of air, at a height of ten metres above the surface of the Earth.","unit_id":29,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":131070,"name":"10 metre wind gust of at least 15 m/s","shortname":"10fgg15","description":"This parameter gives the probability (in %) that the 10 m gust will be 15 m s-1 or above. It is derived from the range of possible outcomes as predicted by the ECMWF ensemble forecasting system. A higher probability indicates that more ensemble members are predicting a 10 m gust speed of 15 m s-1 or above.
The WMO defines a wind gust as the maximum of the wind averaged over 3 second intervals. This duration is shorter than a model time step, and so the ECMWF Integrated Forecasting System deduces the magnitude of a gust within each time step from the time-step-averaged surface stress, surface friction, wind shear and stability. Then, the maximum wind gust is selected from the gusts at each time step during a particular time period which depends on the data extracted.
This parameter is calculated at a height of ten metres above the surface of the Earth. ","unit_id":29,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":131071,"name":"10 metre wind gust of at least 20 m/s","shortname":"10fgg20","description":"This parameter gives the probability (in %) that the 10 m gust will be 20 m s-1 or above. It is derived from the range of possible outcomes as predicted by the ECMWF ensemble forecasting system. A higher probability indicates that more ensemble members are predicting a 10 m gust speed of 20 m s-1 or above.
The WMO defines a wind gust as the maximum of the wind averaged over 3 second intervals. This duration is shorter than a model time step, and so the ECMWF Integrated Forecasting System deduces the magnitude of a gust within each time step from the time-step-averaged surface stress, surface friction, wind shear and stability. Then, the maximum wind gust is selected from the gusts at each time step during a particular time period which depends on the data extracted.
This parameter is calculated at a height of ten metres above the surface of the Earth. ","unit_id":29,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":131072,"name":"10 metre wind gust of at least 25 m/s","shortname":"10fgg25","description":"This parameter gives the probability (in %) that the 10 m gust will be 25 m s-1 or above. It is derived from the range of possible outcomes as predicted by the ECMWF ensemble forecasting system. A higher probability indicates that more ensemble members are predicting a 10 m gust speed of 25 m s-1 or above.
The WMO defines a wind gust as the maximum of the wind averaged over 3 second intervals. This duration is shorter than a model time step, and so the ECMWF Integrated Forecasting System deduces the magnitude of a gust within each time step from the time-step-averaged surface stress, surface friction, wind shear and stability. Then, the maximum wind gust is selected from the gusts at each time step during a particular time period which depends on the data extracted.
This parameter is calculated at a height of ten metres above the surface of the Earth.","unit_id":29,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":131073,"name":"2 metre temperature less than 273.15 K","shortname":"2tl273","description":"Probability","unit_id":29,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":131074,"name":"Significant wave height of at least 2 m","shortname":"swhg2","description":"This parameter gives the probability (in %) that the significant wave height will be 2 m or above. It is derived from the range of possible outcomes as predicted by the ECMWF ensemble forecasting system. A higher probability indicates that more ensemble members are predicting a significant wave height of 2 m or above.
The significant wave height represents the average height of the highest third of surface ocean/sea waves generated by wind and swell. It represents the vertical distance between the wave crest and the wave trough.
The ocean/sea surface wave field consists of a combination of waves with different heights, lengths and directions (known as the two-dimensional wave spectrum). The wave spectrum can be decomposed into wind-sea waves, which are directly affected by local winds, and swell, the waves that were generated by the wind at a different location and time. This parameter takes account of both.
More strictly, this significant wave height is four times the square root of the integral over all directions and all frequencies of the two-dimensional wave spectrum. See further documentation.
Significant wave height can be used to assess sea state and swell. For example, engineers use significant wave height to calculate the load on structures in the open ocean, such as oil platforms, or in coastal applications.","unit_id":29,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":131075,"name":"Significant wave height of at least 4 m","shortname":"swhg4","description":"This parameter gives the probability (in %) that the significant wave height will be 4 m or above. It is derived from the range of possible outcomes as predicted by the ECMWF ensemble forecasting system. A higher probability indicates that more ensemble members are predicting a significant wave height of 4 m or above.
The significant wave height represents the average height of the highest third of surface ocean/sea waves generated by wind and swell. It represents the vertical distance between the wave crest and the wave trough.
The ocean/sea surface wave field consists of a combination of waves with different heights, lengths and directions (known as the two-dimensional wave spectrum). The wave spectrum can be decomposed into wind-sea waves, which are directly affected by local winds, and swell, the waves that were generated by the wind at a different location and time. This parameter takes account of both.
More strictly, this significant wave height is four times the square root of the integral over all directions and all frequencies of the two-dimensional wave spectrum. See further documentation.
Significant wave height can be used to assess sea state and swell. For example, engineers use significant wave height to calculate the load on structures in the open ocean, such as oil platforms, or in coastal applications.","unit_id":29,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":131076,"name":"Significant wave height of at least 6 m","shortname":"swhg6","description":"This parameter gives the probability (in %) that the significant wave height will be 6 m or above. It is derived from the range of possible outcomes as predicted by the ECMWF ensemble forecasting system. A higher probability indicates that more ensemble members are predicting a significant wave height of 6 m or above.
The significant wave height represents the average height of the highest third of surface ocean/sea waves generated by wind and swell. It represents the vertical distance between the wave crest and the wave trough.
The ocean/sea surface wave field consists of a combination of waves with different heights, lengths and directions (known as the two-dimensional wave spectrum). The wave spectrum can be decomposed into wind-sea waves, which are directly affected by local winds, and swell, the waves that were generated by the wind at a different location and time. This parameter takes account of both.
More strictly, this significant wave height is four times the square root of the integral over all directions and all frequencies of the two-dimensional wave spectrum. See further documentation.
Significant wave height can be used to assess sea state and swell. For example, engineers use significant wave height to calculate the load on structures in the open ocean, such as oil platforms, or in coastal applications.","unit_id":29,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":131077,"name":"Significant wave height of at least 8 m","shortname":"swhg8","description":"This parameter gives the probability (in %) that the significant wave height will be 8 m or above. It is derived from the range of possible outcomes as predicted by the ECMWF ensemble forecasting system. A higher probability indicates that more ensemble members are predicting a significant wave height of 8 m or above.
The significant wave height represents the average height of the highest third of surface ocean/sea waves generated by wind and swell. It represents the vertical distance between the wave crest and the wave trough.
The ocean/sea surface wave field consists of a combination of waves with different heights, lengths and directions (known as the two-dimensional wave spectrum). The wave spectrum can be decomposed into wind-sea waves, which are directly affected by local winds, and swell, the waves that were generated by the wind at a different location and time. This parameter takes account of both.
More strictly, this significant wave height is four times the square root of the integral over all directions and all frequencies of the two-dimensional wave spectrum. See further documentation.
Significant wave height can be used to assess sea state and swell. For example, engineers use significant wave height to calculate the load on structures in the open ocean, such as oil platforms, or in coastal applications.","unit_id":29,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":131078,"name":"Mean wave period of at least 8 s","shortname":"mwpg8","description":"This parameter gives the probability (in %) that the mean wave period will be 8 s or above. It is derived from the range of possible outcomes as predicted by the ECMWF ensemble forecasting system. A higher probability indicates that more ensemble members are predicting a mean wave period of 8 s or above.
The wave period is the average time it takes for two consecutive wave crests, on the surface of the ocean/sea, to pass through a fixed point.
The ocean/sea surface wave field consists of a combination of waves with different heights, lengths and directions (known as the two-dimensional wave spectrum). This parameter is derived from the mean over all frequencies and directions of the two-dimensional wave spectrum.
The wave spectrum can be decomposed into wind-sea waves, which are directly affected by local winds, and swell, the waves that were generated by the wind at a different location and time. This parameter takes account of both. See further information.","unit_id":29,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":131079,"name":"Mean wave period of at least 10 s","shortname":"mwpg10","description":"This parameter gives the probability (in %) that the mean wave period will be 10 s or above. It is derived from the range of possible outcomes as predicted by the ECMWF ensemble forecasting system. A higher probability indicates that more ensemble members are predicting a mean wave period of 10 s or above.
The wave period is the average time it takes for two consecutive wave crests, on the surface of the ocean/sea, to pass through a fixed point.
The ocean/sea surface wave field consists of a combination of waves with different heights, lengths and directions (known as the two-dimensional wave spectrum). This parameter is derived from the mean over all frequencies and directions of the two-dimensional wave spectrum.
The wave spectrum can be decomposed into wind-sea waves, which are directly affected by local winds, and swell, the waves that were generated by the wind at a different location and time. This parameter takes account of both. See further information.","unit_id":29,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":131080,"name":"Mean wave period of at least 12 s","shortname":"mwpg12","description":"This parameter gives the probability (in %) that the mean wave period will be 12 s or above. It is derived from the range of possible outcomes as predicted by the ECMWF ensemble forecasting system. A higher probability indicates that more ensemble members are predicting a mean wave period of 12 s or above.
The wave period is the average time it takes for two consecutive wave crests, on the surface of the ocean/sea, to pass through a fixed point.
The ocean/sea surface wave field consists of a combination of waves with different heights, lengths and directions (known as the two-dimensional wave spectrum). This parameter is derived from the mean over all frequencies and directions of the two-dimensional wave spectrum.
The wave spectrum can be decomposed into wind-sea waves, which are directly affected by local winds, and swell, the waves that were generated by the wind at a different location and time. This parameter takes account of both. See further information.","unit_id":29,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":131081,"name":"Mean wave period of at least 15 s","shortname":"mwpg15","description":"This parameter gives the probability (in %) that the mean wave period will be 15 s or above. It is derived from the range of possible outcomes as predicted by the ECMWF ensemble forecasting system. A higher probability indicates that more ensemble members are predicting a mean wave period of 15 s or above.
The wave period is the average time it takes for two consecutive wave crests, on the surface of the ocean/sea, to pass through a fixed point.
The ocean/sea surface wave field consists of a combination of waves with different heights, lengths and directions (known as the two-dimensional wave spectrum). This parameter is derived from the mean over all frequencies and directions of the two-dimensional wave spectrum.
The wave spectrum can be decomposed into wind-sea waves, which are directly affected by local winds, and swell, the waves that were generated by the wind at a different location and time. This parameter takes account of both. See further information.","unit_id":29,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":131082,"name":"Total precipitation of at least 40 mm","shortname":"tpg40","description":"Probability","unit_id":29,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":131083,"name":"Total precipitation of at least 60 mm","shortname":"tpg60","description":"Probability","unit_id":29,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":131084,"name":"Total precipitation of at least 80 mm","shortname":"tpg80","description":"Probability","unit_id":29,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":131085,"name":"Total precipitation of at least 100 mm","shortname":"tpg100","description":"Probability","unit_id":29,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":131086,"name":"Total precipitation of at least 150 mm","shortname":"tpg150","description":"Probability","unit_id":29,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":131087,"name":"Total precipitation of at least 200 mm","shortname":"tpg200","description":"Probability","unit_id":29,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":131088,"name":"Total precipitation of at least 300 mm","shortname":"tpg300","description":"Probability","unit_id":29,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":131089,"name":"Probability of a tropical storm","shortname":"pts","description":"This parameter is the potential tropical storm activity. It is derived from the range of possible outcomes as predicted by the ECMWF ensemble forecasting system. A higher probability indicates that more ensemble members are predicting a tropical storm.
This parameter is calculated from the number of ensemble members that have a tropical storm within a radius of 300 km of a location, within 48 hours. This is called the 'strike probability'.
A tropical storm is a circular pattern of wind centred around an area of non-frontal low atmospheric pressure at mean sea-level that developed over the tropics or sub-tropics. Its wind speeds near the surface of the Earth are greater than 17 m s-1 and less than 32 m s-1. In the northern hemisphere it rotates in an anti-clockwise direction near the surface, and in the southern hemisphere it rotates clockwise.","unit_id":29,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":131090,"name":"Probability of a hurricane","shortname":"ph","description":"This parameter is the potential hurricane or typhoon activity. It is derived from the range of possible outcomes as predicted by the ECMWF ensemble forecasting system. A higher probability indicates that more ensemble members are predicting a hurricane or typhoon.
This parameter is calculated from the number of ensemble members that have a hurricane or typhoon within a radius of 300 km of a location, within 48 hours of the specified time. This is called the 'strike probability'.
A hurricane is a circular pattern of wind centred around an area of non-frontal low atmospheric pressure at mean sea-level that develops over the tropics or sub-tropics. Its wind speeds near the surface of the Earth are greater than 32 m s-1. In the northern hemisphere it rotates in an anti-clockwise direction near the surface, and in the southern hemisphere it rotates clockwise. In the western North Pacific it is called a typhoon.","unit_id":29,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":131091,"name":"Probability of a tropical depression","shortname":"ptd","description":"This parameter is the potential tropical depression activity. It is derived from the range of possible outcomes as predicted by the ECMWF ensemble forecasting system. A higher probability indicates that more ensemble members are predicting a tropical depression.
This parameter is calculated from the number of ensemble members that have a tropical depression within a radius of 300 km of a location, within 48 hours of the specified time. This is sometimes called the 'strike probability'..
A tropical depression is a circular pattern of wind centred around an area of non-frontal low atmospheric pressure at mean sea-level that developed over the tropics or sub-tropics. Its wind speeds near the surface of the Earth are greater than 8 m s-1 and up to 17 m s-1. In the northern hemisphere it rotates in an anti-clockwise direction near the surface, and in the southern hemisphere it rotates clockwise.","unit_id":29,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":131092,"name":"Climatological probability of a tropical storm","shortname":"cpts","description":"","unit_id":29,"encoding_ids":["grib1"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":131093,"name":"Climatological probability of a hurricane","shortname":"cph","description":"","unit_id":29,"encoding_ids":["grib1"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":131094,"name":"Climatological probability of a tropical depression","shortname":"cptd","description":"","unit_id":29,"encoding_ids":["grib1"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":131095,"name":"Probability anomaly of a tropical storm","shortname":"pats","description":"","unit_id":29,"encoding_ids":["grib1"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":131096,"name":"Probability anomaly of a hurricane","shortname":"pah","description":"","unit_id":29,"encoding_ids":["grib1"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":131097,"name":"Probability anomaly of a tropical depression","shortname":"patd","description":"","unit_id":29,"encoding_ids":["grib1"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":131098,"name":"Total precipitation of at least 25 mm","shortname":"tpg25","description":"","unit_id":29,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":131099,"name":"Total precipitation of at least 50 mm","shortname":"tpg50","description":"","unit_id":29,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":131100,"name":"10 metre wind gust of at least 10 m/s","shortname":"10fgg10","description":"","unit_id":29,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":131129,"name":"Geopotential probability","shortname":"zp","description":null,"unit_id":29,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":131130,"name":"Temperature anomaly probability","shortname":"tap","description":null,"unit_id":29,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":131139,"name":"Soil temperature level 1 probability","shortname":"stl1p","description":"","unit_id":29,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":131144,"name":"Snowfall (convective + stratiform) probability","shortname":"sfp","description":null,"unit_id":29,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":131151,"name":"Mean sea level pressure probability","shortname":"mslpp","description":"","unit_id":29,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":131164,"name":"Total cloud cover probability","shortname":"tccp","description":null,"unit_id":29,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":131165,"name":"10 metre speed probability","shortname":"10sp","description":null,"unit_id":29,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":131167,"name":"2 metre temperature probability","shortname":"2tp","description":"This parameter is the probability (in %) that the 2 metre temperature falls within a particular quantile of the probability distribution function (pdf) for 2 metre temperature. It is derived from the range of possible outcomes as predicted by the ECMWF ensemble forecasting system.
The 2 metre temperature is the temperature of air at 2 m above the surface of land, sea or in-land waters. It is the standard for surface-level temperature measurements on land.
2m temperature is calculated by interpolating between the lowest model level and the Earth's surface, taking account of the atmospheric conditions. See further information .
A quantile is the division of the pdf into equally spaced interval. A higher probability indicates that more ensemble members are predicting a 2 metre temperature in that part of the quantile range.","unit_id":29,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":131201,"name":"Maximum 2 metre temperature probability","shortname":"mx2tp","description":null,"unit_id":29,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":131202,"name":"Minimum 2 metre temperature probability","shortname":"mn2tp","description":null,"unit_id":29,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":131228,"name":"Total precipitation probability","shortname":"tpp","description":"This parameter is the probability (in %) that the total precipitation falls within a particular quantile of the probability distribution function (pdf) for total precipitation. It is derived from the range of possible outcomes as predicted by the ECMWF ensemble forecasting system.
The user decides how many quantiles the pdf is divided into, and which one the probability describes, e.g. lowest third, middle third or highest third. A higher probability indicates that more ensemble members are predicting a total precipitation in the selected part of the range.
In the ECMWF Integrated Forecasting System (IFS), total precipitation is rain and snow that falls to the Earth's surface. It is the sum of large-scale precipitation and convective precipitation. Large-scale precipitation is generated by the cloud scheme in the IFS. The cloud scheme represents the formation and dissipation of clouds and large-scale precipitation due to changes in atmospheric quantities (such as pressure, temperature and moisture) predicted directly by the IFS at spatial scales of a grid box or larger. Convective precipitation is generated by the convection scheme in the IFS. The convection scheme represents convection at spatial scales smaller than the grid box. See further information. Precipitation parameters do not include fog, dew or the precipitation that evaporates in the atmosphere before it lands at the surface of the Earth.","unit_id":29,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":131229,"name":"Significant wave height probability","shortname":"swhp","description":null,"unit_id":29,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":131232,"name":"Mean wave period probability","shortname":"mwpp","description":null,"unit_id":29,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":131255,"name":"Indicates a missing value","shortname":"~","description":null,"unit_id":7,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":131256,"name":"10 metre convective gust of at least 25 m/s","shortname":"10cogug25","description":null,"unit_id":5,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":132044,"name":"Convective available potential energy shear index","shortname":"capesi","description":"
From 48r1 this parameter is based on most unstable CAPE rather than the previously used surface based CAPE.
High values of this parameter indicate where deep, organised convection is more likely to occur, if it is initiated. When air rises through a large depth of the atmosphere extensive condensation can occur and heavy rainfall, thunderstorms and other severe weather can result.
The likelihood of severe weather and its level of intensity tend to increase with increasing organisation of convection. Convective supercells are the most prominent example. Such organised areas of convection tend to occur where wind changes rapidly with height i.e., in areas with strong vertical wind shear.
This parameter shows how extreme the ensemble forecast of convective available potential energy shear (CAPES) is, relative to the model climate. It is one of the ECMWF Extreme Forecast Indices (EFIs). Values range from -1 to +1.
The closer the EFI is to +1 or -1, the more extreme the forecast CAPES values are.
EFI = 0 indicates that extreme CAPES values are unlikely, although convection can still occur.
EFI = +1 occurs when all the ensemble members' forecast values are above the maximum of the model climate. In this case, it means that very high CAPES values are expected, relative to the model climate .
EFI = -1 occurs when all the ensemble members' forecast values are below the minimum of the model climate. In this case, it means that very low CAPES values are expected, relative to the model climate.
To help determine whether convection will be initiated or not, the probability forecast for precipitation (for example) can be used, in conjunction with this parameter.
The convective available potential energy shear (CAPES) is the product of wind shear and the square root of convective available potential energy (CAPE). The wind shear denotes bulk shear which is a vector difference of winds at two different heights in the atmosphere (925 hPa and 500 hPa). The square root of CAPE is proportional to the maximum vertical velocity in convective updraughts.
","unit_id":106,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":132045,"name":"Water vapour flux index","shortname":"wvfi","description":"Water Vapour Flux Index is a dimensionless parameter which represents the Extreme Forecast Index (EFI) of the Water Vapour Flux (wvf) averaged for a specified forecast period. It varies between -1 and 1. Shift of Tails (SOT) for wvfi is also computed and it can be retrieved by specifying type=sot. For details about wvfi please see:\r\n \r\nLavers, D.A., E. Zsoter, D.S. Richardson, and F. Pappenberger, 2017: An Assessment of the ECMWF Extreme Forecast Index for Water Vapor Transport during Boreal Winter. Wea. Forecasting, 32, 1667–1674, https://doi.org/10.1175/WAF-D-17-0073.1\r\n \r\nLavers, D. A., F. Pappenberger, D. S. Richardson, and E. Zsoter (2016), ECMWF Extreme Forecast Index for water vapor transport: A forecast tool for atmospheric rivers and extreme precipitation, Geophys. Res. Lett., 43, doi:10.1002/2016GL071320.","unit_id":106,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":132049,"name":"10 metre wind gust index","shortname":"10fgi","description":"This parameter indicates how extreme the ensemble forecast 10 metre wind gust is, relative to the model climate. It is one of the ECMWF Extreme Forecast Indices (EFIs). Values range from -1 to +1.
The closer the EFI is to +1 or -1, the more likely an extreme event is.
EFI = 0 indicates an extreme event is unlikely.
EFI = +1 occurs when all the ensemble members' forecast values are above the maximum of the model climate. In this case, it means that much stronger gusts are expected, relative to the model climate.
EFI = -1 occurs when all the ensemble members' forecast values are below the minimum of the model climate. In this case, it means that very calm conditions are expected, relative to the model climate.
The WMO defines a wind gust as the maximum of the wind averaged over 3 second intervals. This duration is shorter than a model time step, and so the ECMWF Integrated Forecasting System deduces the magnitude of a gust within each time step from the time-step-averaged surface stress, surface friction, wind shear and stability. Then, the maximum wind gust is selected from the gusts at each time step during a particular time period which depends on the data extracted.
This parameter is calculated at a height of ten metres above the surface of the Earth.","unit_id":106,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":132059,"name":"Convective available potential energy index","shortname":"capei","description":"
From 48r1 this parameter is based on most unstable CAPE rather than the previously used surface based CAPE.
High values of this parameter indicate where deep convection is more likely to occur, if it is initiated. When air rises through a large depth of the atmosphere, extensive condensation can occur and heavy rainfall, thunderstorms and other severe weather can result.
This parameter shows how extreme the ensemble forecast of convective available potential energy (CAPE) is, relative to the model climate. It is one of the ECMWF Extreme Forecast Indices (EFIs). Values range from -1 to +1.
The closer the EFI is to +1 or -1, the more extreme the forecast CAPE values are.
EFI = 0 indicates that extreme CAPE values are unlikely, although convection can still occur.
EFI = +1 occurs when all the ensemble members' forecast values are above the maximum of the model climate. In this case, it means that very high CAPE values are expected, relative to the model climate.
EFI = -1 occurs when all the ensemble members' forecast values are below the minimum of the model climate. In this case, it means that very low CAPE values are expected, relative to the model climate.
To help determine whether deep, moist convection will be initiated or not, the probability forecast for precipitation (for example) can be used, in conjunction with this parameter.
","unit_id":106,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":132144,"name":"Snowfall index","shortname":"sfi","description":"This parameter indicates how extreme the ensemble forecast accumulated total snowfall is relative to the model climate. It is one of the ECMWF Extreme Forecast Indices (EFIs). Values range from -1 to +1.
The closer the EFI is to +1 or -1, the more likely an extreme event is.
EFI = 0 indicates an extreme event is unlikely.
EFI = +1 occurs when all the ensemble members' forecast values are above the maximum of the model climate. In this case, it means that heavy snowfall is expected, relative to the model climate.
EFI = -1 occurs when all the ensemble members' forecast values are below the minimum of the model climate. In this case, it means that little snowfall is expected, relative to the model climate.
This parameter is based on the accumulated total snow that has fallen to the Earth's surface. Snowfall is the sum of large-scale snowfall and convective snowfall. Large-scale snowfall is generated by the cloud scheme in the ECMWF Integrated Forecast System. The cloud scheme represents the formation and dissipation of clouds and large-scale snowfall due to changes in atmospheric quantities (such as pressure, temperature and moisture) predicted directly by the IFS at spatial scales of a grid box or larger. Convective snowfall is generated by the convection scheme in the IFS. The convection scheme represents convection at spatial scales smaller than the grid box. See further information.
See more information about the EFI. See more information about the ensemble forecast.","unit_id":106,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":132165,"name":"10 metre speed index","shortname":"10wsi","description":"This parameter indicates how extreme the ensemble forecast 10 metre wind speed is, relative to the model climate. It is one of the ECMWF Extreme Forecast Indices (EFIs). Values range from -1 to +1.
The closer the EFI is to +1 or -1, the more likely an extreme event is.
EFI = 0 indicates an extreme event is unlikely.
EFI = +1 occurs when all the ensemble members' forecast values are above the maximum of the model climate. In this case, it means that very windy conditions are expected, relative to the model climate.
EFI = -1 occurs when all the ensemble members' forecast values are below the minimum of the model climate. In this case, it means that very calm conditions are expected, relative to the model climate.
The 10 metre speed is the horizontal speed of the wind, or movement of air, at a height of ten metres above the surface of the Earth.","unit_id":106,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":132167,"name":"2 metre temperature index","shortname":"2ti","description":"This parameter indicates how extreme the ensemble forecast 2 metre temperature is, relative to the model climate. It is one of the ECMWF Extreme Forecast Indices (EFIs). Values range from -1 to +1.
The closer the EFI is to +1 or -1, the more likely an extreme event is.
EFI = 0 indicates an extreme event is unlikely.
EFI = +1 occurs when all the ensemble members' forecast values are above the maximum of the model climate. In this case, it means that very high temperatures are expected, relative to the model climate.
EFI = -1 occurs when all the ensemble members' forecast values are below the minimum of the model climate. In this case, it means that very low temperatures are expected, relative to the model climate.
2m temperature is calculated by interpolating between the lowest model level and the Earth's surface, taking account of the atmospheric conditions. See further information.","unit_id":106,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":132201,"name":"Maximum temperature at 2 metres index","shortname":"mx2ti","description":"This parameter indicates how extreme the ensemble forecast 2 metre maximum temperature is relative to the model climate. It is one of the ECMWF Extreme Forecast Indices (EFIs). Values range from -1 to +1.
The closer the EFI is to +1 or -1, the more likely an extreme event is.
EFI = 0 indicates an extreme event is unlikely.
EFI = +1 occurs when all the ensemble members' forecast values are above the maximum of the model climate. In this case, it means that very high maximum temperatures are expected, relative to the model climate.
EFI = -1 occurs when all the ensemble members' forecast values are below the minimum of the model climate. In this case, it means that very low maximum temperatures are expected, relative to the model climate.
Here, maximum temperature refers to the highest temperature of air at 2m above the surface of land, sea or in-land waters since the parameter was last archived in a particular forecast.
2m temperature is calculated by interpolating between the lowest model level and the Earth's surface, taking account of the atmospheric conditions. See further information.","unit_id":106,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":132202,"name":"Minimum temperature at 2 metres index","shortname":"mn2ti","description":"This parameter indicates how extreme the ensemble forecast 2 metre minimum temperature is relative to the model climate. It is one of the ECMWF Extreme Forecast Indices (EFIs). Values range from -1 to +1.
The closer the EFI is to +1 or -1, the more likely an extreme event is.
EFI = 0 indicates an extreme event is unlikely.
EFI = +1 occurs when all the ensemble members' forecast values are above the maximum of the model climate. In this case, it means that very high minimum temperatures are expected, relative to the model climate.
EFI = -1 occurs when all the ensemble members' forecast values are below the minimum of the model climate. In this case, it means that very low minimum temperatures are expected, relative to the model climate.
Here, maximum temperature refers to the highest temperature of air at 2m above the surface of land, sea or in-land waters since the parameter was last archived in a particular forecast.
2m temperature is calculated by interpolating between the lowest model level and the Earth's surface, taking account of the atmospheric conditions. See further information.","unit_id":106,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":132216,"name":"Maximum of significant wave height index","shortname":"maxswhi","description":"This parameter indicates how extreme the significant wave height is relative to the model climate. It is part of the ECMWF Extreme Forecast Index (EFI). Values range from -1 to +1.
The closer the EFI is to +1 or -1, the more likely an extreme event is.
EFI = 0 indicates an extreme event is unlikely.
EFI = +1 where all the ensemble members' forecast values are above the maximum of the model climate. In this case, it means that very high waves are expected, relative to the model climate.
The significant wave height represents the average height of the highest third of surface ocean/sea waves, generated by local winds and associated with swell. See further information.","unit_id":106,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":132228,"name":"Total precipitation index","shortname":"tpi","description":"This parameter indicates how extreme the ensemble forecast total precipitation is relative to the model climate. It is one of the ECMWF Extreme Forecast Indices (EFIs). Values range from -1 to +1.
The closer the EFI is to +1 or -1, the more likely an extreme event is.
EFI = 0 indicates an extreme event is unlikely.
EFI = +1 occurs when all the ensemble members' forecast values are above the maximum of the model climate. In this case, it means that very wet conditions are expected, relative to the model climate.
EFI = -1 occurs when all the ensemble members' forecast values are below the minimum of the model climate. In this case, it means that very dry conditions are expected, relative to the model climate.
Note that, because precipitation cannot be less than zero, negative values of this parameter calculated for 24-hour (short-term) precipitation do not provide sensible information (typically a dry day is not extreme/unusual). For accumulation of precipitation over longer periods (10 to 15 days for example), negative values indicate extended periods of dry weather.
See more information about the EFI. See more information about the ensemble forecast .","unit_id":106,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":133001,"name":"2m temperature probability less than -10 C","shortname":"2tplm10","description":null,"unit_id":29,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":133002,"name":"2m temperature probability less than -5 C","shortname":"2tplm5","description":null,"unit_id":29,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":133003,"name":"2m temperature probability less than 0 C","shortname":"2tpl0","description":null,"unit_id":29,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":133004,"name":"2m temperature probability less than 5 C","shortname":"2tpl5","description":null,"unit_id":29,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":133005,"name":"2m temperature probability less than 10 C","shortname":"2tpl10","description":null,"unit_id":29,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":133006,"name":"2m temperature probability greater than 25 C","shortname":"2tpg25","description":null,"unit_id":29,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":133007,"name":"2m temperature probability greater than 30 C","shortname":"2tpg30","description":null,"unit_id":29,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":133008,"name":"2m temperature probability greater than 35 C","shortname":"2tpg35","description":null,"unit_id":29,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":133009,"name":"2m temperature probability greater than 40 C","shortname":"2tpg40","description":null,"unit_id":29,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":133010,"name":"2m temperature probability greater than 45 C","shortname":"2tpg45","description":null,"unit_id":29,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":133011,"name":"Minimum 2 metre temperature probability less than -10 C","shortname":"mn2tplm10","description":null,"unit_id":29,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":133012,"name":"Minimum 2 metre temperature probability less than -5 C","shortname":"mn2tplm5","description":null,"unit_id":29,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":133013,"name":"Minimum 2 metre temperature probability less than 0 C","shortname":"mn2tpl0","description":null,"unit_id":29,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":133014,"name":"Minimum 2 metre temperature probability less than 5 C","shortname":"mn2tpl5","description":null,"unit_id":29,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":133015,"name":"Minimum 2 metre temperature probability less than 10 C","shortname":"mn2tpl10","description":null,"unit_id":29,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":133016,"name":"Maximum 2 metre temperature probability greater than 25 C","shortname":"mx2tpg25","description":null,"unit_id":29,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":133017,"name":"Maximum 2 metre temperature probability greater than 30 C","shortname":"mx2tpg30","description":null,"unit_id":29,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":133018,"name":"Maximum 2 metre temperature probability greater than 35 C","shortname":"mx2tpg35","description":null,"unit_id":29,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":133019,"name":"Maximum 2 metre temperature probability greater than 40 C","shortname":"mx2tpg40","description":null,"unit_id":29,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":133020,"name":"Maximum 2 metre temperature probability greater than 45 C","shortname":"mx2tpg45","description":null,"unit_id":29,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":133021,"name":"10 metre wind speed probability of at least 10 m/s","shortname":"10spg10","description":null,"unit_id":29,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":133022,"name":"10 metre wind speed probability of at least 15 m/s","shortname":"10spg15","description":null,"unit_id":29,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":133023,"name":"10 metre wind speed probability of at least 20 m/s","shortname":"10spg20","description":null,"unit_id":29,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":133024,"name":"10 metre wind speed probability of at least 35 m/s","shortname":"10spg35","description":null,"unit_id":29,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":133025,"name":"10 metre wind speed probability of at least 50 m/s","shortname":"10spg50","description":null,"unit_id":29,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":133026,"name":"10 metre wind gust probability of at least 20 m/s","shortname":"10gpg20","description":null,"unit_id":29,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":133027,"name":"10 metre wind gust probability of at least 35 m/s","shortname":"10gpg35","description":null,"unit_id":29,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":133028,"name":"10 metre wind gust probability of at least 50 m/s","shortname":"10gpg50","description":null,"unit_id":29,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":133029,"name":"10 metre wind gust probability of at least 75 m/s","shortname":"10gpg75","description":null,"unit_id":29,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":133030,"name":"10 metre wind gust probability of at least 100 m/s","shortname":"10gpg100","description":null,"unit_id":29,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":133031,"name":"Total precipitation probability of at least 1 mm","shortname":"tppg1","description":null,"unit_id":29,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":133032,"name":"Total precipitation probability of at least 5 mm","shortname":"tppg5","description":null,"unit_id":29,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":133033,"name":"Total precipitation probability of at least 10 mm","shortname":"tppg10","description":null,"unit_id":29,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":133034,"name":"Total precipitation probability of at least 20 mm","shortname":"tppg20","description":null,"unit_id":29,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":133035,"name":"Total precipitation probability of at least 40 mm","shortname":"tppg40","description":null,"unit_id":29,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":133036,"name":"Total precipitation probability of at least 60 mm","shortname":"tppg60","description":null,"unit_id":29,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":133037,"name":"Total precipitation probability of at least 80 mm","shortname":"tppg80","description":null,"unit_id":29,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":133038,"name":"Total precipitation probability of at least 100 mm","shortname":"tppg100","description":null,"unit_id":29,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":133039,"name":"Total precipitation probability of at least 150 mm","shortname":"tppg150","description":null,"unit_id":29,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":133040,"name":"Total precipitation probability of at least 200 mm","shortname":"tppg200","description":null,"unit_id":29,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":133041,"name":"Total precipitation probability of at least 300 mm","shortname":"tppg300","description":null,"unit_id":29,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":133042,"name":"Snowfall probability of at least 1 mm","shortname":"sfpg1","description":null,"unit_id":29,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":133043,"name":"Snowfall probability of at least 5 mm","shortname":"sfpg5","description":null,"unit_id":29,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":133044,"name":"Snowfall probability of at least 10 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40%","shortname":"tccpg40","description":null,"unit_id":29,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":133057,"name":"Total Cloud Cover probability greater than 50%","shortname":"tccpg50","description":null,"unit_id":29,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":133058,"name":"Total Cloud Cover probability greater than 60%","shortname":"tccpg60","description":null,"unit_id":29,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":133059,"name":"Total Cloud Cover probability greater than 70%","shortname":"tccpg70","description":null,"unit_id":29,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":133060,"name":"Total Cloud Cover probability greater than 80%","shortname":"tccpg80","description":null,"unit_id":29,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":133061,"name":"Total Cloud Cover probability greater than 90%","shortname":"tccpg90","description":null,"unit_id":29,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":133062,"name":"Total Cloud Cover probability greater than 99%","shortname":"tccpg99","description":null,"unit_id":29,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":133063,"name":"High Cloud Cover probability greater than 10%","shortname":"hccpg10","description":null,"unit_id":29,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":133064,"name":"High Cloud Cover probability greater than 20%","shortname":"hccpg20","description":null,"unit_id":29,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":133065,"name":"High Cloud Cover probability greater than 30%","shortname":"hccpg30","description":null,"unit_id":29,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":133066,"name":"High Cloud Cover probability greater than 40%","shortname":"hccpg40","description":null,"unit_id":29,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":133067,"name":"High Cloud Cover probability greater than 50%","shortname":"hccpg50","description":null,"unit_id":29,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":133068,"name":"High Cloud Cover probability greater than 60%","shortname":"hccpg60","description":null,"unit_id":29,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":133069,"name":"High Cloud Cover probability greater than 70%","shortname":"hccpg70","description":null,"unit_id":29,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":133070,"name":"High Cloud Cover probability greater than 80%","shortname":"hccpg80","description":null,"unit_id":29,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":133071,"name":"High Cloud Cover probability greater than 90%","shortname":"hccpg90","description":null,"unit_id":29,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":133072,"name":"High Cloud Cover probability greater than 99%","shortname":"hccpg99","description":null,"unit_id":29,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":133073,"name":"Medium Cloud Cover probability greater than 10%","shortname":"mccpg10","description":null,"unit_id":29,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":133074,"name":"Medium Cloud Cover probability greater than 20%","shortname":"mccpg20","description":null,"unit_id":29,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":133075,"name":"Medium Cloud Cover probability greater than 30%","shortname":"mccpg30","description":null,"unit_id":29,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":133076,"name":"Medium Cloud Cover probability greater than 40%","shortname":"mccpg40","description":null,"unit_id":29,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":133077,"name":"Medium Cloud Cover probability greater than 50%","shortname":"mccpg50","description":null,"unit_id":29,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":133078,"name":"Medium Cloud Cover probability greater than 60%","shortname":"mccpg60","description":null,"unit_id":29,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":133079,"name":"Medium Cloud Cover probability greater than 70%","shortname":"mccpg70","description":null,"unit_id":29,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":133080,"name":"Medium Cloud Cover probability greater than 80%","shortname":"mccpg80","description":null,"unit_id":29,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":133081,"name":"Medium Cloud Cover probability greater than 90%","shortname":"mccpg90","description":null,"unit_id":29,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":133082,"name":"Medium Cloud Cover probability greater than 99%","shortname":"mccpg99","description":null,"unit_id":29,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":133083,"name":"Low Cloud Cover probability greater than 10%","shortname":"lccpg10","description":null,"unit_id":29,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":133084,"name":"Low Cloud Cover probability greater than 20%","shortname":"lccpg20","description":null,"unit_id":29,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":133085,"name":"Low Cloud Cover probability greater than 30%","shortname":"lccpg30","description":null,"unit_id":29,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":133086,"name":"Low Cloud Cover probability greater than 40%","shortname":"lccpg40","description":null,"unit_id":29,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":133087,"name":"Low Cloud Cover probability greater than 50%","shortname":"lccpg50","description":null,"unit_id":29,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":133088,"name":"Low Cloud Cover probability greater than 60%","shortname":"lccpg60","description":null,"unit_id":29,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":133089,"name":"Low Cloud Cover probability greater than 70%","shortname":"lccpg70","description":null,"unit_id":29,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":133090,"name":"Low Cloud Cover probability greater than 80%","shortname":"lccpg80","description":null,"unit_id":29,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":133091,"name":"Low Cloud Cover probability greater than 90%","shortname":"lccpg90","description":null,"unit_id":29,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":133092,"name":"Low Cloud Cover probability greater than 99%","shortname":"lccpg99","description":null,"unit_id":29,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":133093,"name":"Probability of temperature standardized anomaly greater than 1 standard deviation","shortname":"ptsa_gt_1stdev","description":"Probability of temperature anomaly greater than 1 standard deviation of the climatology. Climatology is derived from and updated simultaneously with the operational re-forecasts. For the computation of the probability, the closest preceding climatology to the forecast base time is used.","unit_id":29,"encoding_ids":["grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":133094,"name":"Probability of temperature standardized anomaly greater than 1.5 standard deviation","shortname":"ptsa_gt_1p5stdev","description":"Probability of temperature anomaly greater than 1.5 standard deviation of the climatology. Climatology is derived from and updated simultaneously with the operational re-forecasts. For the computation of the probability, the closest preceding climatology to the forecast base time is used.","unit_id":29,"encoding_ids":["grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":133095,"name":"Probability of temperature standardized anomaly greater than 2 standard deviation","shortname":"ptsa_gt_2stdev","description":"Probability of temperature anomaly greater than 2 standard deviation of the climatology. Climatology is derived from and updated simultaneously with the operational re-forecasts. For the computation of the probability, the closest preceding climatology to the forecast base time is used.","unit_id":29,"encoding_ids":["grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":133096,"name":"Probability of temperature standardized anomaly less than -1 standard deviation","shortname":"ptsa_lt_1stdev","description":"Probability of temperature anomaly less than -1 standard deviation of the climatology. Climatology is derived from and updated simultaneously with the operational re-forecasts. For the computation of the probability, the closest preceding climatology to the forecast base time is used.","unit_id":29,"encoding_ids":["grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":133097,"name":"Probability of temperature standardized anomaly less than -1.5 standard deviation","shortname":"ptsa_lt_1p5stdev","description":"Probability of temperature anomaly less than -1.5 standard deviation of the climatology. Climatology is derived from and updated simultaneously with the operational re-forecasts. For the computation of the probability, the closest preceding climatology to the forecast base time is used.","unit_id":29,"encoding_ids":["grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":133098,"name":"Probability of temperature standardized anomaly less than -2 standard deviation","shortname":"ptsa_lt_2stdev","description":"Probability of temperature anomaly less than -2 standard deviation of the climatology. Climatology is derived from and updated simultaneously with the operational re-forecasts. For the computation of the probability, the closest preceding climatology to the forecast base time is used.","unit_id":29,"encoding_ids":["grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":140080,"name":"Wave experimental parameter 1","shortname":"wx1","description":"output parameter from the wave model, not yet in finalised form for operational production","unit_id":7,"encoding_ids":["grib1"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":140081,"name":"Wave experimental parameter 2","shortname":"wx2","description":"output parameter from the wave model, not yet in finalised form for operational production","unit_id":7,"encoding_ids":["grib1"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":140082,"name":"Wave experimental parameter 3","shortname":"wx3","description":"output parameter from the wave model, not yet in finalised form for operational production","unit_id":7,"encoding_ids":["grib1"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":140083,"name":"Wave experimental parameter 4","shortname":"wx4","description":"output parameter from the wave model, not yet in finalised form for operational production","unit_id":7,"encoding_ids":["grib1"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":140084,"name":"Wave experimental parameter 5","shortname":"wx5","description":"output parameter from the wave model, not yet in finalised form for operational production","unit_id":7,"encoding_ids":["grib1"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":140098,"name":"Wave induced mean sea level correction","shortname":"weta","description":"","unit_id":4,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":140099,"name":"Ratio of wave angular and frequency width","shortname":"wraf","description":"","unit_id":106,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":140100,"name":"Number of events in freak waves statistics","shortname":"wnslc","description":"","unit_id":106,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":140101,"name":"U-component of atmospheric surface momentum flux","shortname":"utaua","description":"","unit_id":32,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":140102,"name":"V-component of atmospheric surface momentum flux","shortname":"vtaua","description":"","unit_id":32,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":140103,"name":"U-component of surface momentum flux into ocean","shortname":"utauo","description":"","unit_id":32,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":140104,"name":"V-component of surface momentum flux into ocean","shortname":"vtauo","description":"","unit_id":32,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":140105,"name":"Wave turbulent energy flux into ocean","shortname":"wphio","description":"","unit_id":76,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":140106,"name":"Wave directional width of first swell partition","shortname":"wdw1","description":"","unit_id":30,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":140107,"name":"Wave frequency width of first swell partition","shortname":"wfw1","description":"","unit_id":23,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":140108,"name":"Wave directional width of second swell partition","shortname":"wdw2","description":"","unit_id":30,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":140109,"name":"Wave frequency width of second swell partition","shortname":"wfw2","description":"","unit_id":23,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":140110,"name":"Wave directional width of third swell partition","shortname":"wdw3","description":"","unit_id":30,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":140111,"name":"Wave frequency width of third swell partition","shortname":"wfw3","description":"","unit_id":23,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":140112,"name":"Wave energy flux magnitude","shortname":"wefxm","description":"This parameter is the amount of energy from ocean/sea waves which are generated by local winds and associated with swell. It is the magnitude of the energy flux per unit length of wave crest, also known as the wave power per unit length of wave crest.
In deep water, the wave energy flux magnitude can be estimated from the mean wave period and the significant wave height. In the ECMWF Integrated Forecasting System, it is calculated by integrating the full two-dimensional wave spectrum multiplied by the wave group velocity (the velocity of the envelope of a group of waves of nearly equal frequencies).","unit_id":178,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":140113,"name":"Wave energy flux mean direction","shortname":"wefxd","description":"This parameter is the direction of the flux of energy of ocean/sea waves which are generated by local winds and associated with swell.
It is the spectral mean direction calculated by integrating the full two-dimensional wave energy spectrum multiplied by the wave group velocity (the velocity of the envelope of a group of waves of nearly equal frequencies).
The units are degrees true which means the direction relative to the geographic location of the north pole. It is the direction that waves are coming FROM, so zero means 'coming from the north' and 90 'coming from the east'.","unit_id":92,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":140114,"name":"Significant wave height of all waves with periods within the inclusive range from 10 to 12 seconds","shortname":"h1012","description":"This parameter represents the average height of the highest third of surface ocean/sea waves that have a period between 10 and 12 seconds. It includes all waves generated by local winds and associated with swell. Wave height represents the vertical distance between the wave crest and the wave trough.
The ocean/sea surface wave field consists of a combination of waves with different heights, lengths and directions (known as the two-dimensional wave spectrum). The wave spectrum can be decomposed into wind-sea waves, which are directly affected by local winds, and swell, the waves that were generated by the wind at a different location and time.
More strictly, this parameter is four times the square root of the integral over all directions of the two-dimensional wave spectrum and all frequencies between 1/12 and 1/10 hertz (i.e. periods between 10 and 12 seconds). See further documentation.
This parameter can be used to assess sea state and swell. For example, engineers use significant wave height to calculate the load on structures in the open ocean, such as oil platforms, or in coastal applications.","unit_id":4,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":140115,"name":"Significant wave height of all waves with periods within the inclusive range from 12 to 14 seconds","shortname":"h1214","description":"This parameter represents the average height of the highest third of surface ocean/sea waves that have a period between 12 and 14 seconds. It includes all waves generated by local winds and associated with swell. Wave height represents the vertical distance between the wave crest and the wave trough.
The ocean/sea surface wave field consists of a combination of waves with different heights, lengths and directions (known as the two-dimensional wave spectrum). The wave spectrum can be decomposed into wind-sea waves, which are directly affected by local winds, and swell, the waves that were generated by the wind at a different location and time.
More strictly, this parameter is four times the square root of the integral over all directions of the two-dimensional wave spectrum and all frequencies between 1/14 and 1/12 hertz (i.e. periods between 12 and 14 seconds). See further documentation.
This parameter can be used to assess sea state and swell. For example, engineers use significant wave height to calculate the load on structures in the open ocean, such as oil platforms, or in coastal applications.","unit_id":4,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":140116,"name":"Significant wave height of all waves with periods within the inclusive range from 14 to 17 seconds","shortname":"h1417","description":"This parameter represents the average height of the highest third of surface ocean/sea waves that have a period between 14 and 17 seconds. It includes all waves generated by local winds and associated with swell. Wave height represents the vertical distance between the wave crest and the wave trough.
The ocean/sea surface wave field consists of a combination of waves with different heights, lengths and directions (known as the two-dimensional wave spectrum). The wave spectrum can be decomposed into wind-sea waves, which are directly affected by local winds, and swell, the waves that were generated by the wind at a different location and time.
More strictly, this parameter is four times the square root of the integral over all directions of the two-dimensional wave spectrum and all frequencies between 1/17 and 1/14 hertz (i.e. periods between 14 and 17 seconds). See further documentation.
This parameter can be used to assess sea state and swell. For example, engineers use significant wave height to calculate the load on structures in the open ocean, such as oil platforms, or in coastal applications.","unit_id":4,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":140117,"name":"Significant wave height of all waves with periods within the inclusive range from 17 to 21 seconds","shortname":"h1721","description":"This parameter represents the average height of the highest third of surface ocean/sea waves that have a period between 17 and 21 seconds. It includes all waves generated by local winds and associated with swell. Wave height represents the vertical distance between the wave crest and the wave trough.
The ocean/sea surface wave field consists of a combination of waves with different heights, lengths and directions (known as the two-dimensional wave spectrum). The wave spectrum can be decomposed into wind-sea waves, which are directly affected by local winds, and swell, the waves that were generated by the wind at a different location and time.
More strictly, this parameter is four times the square root of the integral over all directions of the two-dimensional wave spectrum and all frequencies between 1/21 and 1/17 hertz (i.e. periods between 17 and 21 seconds). See further documentation.
This parameter can be used to assess sea state and swell. For example, engineers use significant wave height to calculate the load on structures in the open ocean, such as oil platforms, or in coastal applications.","unit_id":4,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":140118,"name":"Significant wave height of all waves with periods within the inclusive range from 21 to 25 seconds","shortname":"h2125","description":"This parameter represents the average height of the highest third of surface ocean/sea waves that have a period between 21 and 25 seconds. It includes all waves generated by local winds and associated with swell. Wave height represents the vertical distance between the wave crest and the wave trough.
The ocean/sea surface wave field consists of a combination of waves with different heights, lengths and directions (known as the two-dimensional wave spectrum). The wave spectrum can be decomposed into wind-sea waves, which are directly affected by local winds, and swell, the waves that were generated by the wind at a different location and time.
More strictly, this parameter is four times the square root of the integral over all directions of the two-dimensional wave spectrum and all frequencies between 1/25 and 1/21 hertz (i.e. periods between 21 and 25 seconds). See further documentation.
This parameter can be used to assess sea state and swell. For example, engineers use significant wave height to calculate the load on structures in the open ocean, such as oil platforms, or in coastal applications.","unit_id":4,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":140119,"name":"Significant wave height of all waves with periods within the inclusive range from 25 to 30 seconds","shortname":"h2530","description":"This parameter represents the average height of the highest third of surface ocean/sea waves that have a period between 25 and 30 seconds. It includes all waves generated by local winds and associated with swell. Wave height represents the vertical distance between the wave crest and the wave trough.
The ocean/sea surface wave field consists of a combination of waves with different heights, lengths and directions (known as the two-dimensional wave spectrum). The wave spectrum can be decomposed into wind-sea waves, which are directly affected by local winds, and swell, the waves that were generated by the wind at a different location and time.
More strictly, this parameter is four times the square root of the integral over all directions of the two-dimensional wave spectrum and all frequencies between 1/30 and 1/25 hertz (i.e. periods between 25 and 30 seconds). See further documentation.
This parameter can be used to assess sea state and swell. For example, engineers use significant wave height to calculate the load on structures in the open ocean, such as oil platforms, or in coastal applications.","unit_id":4,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":140120,"name":"Significant wave height of all waves with period larger than 10s","shortname":"sh10","description":"This parameter represents the average height of the highest third of surface ocean/sea waves that have a period of longer than 10 seconds. It includes all waves generated by local winds and associated with swell. Wave height represents the vertical distance between the wave crest and the wave trough.
The ocean/sea surface wave field consists of a combination of waves with different heights, lengths and directions (known as the two-dimensional wave spectrum). The wave spectrum can be decomposed into wind-sea waves, which are directly affected by local winds, and swell, the waves that were generated by the wind at a different location and time.
More strictly, this parameter is four times the square root of the integral over all directions of the two-dimensional wave spectrum and over frequencies less than 0.1 hertz (i.e. periods longer than 10 seconds). See further documentation.
This parameter can be used to assess sea state and swell. For example, engineers use significant wave height to calculate the load on structures in the open ocean, such as oil platforms, or in coastal applications.","unit_id":4,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":140121,"name":"Significant wave height of first swell partition","shortname":"swh1","description":"This parameter represents the average height of the highest third of surface ocean/sea waves associated with the first swell partition. Wave height represents the vertical distance between the wave crest and the wave trough.
The ocean/sea surface wave field consists of a combination of waves with different heights, lengths and directions (known as the two-dimensional wave spectrum). The wave spectrum can be decomposed into wind-sea waves, which are directly affected by local winds, and swell, the waves that were generated by the wind at a different location and time.
In many situations, swell can be made up of different swell systems, for example, from two distant and separate storms. To account for this, the swell spectrum is partitioned into up to three parts. The swell partitions are labelled first, second and third based on their respective wave height. Therefore, there is no guarantee of spatial coherence (the first might be from one system at one location and another system at the neighbouring location). See further information.
More strictly, this parameter is four times the square root of the integral over all directions and all frequencies of the first swell partition of the two-dimensional swell spectrum. The swell spectrum is obtained by only considering the components of the two-dimensional wave spectrum that are not under the influence of the local wind.
This parameter can be used to assess swell. For example, engineers use significant wave height to calculate the load on structures in the open ocean, such as oil platforms, or in coastal applications.","unit_id":4,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":140122,"name":"Mean wave direction of first swell partition","shortname":"mwd1","description":"This parameter is the mean direction of waves in the first swell partition.
The ocean/sea surface wave field consists of a combination of waves with different heights, lengths and directions (known as the two-dimensional wave spectrum). The wave spectrum can be decomposed into wind-sea waves, which are directly affected by local winds, and swell, the waves that were generated by the wind at a different location and time.
In many situations, swell can be made up of different swell systems, for example, from two distant and separate storms. To account for this, the swell spectrum is partitioned into up to three parts. The swell partitions are labelled first, second and third based on their respective wave height. Therefore, there is no guarantee of spatial coherence (the first swell partition might be from one system at one location and a different system at the neighbouring location). See further information.
The units are degrees true which means the direction relative to the geographic location of the north pole. It is the direction that waves are coming FROM, so zero means 'coming from the north' and 90 'coming from the east'.","unit_id":41,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":140123,"name":"Mean wave period of first swell partition","shortname":"mwp1","description":"This parameter is the mean period of waves in the first swell partition. The wave period is the average time it takes for two consecutive wave crests, on the surface of the ocean/sea, to pass through a fixed point.
The ocean/sea surface wave field consists of a combination of waves with different heights, lengths and directions (known as the two-dimensional wave spectrum). The wave spectrum can be decomposed into wind-sea waves, which are directly affected by local winds, and swell, the waves that were generated by the wind at a different location and time.
In many situations, swell can be made up of different swell systems, for example, from two distant and separate storms. To account for this, the swell spectrum is partitioned into up to three parts. The swell partitions are labelled first, second and third based on their respective wave height. Therefore, there is no guarantee of spatial coherence (the first swell partition might be from one system at one location and a different system at the neighbouring location). See further information.","unit_id":12,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":140124,"name":"Significant wave height of second swell partition","shortname":"swh2","description":"This parameter represents the average height of the highest third of surface ocean/sea waves associated with the second swell partition. Wave height represents the vertical distance between the wave crest and the wave trough.
The ocean/sea surface wave field consists of a combination of waves with different heights, lengths and directions (known as the two-dimensional wave spectrum). The wave spectrum can be decomposed into wind-sea waves, which are directly affected by local winds, and swell, the waves that were generated by the wind at a different location and time.
In many situations, swell can be made up of different swell systems, for example, from two distant and separate storms. To account for this, the swell spectrum is partitioned into up to three parts. The swell partitions are labelled first, second and third based on their respective wave height. Therefore, there is no guarantee of spatial coherence (the second might be from one system at one location and another system at the neighbouring location). See further information.
More strictly, this parameter is four times the square root of the integral over all directions and all frequencies of the first swell partition of the two-dimensional swell spectrum. The swell spectrum is obtained by only considering the components of the two-dimensional wave spectrum that are not under the influence of the local wind.
This parameter can be used to assess swell. For example, engineers use significant wave height to calculate the load on structures in the open ocean, such as oil platforms, or in coastal applications.","unit_id":4,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":140125,"name":"Mean wave direction of second swell partition","shortname":"mwd2","description":"This parameter is the mean direction of waves in the second swell partition.
The ocean/sea surface wave field consists of a combination of waves with different heights, lengths and directions (known as the two-dimensional wave spectrum). The wave spectrum can be decomposed into wind-sea waves, which are directly affected by local winds, and swell, the waves that were generated by the wind at a different location and time.
In many situations, swell can be made up of different swell systems, for example, from two distant and separate storms. To account for this, the swell spectrum is partitioned into up to three parts. The swell partitions are labelled first, second and third based on their respective wave height. Therefore, there is no guarantee of spatial coherence (the second swell partition might be from one system at one location and a different system at the neighbouring location). See further information.
The units are degrees true which means the direction relative to the geographic location of the north pole. It is the direction that waves are coming FROM, so zero means 'coming from the north' and 90 'coming from the east'.","unit_id":41,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":140126,"name":"Mean wave period of second swell partition","shortname":"mwp2","description":"This parameter is the mean period of waves in the second swell partition. The wave period is the average time it takes for two consecutive wave crests, on the surface of the ocean/sea, to pass through a fixed point.
The ocean/sea surface wave field consists of a combination of waves with different heights, lengths and directions (known as the two-dimensional wave spectrum). The wave spectrum can be decomposed into wind-sea waves, which are directly affected by local winds, and swell, the waves that were generated by the wind at a different location and time.
In many situations, swell can be made up of different swell systems, for example, from two distant and separate storms. To account for this, the swell spectrum is partitioned into up to three parts. The swell partitions are labelled first, second and third based on their respective wave height. Therefore, there is no guarantee of spatial coherence (the second swell partition might be from one system at one location and a different system at the neighbouring location). See further information.","unit_id":12,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":140127,"name":"Significant wave height of third swell partition","shortname":"swh3","description":"This parameter represents the average height of the highest third of surface ocean/sea waves associated with the third swell partition. Wave height represents the vertical distance between the wave crest and the wave trough.
The ocean/sea surface wave field consists of a combination of waves with different heights, lengths and directions (known as the two-dimensional wave spectrum). The wave spectrum can be decomposed into wind-sea waves, which are directly affected by local winds, and swell, the waves that were generated by the wind at a different location and time.
In many situations, swell can be made up of different swell systems, for example, from two distant and separate storms. To account for this, the swell spectrum is partitioned into up to three parts. The swell partitions are labelled first, second and third based on their respective wave height. Therefore, there is no guarantee of spatial coherence (the third might be from one system at one location and another system at the neighbouring location). See further information.
More strictly, this parameter is four times the square root of the integral over all directions and all frequencies of the first swell partition of the two-dimensional swell spectrum. The swell spectrum is obtained by only considering the components of the two-dimensional wave spectrum that are not under the influence of the local wind.
This parameter can be used to assess swell. For example, engineers use significant wave height to calculate the load on structures in the open ocean, such as oil platforms, or in coastal applications.","unit_id":4,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":140128,"name":"Mean wave direction of third swell partition","shortname":"mwd3","description":"This parameter is the mean direction of waves in the third swell partition.
The ocean/sea surface wave field consists of a combination of waves with different heights, lengths and directions (known as the two-dimensional wave spectrum). The wave spectrum can be decomposed into wind-sea waves, which are directly affected by local winds, and swell, the waves that were generated by the wind at a different location and time.
In many situations, swell can be made up of different swell systems, for example, from two distant and separate storms. To account for this, the swell spectrum is partitioned into up to three parts. The swell partitions are labelled first, second and third based on their respective wave height. Therefore, there is no guarantee of spatial coherence (the third swell partition might be from one system at one location and a different system at the neighbouring location). See further information.
The units are degrees true which means the direction relative to the geographic location of the north pole. It is the direction that waves are coming FROM, so zero means 'coming from the north' and 90 'coming from the east'.","unit_id":41,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":140129,"name":"Mean wave period of third swell partition","shortname":"mwp3","description":"This parameter is the mean period of waves in the third swell partition. The wave period is the average time it takes for two consecutive wave crests, on the surface of the ocean/sea, to pass through a fixed point.
The ocean/sea surface wave field consists of a combination of waves with different heights, lengths and directions (known as the two-dimensional wave spectrum). The wave spectrum can be decomposed into wind-sea waves, which are directly affected by local winds, and swell, the waves that were generated by the wind at a different location and time.
In many situations, swell can be made up of different swell systems, for example, from two distant and separate storms. To account for this, the swell spectrum is partitioned into up to three parts. The swell partitions are labelled first, second and third based on their respective wave height. Therefore, there is no guarantee of spatial coherence (the third swell partition might be from one system at one location and a different system at the neighbouring location). See further information.","unit_id":12,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":140131,"name":"Time domain maximum individual crest height","shortname":"tdcmax","description":"The detailed description of this parameter can be found in the appendix section of the following publication:\r\nFrancesco Barbariol, Jean-Raymond Bidlot, Luigi Cavaleri, Mauro Sclavo, Jim Thomson, Alvise Benetazzo\r\nmaximum wave heights from global model reanalysis\r\nProgress in Oceanography (IF4.08), Pub Date : 2019-07-01, DOI: 10.1016/j.pocean.2019.03.009\r\n \r\nSee equation 2.","unit_id":4,"encoding_ids":["grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":140132,"name":"Time domain maximum individual wave height","shortname":"tdhmax","description":"The detailed description of this parameter can be found in the appendix section of the following publication:\r\nFrancesco Barbariol, Jean-Raymond Bidlot, Luigi Cavaleri, Mauro Sclavo, Jim Thomson, Alvise Benetazzo\r\nmaximum wave heights from global model reanalysis\r\nProgress in Oceanography (IF4.08), Pub Date : 2019-07-01, DOI: 10.1016/j.pocean.2019.03.009\r\n \r\nSee equation 5.","unit_id":4,"encoding_ids":["grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":140133,"name":"Space time maximum individual crest height","shortname":"stcmax","description":"The detailed description of this parameter can be found in the appendix section of the following publication:\r\nFrancesco Barbariol, Jean-Raymond Bidlot, Luigi Cavaleri, Mauro Sclavo, Jim Thomson, Alvise Benetazzo\r\nmaximum wave heights from global model reanalysis\r\nProgress in Oceanography (IF4.08), Pub Date : 2019-07-01, DOI: 10.1016/j.pocean.2019.03.009\r\n \r\nSee equation 10.","unit_id":4,"encoding_ids":["grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":140134,"name":"Space time maximum individual wave height","shortname":"sthmax","description":"The detailed description of this parameter can be found in the appendix section of the following publication:\r\nFrancesco Barbariol, Jean-Raymond Bidlot, Luigi Cavaleri, Mauro Sclavo, Jim Thomson, Alvise Benetazzo\r\nmaximum wave heights from global model reanalysis\r\nProgress in Oceanography (IF4.08), Pub Date : 2019-07-01, DOI: 10.1016/j.pocean.2019.03.009\r\n \r\nSee equation 11.","unit_id":4,"encoding_ids":["grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":140135,"name":"Peak wave period of wind waves","shortname":"pp1dw","description":null,"unit_id":12,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":140136,"name":"Peak wave period of total swell","shortname":"pp1ds","description":null,"unit_id":12,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":140137,"name":"Peak wave period of first swell partition","shortname":"pp1d1","description":null,"unit_id":12,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":140138,"name":"Peak wave period of second swell partition","shortname":"pp1d2","description":null,"unit_id":12,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":140139,"name":"Peak wave period of third swell partition","shortname":"pp1d3","description":null,"unit_id":12,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":140140,"name":"Peak wave direction (total)","shortname":"pwd","description":null,"unit_id":92,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":140141,"name":"Peak wave direction of wind waves","shortname":"pwdw","description":null,"unit_id":92,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":140142,"name":"Peak wave direction of total swell","shortname":"pwds","description":null,"unit_id":92,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":140143,"name":"Peak wave direction of first swell partition","shortname":"pwd1","description":null,"unit_id":92,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":140144,"name":"Peak wave direction of second swell partition","shortname":"pwd2","description":null,"unit_id":92,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":140145,"name":"Peak wave direction of third swell partition","shortname":"pwd3","description":null,"unit_id":92,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":140146,"name":"Whitecap fraction","shortname":"wcfr","description":null,"unit_id":168,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":140147,"name":"Benjamin-Feir index 2D","shortname":"bfi2d","description":null,"unit_id":106,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":140148,"name":"Crest-trough correlation","shortname":"ctc","description":null,"unit_id":106,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":140149,"name":"X component of the wave radiative stress to sea ice","shortname":"xwrs","description":null,"unit_id":32,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":140150,"name":"Y component of the wave radiative stress to sea ice","shortname":"ywrs","description":null,"unit_id":32,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":140200,"name":"Maximum of significant wave height","shortname":"maxswh","description":"This parameter is used to give the significant wave height climate distribution as obtained from the wave ensemble forecast hindcast runs","unit_id":4,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":140207,"name":"Wave Spectral Skewness","shortname":"wss","description":"This parameter is a statistical measure used to forecast extreme or freak ocean/sea waves. It describes the nature of the sea surface elevation and how it is affected by waves generated by local winds and associated with swell.
Under typical conditions, the sea surface elevation, as described by its probability density function, has a near normal distribution in the statistical sense. However, under certain wave conditions the probability density function of the sea surface elevation can deviate considerably from normality, signalling increased probability of freak waves.
This parameter gives one measure of the deviation from normality. It is a measure of the asymmetry of the probability density function of the sea surface elevation. So, a positive/negative skewness (typical range -0.2 to 0.12) means more frequent occurrences of extreme values above/below the mean, relative to a normal distribution.","unit_id":106,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":140208,"name":"Free convective velocity over the oceans","shortname":"wstar","description":"This parameter is an estimate of the vertical velocity of updraughts generated by free convection. Free convection is fluid motion induced by buoyancy forces, which are driven by density gradients. The free convective velocity is used to estimate the impact of wind gusts on ocean wave growth.
It is calculated at the height of the lowest temperature inversion (the height above the surface of the Earth where the temperature increases with height).
This parameter is one of the parameters used to force the wave model, therefore it is only calculated over water bodies represented in the ocean wave model. It is interpolated from the atmospheric model horizontal grid onto the horizontal grid used by the ocean wave model.","unit_id":5,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":140209,"name":"Air density over the oceans","shortname":"rhoao","description":"This parameter is the mass of air per cubic metre over the oceans, derived from the temperature, specific humidity and pressure at the lowest model level in the atmospheric model.
This parameter is one of the parameters used to force the wave model, therefore it is only calculated over water bodies represented in the ocean wave model. It is interpolated from the atmospheric model horizontal grid onto the horizontal grid used by the ocean wave model.","unit_id":9,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":140210,"name":"Mean square wave strain in sea ice","shortname":"mswsi","description":"When waves propagate into a sea ice field, they generate mechanical strain\nonto the floating ice sheets. This can be estimated in mean square sense by computing\nthe following integral over frequency (f): \nInt {F(f) E(f)^2 df}, \nwhere \nF(f) is the frequency wave spectrum. \nE(f) is the strain in the ice: \nE(f) = h k_ice^3 / (2k) \nwith h the ice thickness, k the wave number in the water, k_ice is the wave number under the ice.","unit_id":7,"encoding_ids":["grib1"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":140211,"name":"Normalized energy flux into waves","shortname":"phiaw","description":"This parameter is the normalised vertical flux of energy from wind into the ocean waves. A positive flux implies a flux into the waves.
The energy flux has units of Watts per metre squared, and this is normalised by being divided by the product of air density and the cube of the friction velocity.\n Parameters are normalised by being divided by the product of air density and the square of the friction velocity.","unit_id":106,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":140212,"name":"Normalized energy flux into ocean","shortname":"phioc","description":"This parameter is the normalised vertical flux of turbulent kinetic energy from ocean waves into the ocean. The energy flux is calculated from an estimation of white capping waves across the surface of the ocean. A white capping wave is one that appears white at its crest as it breaks, due to air being mixed into the water. When waves break in this way, there is a transfer of energy from the waves to the ocean. A negative flux implies a flux from the waves into the ocean.
The energy flux has units of Watts per metre squared, and this is normalised by being divided by the product of air density and the cube of the friction velocity.\n Parameters are normalised by being divided by the product of air density and the square of the friction velocity.","unit_id":106,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":140213,"name":"Turbulent Langmuir number","shortname":"tla","description":"Square root of the ratio of friction velocity to the surface Stokes drift.\nThis parameter is currently not produced.","unit_id":7,"encoding_ids":["grib1"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":140214,"name":"Normalized stress into ocean","shortname":"tauoc","description":"This parameter is the normalised surface stress, or momentum flux, from the air into the ocean due to turbulence at the air-sea interface and breaking waves. It does not include the flux used to generate waves. The ECMWF convention for vertical fluxes is positive downwards.
The stress has units of Newtons per metre squared, and this is normalised by being divided by the product of air density and the square of the friction velocity.\n Parameters are normalised by being divided by the product of air density and the square of the friction velocity.","unit_id":106,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":140215,"name":"U-component surface stokes drift","shortname":"ust","description":"This parameter is the eastward component of the surface Stokes drift. The Stokes drift is the net drift velocity due to surface wind waves. It is confined to the upper few metres of the ocean water column, with the largest value at the surface.
For example, a fluid particle near the surface will slowly move in the direction of wave propagation.","unit_id":5,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":140216,"name":"V-component surface stokes drift","shortname":"vst","description":"This parameter is the northward component of the surface Stokes drift. The Stokes drift is the net drift velocity due to surface wind waves. It is confined to the upper few metres of the ocean water column, with the largest value at the surface.
For example, a fluid particle near the surface will slowly move in the direction of wave propagation.","unit_id":5,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":140217,"name":"Period corresponding to maximum individual wave height","shortname":"tmax","description":"This parameter is the period of the expected highest individual wave within a 20-minute time window. It can be used as a guide to the characteristics of extreme or freak waves. Wave period is the average time it takes for two consecutive wave crests, on the surface of the ocean/sea, to pass through a fixed point.
Occasionally waves of different periods reinforce and interact non-linearly giving a wave height considerably larger than the significant wave height. If the maximum individual wave height is more than twice the significant wave height, then the wave is considered to be a freak wave. The significant wave height represents the average height of the highest third of surface ocean/sea waves, generated by local winds and associated with swell.
The ocean/sea surface wave field consists of a combination of waves with different heights, lengths and directions (known as the two-dimensional wave spectrum). This parameter is derived statistically from the two-dimensional wave spectrum. See further information.
The wave spectrum can be decomposed into wind-sea waves, which are directly affected by local winds, and swell, the waves that were generated by the wind at a different location and time. This parameter takes account of both.","unit_id":12,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":140218,"name":"Envelop-maximum individual wave height","shortname":"hmax","description":"
This parameter is an estimate of the height of the expected highest individual wave within a 20 minute time window. It can be used as a guide to the likelihood of extreme or freak waves.
The interactions between waves are non-linear and occasionally concentrate wave energy giving a wave height considerably larger than the significant wave height. If the maximum individual wave height is more than twice the significant wave height, then the wave is considered as a freak wave. The significant wave height represents the average height of the highest third of surface ocean/sea waves, generated by local winds and associated with swell.
The ocean/sea surface wave field consists of a combination of waves with different heights, lengths and directions (known as the two-dimensional wave spectrum). This parameter is derived statistically from the two-dimensional wave spectrum. See further information.
The wave spectrum can be decomposed into wind-sea waves, which are directly affected by local winds, and swell, the waves that were generated by the wind at a different location and time. This parameter takes account of both.
","unit_id":4,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":140219,"name":"Model bathymetry","shortname":"wmb","description":"This parameter is the depth of water from the surface to the bottom of the ocean. It is used by the ocean wave model to specify the propagation properties of the different waves that could be present.
Note that the ocean wave model grid is too coarse to resolve some small islands and mountains on the bottom of the ocean, but they can have an impact on surface ocean waves. The ocean wave model has been modified to reduce the wave energy flowing around or over features at spatial scales smaller than the grid box.","unit_id":4,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":140220,"name":"Mean wave period based on first moment","shortname":"mp1","description":"This parameter is the reciprocal of the mean frequency of the wave components that represent the sea state. All wave components have been averaged proportionally to their respective amplitude. This parameter can be used to estimate the magnitude of Stokes drift transport in deep water.
The ocean/sea surface wave field consists of a combination of waves with different heights, lengths and directions (known as the two-dimensional wave spectrum). Moments are statistical quantities derived from the two-dimensional wave spectrum.","unit_id":12,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":140221,"name":"Mean zero-crossing wave period","shortname":"mp2","description":"This parameter represents the mean length of time between occasions where the sea/ocean surface crosses mean sea level. In combination with wave height information, it could be used to assess the length of time that a coastal structure might be under water, for example.
The ocean/sea surface wave field consists of a combination of waves with different heights, lengths and directions (known as the two-dimensional wave spectrum). In the ECMWF Integrated Forecasting System this parameter is calculated from the characteristics of the two-dimensional wave spectrum.","unit_id":12,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":140222,"name":"Wave spectral directional width","shortname":"wdw","description":"This parameter indicates whether waves (generated by local winds and associated with swell) are coming from similar directions or from a wide range of directions.
The ocean/sea surface wave field consists of a combination of waves with different heights, lengths and directions (known as the two-dimensional wave spectrum). Many ECMWF wave parameters (such as the mean wave period) give information averaged over all wave frequencies and directions, so do not give any information about the distribution of wave energy across frequencies and directions. This parameter gives more information about the nature of the two-dimensional wave spectrum. This parameter is a measure of the range of wave directions for each frequency integrated across the two-dimensional spectrum.
This parameter takes values between 0 and the square root of 2. Where 0 corresponds to a uni-directional spectrum (i.e., all wave frequencies from the same direction) and the square root of 2 indicates a uniform spectrum (i.e., all wave frequencies from a different direction).","unit_id":30,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":140223,"name":"Mean wave period based on first moment for wind waves","shortname":"p1ww","description":"This parameter is the reciprocal of the mean frequency of the wave components generated by local winds. All wave components have been averaged proportionally to their respective amplitude. This parameter can be used to estimate the magnitude of Stokes drift transport in deep water associated with wind waves.
The ocean/sea surface wave field consists of a combination of waves with different heights, lengths and directions (known as the two-dimensional wave spectrum). The wave spectrum can be decomposed into wind-sea waves, which are directly affected by local winds, and swell, the waves that were generated by the wind at a different location and time.This parameter takes account of wind-sea waves only. Moments are statistical quantities derived from the two-dimensional wave spectrum.","unit_id":12,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":140224,"name":"Mean wave period based on second moment for wind waves","shortname":"p2ww","description":"This parameter is equivalent to the zero-crossing mean wave period for waves generated by local winds. The zero-crossing mean wave period represents the mean length of time between occasions where the sea/ocean surface crosses a defined zeroth level (such as mean sea level).
The ocean/sea surface wave field consists of a combination of waves with different heights, lengths and directions (known as the two-dimensional wave spectrum). The wave spectrum can be decomposed into wind-sea waves, which are directly affected by local winds, and swell, the waves that were generated by the wind at a different location and time. Moments are statistical quantities derived from the two-dimensional wave spectrum.","unit_id":12,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":140225,"name":"Wave spectral directional width for wind waves","shortname":"dwww","description":"This parameter indicates whether waves generated by the local wind are coming from similar directions or from a wide range of directions.
The ocean/sea surface wave field consists of a combination of waves with different heights, lengths and directions (known as the two-dimensional wave spectrum). The wave spectrum can be decomposed into wind-sea waves, which are directly affected by local winds, and swell, the waves that were generated by the wind at a different location and time. This parameter takes account of wind-sea waves only.
Many ECMWF wave parameters (such as the mean wave period) give information averaged over all wave frequencies and directions, so do not give any information about the distribution of wave energy across frequencies and directions. This parameter gives more information about the nature of the two-dimensional wave spectrum. This parameter is a measure of the range of wave directions for each frequency integrated across the two-dimensional spectrum.
This parameter takes values between 0 and the square root of 2. Where 0 corresponds to a uni-directional spectrum (i.e., all wave frequencies from the same direction) and the square root of 2 indicates a uniform spectrum (i.e., all wave frequencies from a different direction).","unit_id":30,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":140226,"name":"Mean wave period based on first moment for swell","shortname":"p1ps","description":"This parameter is the reciprocal of the mean frequency of the wave components associated with swell. All wave components have been averaged proportionally to their respective amplitude. This parameter can be used to estimate the magnitude of Stokes drift transport in deep water associated with swell.
The ocean/sea surface wave field consists of a combination of waves with different heights, lengths and directions (known as the two-dimensional wave spectrum). The wave spectrum can be decomposed into wind-sea waves, which are directly affected by local winds, and swell, the waves that were generated by the wind at a different location and time.This parameter takes account of all swell only. Moments are statistical quantities derived from the two-dimensional wave spectrum.","unit_id":12,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":140227,"name":"Mean wave period based on second moment for swell","shortname":"p2ps","description":"This parameter is equivalent to the zero-crossing mean wave period for swell. The zero-crossing mean wave period represents the mean length of time between occasions where the sea/ocean surface crosses a defined zeroth level (such as mean sea level).
The ocean/sea surface wave field consists of a combination of waves with different heights, lengths and directions (known as the two-dimensional wave spectrum). The wave spectrum can be decomposed into wind-sea waves, which are directly affected by local winds, and swell, the waves that were generated by the wind at a different location and time. Moments are statistical quantities derived from the two-dimensional wave spectrum.","unit_id":12,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":140228,"name":"Wave spectral directional width for swell","shortname":"dwps","description":"This parameter indicates whether waves associated with swell are coming from similar directions or from a wide range of directions.
The ocean/sea surface wave field consists of a combination of waves with different heights, lengths and directions (known as the two-dimensional wave spectrum). The wave spectrum can be decomposed into wind-sea waves, which are directly affected by local winds, and swell, the waves that were generated by the wind at a different location and time. This parameter takes account of all swell only.
Many ECMWF wave parameters (such as the mean wave period) give information averaged over all wave frequencies and directions, so do not give any information about the distribution of wave energy across frequencies and directions. This parameter gives more information about the nature of the two-dimensional wave spectrum. This parameter is a measure of the range of wave directions for each frequency integrated across the two-dimensional spectrum.
This parameter takes values between 0 and the square root of 2. Where 0 corresponds to a uni-directional spectrum (i.e., all wave frequencies from the same direction) and the square root of 2 indicates a uniform spectrum (i.e., all wave frequencies from a different direction).","unit_id":30,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":140229,"name":"Significant height of combined wind waves and swell","shortname":"swh","description":"This parameter represents the average height of the highest third of surface ocean/sea waves generated by wind and swell. It represents the vertical distance between the wave crest and the wave trough.
The ocean/sea surface wave field consists of a combination of waves with different heights, lengths and directions (known as the two-dimensional wave spectrum).
The wave spectrum can be decomposed into wind-sea waves, which are directly affected by local winds, and swell, the waves that were generated by the wind at a different location and time. This parameter takes account of both.
More strictly, this parameter is four times the square root of the integral over all directions and all frequencies of the two-dimensional wave spectrum. See further documentation.
This parameter can be used to assess sea state and swell. For example, engineers use significant wave height to calculate the load on structures in the open ocean, such as oil platforms, or in coastal applications.","unit_id":4,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":140230,"name":"Mean wave direction","shortname":"mwd","description":"This parameter is the mean direction of ocean/sea surface waves. The ocean/sea surface wave field consists of a combination of waves with different heights, lengths and directions (known as the two-dimensional wave spectrum). This parameter is a mean over all frequencies and directions of the two-dimensional wave spectrum.
The wave spectrum can be decomposed into wind-sea waves, which are directly affected by local winds, and swell, the waves that were generated by the wind at a different location and time. This parameter takes account of both. See further documentation.
This parameter can be used to assess sea state and swell. For example, engineers use this type of wave information when designing structures in the open ocean, such as oil platforms, or in coastal applications.
The units are degree true which means the direction relative to the geographic location of the north pole. Zero means 'coming from the north' and 90 'coming from the east'.","unit_id":92,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":140231,"name":"Peak wave period","shortname":"pp1d","description":"This parameter represents the period of the most energetic ocean waves generated by local winds and associated with swell. The wave period is the average time it takes for two consecutive wave crests, on the surface of the ocean/sea, to pass through a fixed point.
The ocean/sea surface wave field consists of a combination of waves with different heights, lengths and directions (known as the two-dimensional wave spectrum). This parameter is calculated from the reciprocal of the frequency corresponding to the largest value (peak) of the frequency wave spectrum. The frequency wave spectrum is obtained by integrating the two-dimensional wave spectrum over all directions.
The wave spectrum can be decomposed into wind-sea waves, which are directly affected by local winds, and swell, the waves that were generated by the wind at a different location and time. This parameter takes account of both.","unit_id":12,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":140232,"name":"Mean wave period","shortname":"mwp","description":"This parameter is the average time it takes for two consecutive wave crests, on the surface of the ocean/sea, to pass through a fixed point. The ocean/sea surface wave field consists of a combination of waves with different heights, lengths and directions (known as the two-dimensional wave spectrum). This parameter is a mean over all frequencies and directions of the two-dimensional wave spectrum.
The wave spectrum can be decomposed into wind-sea waves, which are directly affected by local winds, and swell, the waves that were generated by the wind at a different location and time. This parameter takes account of both. See further documentation.
This parameter can be used to assess sea state and swell. For example, engineers use such wave information when designing structures in the open ocean, such as oil platforms, or in coastal applications.","unit_id":12,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":140233,"name":"Coefficient of drag with waves","shortname":"cdww","description":"This parameter is the resistance that ocean waves exert on the atmosphere. It is sometimes also called a 'friction coefficient'.
It is calculated by the wave model as the ratio of the square of the friction velocity, to the square of the neutral wind speed at a height of 10 metres above the surface of the Earth.
The neutral wind is calculated from the surface stress and the corresponding roughness length by assuming that the air is neutrally stratified. The neutral wind is, by definition, in the direction of the surface stress. The size of the roughness length depends on the sea state.","unit_id":23,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":140234,"name":"Significant height of wind waves","shortname":"shww","description":"This parameter represents the average height of the highest third of surface ocean/sea waves generated by the local wind. It represents the vertical distance between the wave crest and the wave trough.
The ocean/sea surface wave field consists of a combination of waves with different heights, lengths and directions (known as the two-dimensional wave spectrum). The wave spectrum can be decomposed into wind-sea waves, which are directly affected by local winds, and swell, the waves that were generated by the wind at a different location and time. This parameter takes account of wind-sea waves only.
More strictly, this parameter is four times the square root of the integral over all directions and all frequencies of the two-dimensional wind-sea wave spectrum. The wind-sea wave spectrum is obtained by only considering the components of the two-dimensional wave spectrum that are still under the influence of the local wind. See further documentation.
This parameter can be used to assess wind-sea waves. For example, engineers use significant wave height to calculate the load on structures in the open ocean, such as oil platforms, or in coastal applications.","unit_id":4,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":140235,"name":"Mean direction of wind waves","shortname":"mdww","description":"The mean direction of waves generated by local winds.
The ocean/sea surface wave field consists of a combination of waves with different heights, lengths and directions (known as the two-dimensional wave spectrum). The wave spectrum can be decomposed into wind-sea waves, which are directly affected by local winds, and swell, the waves that were generated by the wind at a different location and time.This parameter takes account of wind-sea waves only. It is the mean over all frequencies and directions of the total wind-sea wave spectrum. See further information.
The units are degrees true which means the direction relative to the geographic location of the north pole. It is the direction that waves are coming FROM, so zero means 'coming from the north' and 90 'coming from the east'.","unit_id":41,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":140236,"name":"Mean period of wind waves","shortname":"mpww","description":"This parameter is the average time it takes for two consecutive wave crests, on the surface of the ocean/sea generated by local winds, to pass through a fixed point.
The ocean/sea surface wave field consists of a combination of waves with different heights, lengths and directions (known as the two-dimensional wave spectrum). The wave spectrum can be decomposed into wind-sea waves, which are directly affected by local winds, and swell, the waves that were generated by the wind at a different location and time. This parameter takes account of wind-sea waves only. It is the mean over all frequencies and directions of the total wind-sea spectrum. See further information.","unit_id":12,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":140237,"name":"Significant height of total swell","shortname":"shts","description":"This parameter represents the average height of the highest third of surface ocean/sea waves associated with swell. It represents the vertical distance between the wave crest and the wave trough.
The ocean/sea surface wave field consists of a combination of waves with different heights, lengths and directions (known as the two-dimensional wave spectrum). The wave spectrum can be decomposed into wind-sea waves, which are directly affected by local winds, and swell, the waves that were generated by the wind at a different location and time. This parameter takes account of total swell only.
More strictly, this parameter is four times the square root of the integral over all directions and all frequencies of the two-dimensional total swell spectrum. The total swell spectrum is obtained by only considering the components of the two-dimensional wave spectrum that are not under the influence of the local wind. See further documentation.
This parameter can be used to assess swell. For example, engineers use significant wave height to calculate the load on structures in the open ocean, such as oil platforms, or in coastal applications.","unit_id":4,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":140238,"name":"Mean direction of total swell","shortname":"mdts","description":"This parameter is the mean direction of waves associated with swell.
The ocean/sea surface wave field consists of a combination of waves with different heights, lengths and directions (known as the two-dimensional wave spectrum). The wave spectrum can be decomposed into wind-sea waves, which are directly affected by local winds, and swell, the waves that were generated by the wind at a different location and time.This parameter takes account of all swell only. It is the mean over all frequencies and directions of the total swell spectrum. See further information.
The units are degrees true which means the direction relative to the geographic location of the north pole. It is the direction that waves are coming FROM, so zero means 'coming from the north' and 90 'coming from the east'.","unit_id":41,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":140239,"name":"Mean period of total swell","shortname":"mpts","description":"This parameter is the average time it takes for two consecutive wave crests, on the surface of the ocean/sea associated with swell, to pass through a fixed point.
The ocean/sea surface wave field consists of a combination of waves with different heights, lengths and directions (known as the two-dimensional wave spectrum). The wave spectrum can be decomposed into wind-sea waves, which are directly affected by local winds, and swell, the waves that were generated by the wind at a different location and time. This parameter takes account of all swell only. It is the mean over all frequencies and directions of the total swell spectrum. See further information.","unit_id":12,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":140240,"name":"Standard deviation wave height","shortname":"sdhs","description":"
Used only for post processed wave climate fields before ERA-interim.
This parameter is only available in GRIB1.
","unit_id":4,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":140241,"name":"Mean of 10 metre wind speed","shortname":"mu10","description":"
Used only for post processed wave climate fields before ERA-interim.
Used only for post processed wave climate fields before ERA-interim.
This parameter is only available in GRIB1.
","unit_id":41,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":140243,"name":"Standard deviation of 10 metre wind speed","shortname":"sdu","description":"
Used only for post processed wave climate fields before ERA-interim.
This parameter is only available in GRIB1.
","unit_id":5,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":140244,"name":"Mean square slope of waves","shortname":"msqs","description":"This parameter can be related analytically to the average slope of combined wind-sea and swell waves. It can also be expressed as a function of wind speed under some statistical assumptions. The higher the slope, the steeper the waves. This parameter indicates the roughness of the sea/ocean surface which affects the interaction between ocean and atmosphere. See further information.
The ocean/sea surface wave field consists of a combination of waves with different heights, lengths and directions (known as the two-dimensional wave spectrum). This parameter is derived statistically from the two-dimensional wave spectrum.","unit_id":23,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":140245,"name":"10 metre wind speed","shortname":"wind","description":"This parameter is the horizontal speed of the 'neutral wind', at a height of ten metres above the surface of the Earth. The units of this parameter are metres per second.
The neutral wind is calculated from the surface stress and the corresponding roughness length by assuming that the air is neutrally stratified. The neutral wind is, by definition, in the direction of the surface stress. The size of the roughness length depends on sea state.
This parameter is the wind speed used to force the wave model, therefore it is only calculated over water bodies represented in the ocean wave model. It is interpolated from the atmospheric model's horizontal grid onto the horizontal grid used by the ocean wave model. ","unit_id":5,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":140246,"name":"Altimeter wave height","shortname":"awh","description":" Gridded altimeter wave height data as presented to the wave model data assimilation scheme. This parameter only exists as type analysis.","unit_id":4,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":140247,"name":"Altimeter corrected wave height","shortname":"acwh","description":" Gridded bias corrected altimeter wave height data as presented to the wave model data assimilation scheme. This parameter only exists as type analysis.","unit_id":4,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":140248,"name":"Altimeter range relative correction","shortname":"arrc","description":"Gridded altimeter range correction as determined from the wave model. This parameter only exists as type analysis.","unit_id":7,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":140249,"name":"10 metre wind direction","shortname":"dwi","description":"This parameter is the direction from which the 'neutral wind' blows, in degrees clockwise from true north, at a height of ten metres above the surface of the Earth.
The neutral wind is calculated from the surface stress and roughness length by assuming that the air is neutrally stratified. The neutral wind is, by definition, in the direction of the surface stress. The size of the roughness length depends on the sea state.
This parameter is the wind direction used to force the wave model, therefore it is only calculated over water bodies represented in the ocean wave model. It is interpolated from the atmospheric model's horizontal grid onto the horizontal grid used by the ocean wave model.","unit_id":41,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":140250,"name":"2D wave spectra (multiple)","shortname":"2dsp","description":"This parameter has not been used since 1998. It has been replaced by 2D wave spectra (single)","unit_id":42,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":140251,"name":"2D wave spectra (single)","shortname":"2dfd","description":"The ocean/sea surface wave field consists of a combination of waves with different heights, lengths and directions (known as the two-dimensional wave spectrum). This parameter represents the wave energy for each frequency and direction at each model grid point i.e., it describes the contribution to the frequency and direction of the two-dimensional wave spectrum.
Strictly, this parameter is the base ten logarithm of the spectral density of ocean waves in two dimensions (across the horizontal surface of the ocean). Therefore, all values (except missing data) need to be raised to the power of ten to give the spectral density. 'Missing data' is indicated by a value of 0. The spectral density describes the combination of waves with different heights, lengths and directions. See further documentation.","unit_id":42,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":140252,"name":"Wave spectral kurtosis","shortname":"wsk","description":"This parameter is a statistical measure used to forecast extreme or freak ocean/sea waves. It describes the nature of the sea surface elevation and how it is affected by waves generated by local winds and associated with swell.
Under typical conditions, the sea surface elevation, as described by its probability density function, has a near normal distribution in the statistical sense. However, under certain wave conditions the probability density function of the sea surface elevation can deviate considerably from normality, signalling increased probability of freak waves.
This parameter gives one measure of the deviation from normality. It shows how much of the probability density function of the sea surface elevation exists in the tails of the distribution. So, a positive kurtosis (typical range 0.0 to 0.06) means more frequent occurrences of very extreme values (either above or below the mean), relative to a normal distribution.","unit_id":23,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":140253,"name":"Benjamin-Feir index","shortname":"bfi","description":"This parameter is used to calculate the likelihood of freak ocean waves, which are waves that are higher than twice the mean height of the highest third of waves. Large values of this parameter (in practice of the order 1) indicate increased probability of the occurrence of freak waves.
The ocean/sea surface wave field consists of a combination of waves with different heights, lengths and directions (known as the two-dimensional wave spectrum). This parameter is derived from the statistics of the two-dimensional wave spectrum. More precisely, it is the square of the ratio of the integral ocean wave steepness and the relative width of the frequency spectrum of the waves.
Further information on the calculation of this parameter is given in Section 10.6 of the ECMWF Wave Model documentation.","unit_id":23,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":140254,"name":"Wave spectral peakedness","shortname":"wsp","description":"This parameter is a statistical measure used to forecast extreme or freak waves. It is a measure of the relative width of the ocean/sea wave frequency spectrum (i.e., whether the ocean/sea wave field is made up of a narrow or broad range of frequencies).
The ocean/sea surface wave field consists of a combination of waves with different heights, lengths and directions (known as the two-dimensional wave spectrum). When the wave field is more focussed around a narrow range of frequencies, the probability of freak/extreme waves increases.
This parameter is Goda's peakedness factor and is used to calculate the Benjamin-Feir Index (BFI). The BFI is in turn used to estimate the probability and nature of extreme/freak waves.","unit_id":23,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":140255,"name":"Indicates a missing value","shortname":"~","description":null,"unit_id":7,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":141098,"name":"Time-mean wave induced mean sea level correction","shortname":"avg_weta","description":null,"unit_id":4,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":141099,"name":"Time-mean ratio of wave angular and frequency width","shortname":"avg_wraf","description":null,"unit_id":106,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":141100,"name":"Time-mean number of events in freak waves statistics","shortname":"avg_wnslc","description":null,"unit_id":106,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":141101,"name":"Time-mean U-component of atmospheric surface momentum flux","shortname":"avg_utaua","description":null,"unit_id":32,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":141102,"name":"Time-mean V-component of atmospheric surface momentum flux","shortname":"avg_vtaua","description":null,"unit_id":32,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":141103,"name":"Time-mean U-component of surface momentum flux into ocean","shortname":"avg_utauo","description":null,"unit_id":32,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":141104,"name":"Time-mean V-component of surface momentum flux into ocean","shortname":"avg_vtauo","description":null,"unit_id":32,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":141105,"name":"Time-mean wave turbulent energy flux into ocean","shortname":"avg_wphio","description":null,"unit_id":76,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":141106,"name":"Time-mean wave directional width of first swell partition","shortname":"avg_wdw1","description":null,"unit_id":30,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":141107,"name":"Time-mean wave frequency width of first swell partition","shortname":"avg_wfw1","description":null,"unit_id":23,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":141108,"name":"Time-mean wave directional width of second swell partition","shortname":"avg_wdw2","description":null,"unit_id":30,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":141109,"name":"Time-mean wave frequency width of second swell partition","shortname":"avg_wfw2","description":null,"unit_id":23,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":141110,"name":"Time-mean wave directional width of third swell partition","shortname":"avg_wdw3","description":null,"unit_id":30,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":141111,"name":"Time-mean wave frequency width of third swell partition","shortname":"avg_wfw3","description":null,"unit_id":23,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":141112,"name":"Time-mean wave energy flux magnitude","shortname":"avg_wefxm","description":null,"unit_id":178,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":141113,"name":"Time-mean wave energy flux mean direction","shortname":"avg_wefxd","description":null,"unit_id":92,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":141114,"name":"Time-mean significant wave height of all waves with periods within the inclusive range from 10 to 12 seconds","shortname":"avg_h1012","description":null,"unit_id":4,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":141115,"name":"Time-mean significant wave height of all waves with periods within the inclusive range from 12 to 14 seconds","shortname":"avg_h1214","description":null,"unit_id":4,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":141116,"name":"Time-mean significant wave height of all waves with periods within the inclusive range from 14 to 17 seconds","shortname":"avg_h1417","description":null,"unit_id":4,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":141117,"name":"Time-mean significant wave height of all waves with periods within the inclusive range from 17 to 21 seconds","shortname":"avg_h1721","description":null,"unit_id":4,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":141118,"name":"Time-mean significant wave height of all waves with periods within the inclusive range from 21 to 25 seconds","shortname":"avg_h2125","description":null,"unit_id":4,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":141119,"name":"Time-mean significant wave height of all waves with periods within the inclusive range from 25 to 30 seconds","shortname":"avg_h2530","description":null,"unit_id":4,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":141120,"name":"Time-mean significant wave height of all waves with period larger than 10s","shortname":"avg_sh10","description":null,"unit_id":4,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":141121,"name":"Time-mean significant wave height of first swell partition","shortname":"avg_swh1","description":null,"unit_id":4,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":141122,"name":"Time-mean mean wave direction of first swell partition","shortname":"avg_mwd1","description":null,"unit_id":41,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":141123,"name":"Time-mean mean wave period of first swell partition","shortname":"avg_mwp1","description":null,"unit_id":12,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":141124,"name":"Time-mean significant wave height of second swell partition","shortname":"avg_swh2","description":null,"unit_id":4,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":141125,"name":"Time-mean mean wave direction of second swell partition","shortname":"avg_mwd2","description":null,"unit_id":41,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":141126,"name":"Time-mean mean wave period of second swell partition","shortname":"avg_mwp2","description":null,"unit_id":12,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":141127,"name":"Time-mean significant wave height of third swell partition","shortname":"avg_swh3","description":null,"unit_id":4,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":141128,"name":"Time-mean mean wave direction of third swell partition","shortname":"avg_mwd3","description":null,"unit_id":41,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":141129,"name":"Time-mean mean wave period of third swell partition","shortname":"avg_mwp3","description":null,"unit_id":12,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":141131,"name":"Time-mean time domain maximum individual crest height","shortname":"avg_tdcmax","description":null,"unit_id":4,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":141132,"name":"Time-mean time domain maximum individual wave height","shortname":"avg_tdhmax","description":null,"unit_id":4,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":141133,"name":"Time-mean space time maximum individual crest height","shortname":"avg_stcmax","description":null,"unit_id":4,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":141134,"name":"Time-mean space time maximum individual wave height","shortname":"avg_sthmax","description":null,"unit_id":4,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":141135,"name":"Time-mean peak wave period of wind waves","shortname":"avg_pp1dw","description":null,"unit_id":12,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":141136,"name":"Time-mean peak wave period of total swell","shortname":"avg_pp1ds","description":null,"unit_id":12,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":141137,"name":"Time-mean peak wave period of first swell partition","shortname":"avg_pp1d1","description":null,"unit_id":12,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":141138,"name":"Time-mean peak wave period of second swell partition","shortname":"avg_pp1d2","description":null,"unit_id":12,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":141139,"name":"Time-mean peak wave period of third swell partition","shortname":"avg_pp1d3","description":null,"unit_id":12,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":141140,"name":"Time-mean peak wave direction 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temperature","shortname":"qtrea","description":null,"unit_id":2,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":160212,"name":"Covariance of U component and geopotential","shortname":"uzrea","description":null,"unit_id":60,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":160213,"name":"Covariance of U component and temperature","shortname":"utrea","description":null,"unit_id":61,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":160214,"name":"Covariance of U component and specific humidity","shortname":"uqrea","description":null,"unit_id":5,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":160216,"name":"Covariance of V component and geopotential","shortname":"vzrea","description":null,"unit_id":60,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":160217,"name":"Covariance of V component and temperature","shortname":"vtrea","description":null,"unit_id":61,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":160218,"name":"Covariance of V component and specific humidity","shortname":"vqrea","description":null,"unit_id":5,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":160219,"name":"Covariance of V component and U component","shortname":"vurea","description":null,"unit_id":15,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":160221,"name":"Covariance of W component and geopotential","shortname":"wzrea","description":null,"unit_id":62,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":160222,"name":"Covariance of W component and temperature","shortname":"wtrea","description":null,"unit_id":63,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":160223,"name":"Covariance of W component and specific humidity","shortname":"wqrea","description":null,"unit_id":26,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":160224,"name":"Covariance of W component and U component","shortname":"wurea","description":null,"unit_id":64,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":160225,"name":"Covariance of W component and V component","shortname":"wvrea","description":null,"unit_id":64,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":160231,"name":"Instantaneous surface heat flux","shortname":"ishfrea","description":null,"unit_id":6,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":160239,"name":"Convective snowfall","shortname":"csfrea","description":null,"unit_id":33,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":160240,"name":"Large scale snowfall","shortname":"lsfrea","description":null,"unit_id":33,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":160241,"name":"Cloud liquid water content","shortname":"clwcerrea","description":null,"unit_id":21,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":160242,"name":"Cloud cover","shortname":"ccrea","description":null,"unit_id":3,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":160243,"name":"Forecast albedo","shortname":"falrea","description":null,"unit_id":7,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":160246,"name":"10 metre wind speed","shortname":"10wsrea","description":null,"unit_id":5,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":160247,"name":"Momentum flux","shortname":"moflrea","description":null,"unit_id":32,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":160249,"name":"Gravity wave dissipation flux","shortname":"~","description":null,"unit_id":6,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":160254,"name":"Heaviside beta function","shortname":"hsdrea","description":null,"unit_id":3,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":162031,"name":"Total column vertically-integrated divergence of water geopotential flux","shortname":"viwgd","description":null,"unit_id":76,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":162032,"name":"Total column vertically-integrated eastward enthalpy flux","shortname":"viee","description":null,"unit_id":178,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":162033,"name":"Total column vertically-integrated northward enthalpy flux","shortname":"vien","description":null,"unit_id":178,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":162034,"name":"Total column vertically-integrated divergence of enthalpy flux","shortname":"vied","description":null,"unit_id":76,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":162035,"name":"Total column vertically-integrated divergence of water enthalpy flux","shortname":"viwed","description":null,"unit_id":76,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":162036,"name":"Total column vertically-integrated divergence of water vapour flux","shortname":"viwvd","description":null,"unit_id":33,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":162037,"name":"Total column vertically-integrated divergence of cloud liquid water flux","shortname":"viclwd","description":null,"unit_id":33,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":162038,"name":"Total column vertically-integrated divergence of cloud ice water flux","shortname":"viciwd","description":null,"unit_id":33,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":162039,"name":"Total column vertically-integrated divergence of rain flux","shortname":"vird","description":null,"unit_id":33,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":162040,"name":"Total column vertically-integrated divergence of snow flux","shortname":"visd","description":null,"unit_id":33,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":162041,"name":"Total column vertically-integrated eastward cloud liquid water flux","shortname":"viclwe","description":null,"unit_id":66,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":162042,"name":"Total column vertically-integrated northward cloud liquid water flux","shortname":"viclwn","description":null,"unit_id":66,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":162043,"name":"Total column vertically-integrated eastward cloud ice water flux","shortname":"viciwe","description":null,"unit_id":66,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":162044,"name":"Total column vertically-integrated northward cloud ice water flux","shortname":"viciwn","description":null,"unit_id":66,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":162045,"name":"Water vapour flux","shortname":"wvf","description":"Water Vapour Flux represents the magnitude of the combined vertical integrals of the eastward and northward water vapour flux components. The average value of each component over a specified forecast period (e.g. 24 hours) is computed using the instantaneous values from each output forecast step; these are then combined to make the total wvf, which is then used to compute the model climate and the Extreme Forecast Index (EFI) for Water Vapour Flux (wvfi)","unit_id":66,"encoding_ids":["grib1"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":162046,"name":"Total column vertically-integrated eastward rain flux","shortname":"vire","description":null,"unit_id":66,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":162047,"name":"Total column vertically-integrated northward rain flux","shortname":"virn","description":null,"unit_id":66,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":162048,"name":"Total column vertically-integrated eastward snow flux","shortname":"vise","description":null,"unit_id":66,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":162049,"name":"Total column vertically-integrated northward snow flux","shortname":"visn","description":null,"unit_id":66,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":162050,"name":"Total column vertically-integrated net source of ozone","shortname":"vions","description":null,"unit_id":33,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":162051,"name":"Surface geopotential","shortname":"~","description":null,"unit_id":15,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":162053,"name":"Total column vertically-integrated mass of atmosphere","shortname":"vima","description":"This parameter is the total mass of air for a column extending from the surface of the Earth to the top of the atmosphere, per square metre.
This parameter is calculated by dividing surface pressure by the Earth's gravitational acceleration, g (=9.80665 m s-2), and has units of kilograms per square metre.
This parameter can be used to study the atmospheric mass budget. See further information.","unit_id":22,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":162054,"name":"Total column vertically-integrated temperature","shortname":"vit","description":"
This parameter is the mass-weighted vertical integral of temperature for a column of air extending from the surface of the Earth to the top of the atmosphere.
","unit_id":65,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":162055,"name":"Total column vertically-integrated water vapour","shortname":"viwv","description":"","unit_id":22,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":162056,"name":"Total column vertically-integrated cloud liquid water","shortname":"vilw","description":"","unit_id":22,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":162057,"name":"Total column vertically-integrated cloud frozen water","shortname":"viiw","description":"","unit_id":22,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":162058,"name":"Total column vertically-integrated ozone","shortname":"vioz","description":"","unit_id":22,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":162059,"name":"Total column vertically-integrated kinetic energy","shortname":"vike","description":"","unit_id":6,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":162060,"name":"Total column vertically-integrated enthalpy","shortname":"vithe","description":"This parameter is the mass-weighted vertical integral of thermal energy for a column of air extending from the surface of the Earth to the top of the atmosphere. Thermal energy is calculated from the product of temperature and the specific heat capacity of air at constant pressure.
The thermal energy is equal to enthalpy, which is the sum of the internal energy and the energy associated with the pressure of the air on its surroundings.
Internal energy is the energy contained within a system i.e., the microscopic energy of the air molecules, rather than the macroscopic energy associated with, for example, wind, or gravitational potential energy. The energy associated with the pressure of the air on its surroundings is the energy required to make room for the system by displacing its surroundings and is calculated from the product of pressure and volume.
This parameter can be used to study the atmospheric energy budget.
Total atmospheric energy is made up of internal, potential, kinetic and latent energy. See further documentation.","unit_id":6,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":162061,"name":"Total column vertically-integrated potential + internal energy","shortname":"vipie","description":"This parameter is the mass weighted vertical integral of potential and internal energy for a column of air extending from the surface of the Earth to the top of the atmosphere.
The potential energy of an air parcel is the amount of work that would have to be done, against the force of gravity, to lift the air to that location from mean sea level. Internal energy is the energy contained within a system i.e., the microscopic energy of the air molecules, rather than the macroscopic energy associated with, for example, wind, or gravitational potential energy.
This parameter can be used to study the atmospheric energy budget.
Total atmospheric energy is made up of internal, potential, kinetic and latent energy. See further documentation.","unit_id":6,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":162062,"name":"Total column vertically-integrated potential+internal+latent energy","shortname":"vipile","description":"This parameter is the mass weighted vertical integral of potential, internal and latent energy for a column of air extending from the surface of the Earth to the top of the atmosphere.
The potential energy of an air parcel is the amount of work that would have to be done, against the force of gravity, to lift the air to that location from mean sea level. Internal energy is the energy contained within a system i.e., the microscopic energy of the air molecules, rather than the macroscopic energy associated with, for example, wind, or gravitational potential energy.
The latent energy refers to the energy associated with the water vapour in the atmosphere and is equal to the energy required to convert liquid water into water vapour.
This parameter can be used to study the atmospheric energy budget.
Total atmospheric energy is made up of internal, potential, kinetic and latent energy. See further documentation.","unit_id":6,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":162063,"name":"Total column vertically-integrated total energy","shortname":"vitoe","description":"","unit_id":6,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":162064,"name":"Total column vertically-integrated energy conversion","shortname":"viec","description":"This parameter is one contribution to the amount of energy being converted between kinetic energy, and internal plus potential energy, for a column of air extending from the surface of the Earth to the top of the atmosphere. Negative values indicate a conversion to kinetic energy from potential plus internal energy.
This parameter can be used to study the atmospheric energy budget. The circulation of the atmosphere can also be considered in terms of energy conversions.
See further documentation.","unit_id":76,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":162065,"name":"Total column vertically-integrated eastward mass flux","shortname":"vimae","description":"
This parameter is the horizontal rate of flow of mass, in the eastward direction, per metre across the flow, for a column of air extending from the surface of the Earth to the top of the atmosphere. Positive values indicate a flux from west to east.
This parameter can be used to study the atmospheric mass and energy budgets. See further information.
","unit_id":66,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":162066,"name":"Total column vertically-integrated northward mass flux","shortname":"viman","description":"
This parameter is the horizontal rate of flow of mass, in the northward direction, per metre across the flow, for a column of air extending from the surface of the Earth to the top of the atmosphere. Positive values indicate a flux from south to north.
This parameter can be used to study the atmospheric mass and energy budgets. See further information.
","unit_id":66,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":162067,"name":"Total column vertically-integrated eastward kinetic energy flux","shortname":"vikee","description":"
This parameter is the horizontal rate of flow of kinetic energy, in the eastward direction, per metre across the flow, for a column of air extending from the surface of the Earth to the top of the atmosphere. Positive values indicate a flux from west to east.
Atmospheric kinetic energy is the energy of the atmosphere due to its motion. Only horizontal motion is considered in the calculation of this parameter.
This parameter can be used to study the atmospheric energy budget.
","unit_id":178,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":162068,"name":"Total column vertically-integrated northward kinetic energy flux","shortname":"viken","description":"
This parameter is the horizontal rate of flow of kinetic energy, in the northward direction, per metre across the flow, for a column of air extending from the surface of the Earth to the top of the atmosphere. Positive values indicate a flux from south to north.
Atmospheric kinetic energy is the energy of the atmosphere due to its motion. Only horizontal motion is considered in the calculation of this parameter.
This parameter can be used to study the atmospheric energy budget.
","unit_id":178,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":162069,"name":"Total column vertically-integrated eastward heat flux","shortname":"vithee","description":"This parameter is the horizontal rate of flow of heat in the eastward direction, per meter across the flow, for a column of air extending from the surface of the Earth to the top of the atmosphere. Positive values indicate a flux from west to east.
Heat (or thermal energy) is equal to enthalpy, which is the sum of the internal energy and the energy associated with the pressure of the air on its surroundings.
Internal energy is the energy contained within a system i.e., the microscopic energy of the air molecules, rather than the macroscopic energy associated with, for example, wind, or gravitational potential energy. The energy associated with the pressure of the air on its surroundings is the energy required to make room for the system by displacing its surroundings and is calculated from the product of pressure and volume.
This parameter can be used to study the atmospheric energy budget.
See further documentation.","unit_id":178,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":162070,"name":"Total column vertically-integrated northward heat flux","shortname":"vithen","description":"This parameter is the horizontal rate of flow of heat in the northward direction, per meter across the flow, for a column of air extending from the surface of the Earth to the top of the atmosphere. Positive values indicate a flux from south to north.
Heat (or thermal energy) is equal to enthalpy, which is the sum of the internal energy and the energy associated with the pressure of the air on its surroundings.
Internal energy is the energy contained within a system i.e., the microscopic energy of the air molecules, rather than the macroscopic energy associated with, for example, wind, or gravitational potential energy. The energy associated with the pressure of the air on its surroundings is the energy required to make room for the system by displacing its surroundings and is calculated from the product of pressure and volume.
This parameter can be used to study the atmospheric energy budget.
See further documentation.","unit_id":178,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":162071,"name":"Total column vertically-integrated eastward water vapour flux","shortname":"viwve","description":"This parameter is the horizontal rate of flow of water vapour, in the eastward direction, per metre across the flow, for a column of air extending from the surface of the Earth to the top of the atmosphere. Positive values indicate a flux from west to east.","unit_id":66,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":162072,"name":"Total column vertically-integrated northward water vapour flux","shortname":"viwvn","description":"This parameter is the horizontal rate of flow of water vapour, in the northward direction, per metre across the flow, for a column of air extending from the surface of the Earth to the top of the atmosphere. Positive values indicate a flux from south to north.","unit_id":66,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":162073,"name":"Total column vertically-integrated eastward geopotential flux","shortname":"vige","description":null,"unit_id":178,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":162074,"name":"Total column vertically-integrated northward geopotential flux","shortname":"vign","description":"
This parameter is the horizontal rate of flow of geopotential in the northward direction, per metre across the flow, for a column of air extending from the surface of the Earth to the top of the atmosphere. Positive values indicate a flux from south to north.
Geopotential is the gravitational potential energy of a unit mass, at a particular location, relative to mean sea level. It is also the amount of work that would have to be done, against the force of gravity, to lift a unit mass to that location from mean sea level.
","unit_id":178,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":162075,"name":"Total column vertically-integrated eastward total energy flux","shortname":"vitee","description":"
This parameter is the horizontal rate of flow of total energy in the eastward direction, per metre across the flow, for a column of air extending from the surface of the Earth to the top of the atmosphere. Positive values indicate a flux from west to east.
Total atmospheric energy is made up of internal, potential, kinetic and latent energy.
This parameter can be used to study the atmospheric energy budget.
","unit_id":178,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":162076,"name":"Total column vertically-integrated northward total energy flux","shortname":"viten","description":"
This parameter is the horizontal rate of flow of total energy in the northward direction, per metre across the flow, for a column of air extending from the surface of the Earth to the top of the atmosphere. Positive values indicate a flux from south to north.
Total atmospheric energy is made up of internal, potential, kinetic and latent energy.
This parameter can be used to study the atmospheric energy budget.
This parameter is the horizontal rate of flow of ozone in the eastward direction, per metre across the flow, for a column of air extending from the surface of the Earth to the top of the atmosphere. Positive values denote a flux from west to east.
In the ECMWF Integrated Forecasting System (IFS), there is a simplified representation of ozone chemistry (including a representation of the chemistry which has caused the ozone hole). Ozone is also transported around in the atmosphere through the motion of air. See further documentation.
This parameter is the horizontal rate of flow of ozone in the northward direction, per metre across the flow, for a column of air extending from the surface of the Earth to the top of the atmosphere. Positive values denote a flux from south to north.
In the ECMWF Integrated Forecasting System (IFS), there is a simplified representation of ozone chemistry (including a representation of the chemistry which has caused the ozone hole). Ozone is also transported around in the atmosphere through the motion of air.See further documentation.
","unit_id":66,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":162079,"name":"Total column vertically-integrated divergence of cloud liquid water flux","shortname":"vilwd","description":"
The vertical integral of the cloud liquid water flux is the horizontal rate of flow of cloud liquid water, per metre across the flow, for a column of air extending from the surface of the Earth to the top of the atmosphere. Its horizontal divergence is the rate of cloud liquid water spreading outward from a point, per square metre. This parameter is positive for cloud liquid water that is spreading out, or diverging, and negative for the opposite, for cloud liquid water that is concentrating, or converging (convergence).
This parameter thus indicates whether atmospheric motions act to decrease (for divergence) or increase (for convergence) the vertical integral of cloud liquid water.
","unit_id":33,"encoding_ids":["grib1"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":162080,"name":"Total column vertically-integrated divergence of cloud frozen water flux","shortname":"viiwd","description":"The vertical integral of the cloud frozen water flux is the horizontal rate of flow of cloud frozen water, per metre across the flow, for a column of air extending from the surface of the Earth to the top of the atmosphere. Its horizontal divergence is the rate of cloud frozen water spreading outward from a point, per square metre. This parameter is positive for cloud frozen water that is spreading out, or diverging, and negative for the opposite, for cloud frozen water that is concentrating, or converging (convergence).
This parameter thus indicates whether atmospheric motions act to decrease (for divergence) or increase (for convergence) the vertical integral of cloud frozen water.
Note that 'cloud frozen water' is the same as 'cloud ice water'.","unit_id":33,"encoding_ids":["grib1"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":162081,"name":"Total column vertically-integrated divergence of mass flux","shortname":"vimad","description":"
The vertical integral of the mass flux is the horizontal rate of flow of mass, per metre across the flow, for a column of air extending from the surface of the Earth to the top of the atmosphere. Its horizontal divergence is the rate of mass spreading outward from a point, per square metre.
This parameter is positive for mass that is spreading out, or diverging, and negative for the opposite, for mass that is concentrating, or converging (convergence).
This parameter thus indicates whether atmospheric motions act to decrease (for divergence) or increase (for convergence) the vertical integral of mass.
This parameter can be used to study the atmospheric mass and energy budgets. See further information.
","unit_id":33,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":162082,"name":"Total column vertically-integrated divergence of kinetic energy flux","shortname":"viked","description":"
The vertical integral of the kinetic energy flux is the horizontal rate of flow of kinetic energy, per metre across the flow, for a column of air extending from the surface of the Earth to the top of the atmosphere. Its horizontal divergence is the rate of kinetic energy spreading outward from a point, per square metre. This parameter is positive for kinetic energy that is spreading out, or diverging, and negative for the opposite, for kinetic energy that is concentrating, or converging (convergence).
This parameter thus indicates whether atmospheric motions act to decrease (for divergence) or increase (for convergence) the vertical integral of kinetic energy.
Atmospheric kinetic energy is the energy of the atmosphere due to its motion. Only horizontal motion is considered in the calculation of this parameter.
This parameter can be used to study the atmospheric energy budget.
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This parameter thus indicates whether atmospheric motions act to decrease (for divergence) or increase (for convergence) the vertical integral of thermal energy.
The thermal energy is equal to enthalpy, which is the sum of the internal energy and the energy associated with the pressure of the air on its surroundings.
Internal energy is the energy contained within a system i.e., the microscopic energy of the air molecules, rather than the macroscopic energy associated with, for example, wind, or gravitational potential energy. The energy associated with the pressure of the air on its surroundings is the energy required to make room for the system by displacing its surroundings and is calculated from the product of pressure and volume.
This parameter can be used to study the flow of thermal energy through the climate system and to investigate the atmospheric energy budget.","unit_id":76,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":162084,"name":"Total column vertically-integrated moisture divergence flux","shortname":"vimdf","description":"
The vertical integral of the moisture flux is the horizontal rate of flow of moisture, per metre across the flow, for a column of air extending from the surface of the Earth to the top of the atmosphere. Its horizontal divergence is the rate of moisture spreading outward from a point, per square metre.
This parameter is positive for moisture that is spreading out, or diverging, and negative for the opposite, for moisture that is concentrating, or converging (convergence).
This parameter thus indicates whether atmospheric motions act to decrease (for divergence) or increase (for convergence) the vertical integral of moisture.
","unit_id":33,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":162085,"name":"Total column vertically-integrated divergence of geopotential flux","shortname":"vigd","description":"
The vertical integral of the geopotential flux is the horizontal rate of flow of geopotential, per metre across the flow, for a column of air extending from the surface of the Earth to the top of the atmosphere. Its horizontal divergence is the rate of geopotential spreading outward from a point, per square metre.
This parameter is positive for geopotential that is spreading out, or diverging, and negative for the opposite, for geopotential that is concentrating, or converging (convergence).
This parameter thus indicates whether atmospheric motions act to decrease (for divergence) or increase (for convergence) the vertical integral of geopotential.
Geopotential is the gravitational potential energy of a unit mass, at a particular location, relative to mean sea level. It is also the amount of work that would have to be done, against the force of gravity, to lift a unit mass to that location from mean sea level.
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The vertical integral of the ozone flux is the horizontal rate of flow of ozone, per metre across the flow, for a column of air extending from the surface of the Earth to the top of the atmosphere. Its horizontal divergence is the rate of ozone spreading outward from a point, per square metre. This parameter is positive for ozone that is spreading out, or diverging, and negative for the opposite, for ozone that is concentrating, or converging (convergence).
This parameter thus indicates whether atmospheric motions act to decrease (for divergence) or increase (for convergence) the vertical integral of ozone.
In the ECMWF Integrated Forecasting System (IFS), there is a simplified representation of ozone chemistry (including a representation of the chemistry which has caused the ozone hole). Ozone is also transported around in the atmosphere through the motion of air.See further documentation.
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This parameter is the horizontal rate of flow of cloud liquid water, in the eastward direction, per metre across the flow, for a column of air extending from the surface of the Earth to the top of the atmosphere. Positive values indicate a flux from west to east.
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Note that 'cloud frozen water' is the same as 'cloud ice water'.","unit_id":66,"encoding_ids":["grib1"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":162091,"name":"Total column vertically-integrated northward cloud frozen water flux ","shortname":"viiwn","description":"","unit_id":66,"encoding_ids":["grib1"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":162092,"name":"Total column vertically-integrated mass tendency","shortname":"vimat","description":"This parameter is the rate of change of the mass of a column of air extending from the Earth's surface to the top of the atmosphere. An increasing mass of the column indicates rising surface pressure. In contrast, a decrease indicates a falling surface pressure trend.
The mass of the column is calculated by dividing pressure at the Earth's surface by the gravitational acceleration, g (=9.80665 m s-2).
This parameter can be used to study the atmospheric mass and energy budgets. See further information.","unit_id":33,"encoding_ids":["grib1"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":162093,"name":"Total column vertically-integrated water enthalpy","shortname":"viwe","description":null,"unit_id":6,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":162100,"name":"Time-integrated temperature tendency due to short-wave radiation","shortname":"srta","description":"","unit_id":2,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":162101,"name":"Time-integrated temperature tendency due to long-wave radiation","shortname":"trta","description":"","unit_id":2,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":162102,"name":"Time-integrated temperature tendency due to short wave radiation, clear 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The horizontal wind field can be separated into divergent flow (i.e., flow that is purely divergent, with no swirl or rotation) and rotational flow (i.e., flow that is purely rotational and has no divergence).
The rotational (non-divergent) flow follows lines of constant stream function value (streamlines) and the speed of flow is proportional to the stream function gradient.
So streamlines show patterns of horizontal, rotational, air flow and the paths that particles would follow if the flow did not change with time.","unit_id":1,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":171002,"name":"Velocity potential anomaly","shortname":"vpota","description":"An anomaly is a difference from a defined long-term average. Positive/negative values of this parameter indicate that the velocity potential is higher/lower than the long-term average. The long-term average is typically derived from several decades of model data and will vary with location and time of year (see further information).
The horizontal wind field can be separated into divergent flow (i.e., flow that is purely divergent, with no swirl or rotation) and rotational flow (i.e., flow that is purely rotational and has no divergence).
This parameter is the scalar quantity whose gradient is the velocity vector of the irrotational flow. It can be used to show areas where the air is diverging (spreading out) or converging, which, depending on the vertical level, relate to ascending or descending air.","unit_id":1,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":171003,"name":"Potential temperature anomaly","shortname":"pta","description":"","unit_id":2,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":171004,"name":"Equivalent potential temperature anomaly","shortname":"epta","description":"","unit_id":2,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":171005,"name":"Saturated equivalent potential temperature anomaly","shortname":"septa","description":"","unit_id":2,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":171006,"name":"100 metre U wind component anomaly","shortname":"100ua","description":"","unit_id":5,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":171007,"name":"100 metre V wind component anomaly","shortname":"100va","description":"","unit_id":5,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":171008,"name":"100 metre wind speed anomaly","shortname":"100sia","description":null,"unit_id":5,"encoding_ids":["grib1"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":171011,"name":"U component of divergent wind anomaly","shortname":"udwa","description":"","unit_id":5,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":171012,"name":"V component of divergent wind anomaly","shortname":"vdwa","description":"","unit_id":5,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":171013,"name":"U component of rotational wind anomaly","shortname":"urwa","description":"","unit_id":5,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":171014,"name":"V component of rotational wind anomaly","shortname":"vrwa","description":"","unit_id":5,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":171021,"name":"Unbalanced component of temperature anomaly","shortname":"uctpa","description":"","unit_id":2,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":171022,"name":"Unbalanced component of logarithm of surface pressure anomaly","shortname":"uclna","description":"","unit_id":7,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":171023,"name":"Unbalanced component of divergence anomaly","shortname":"ucdva","description":"","unit_id":8,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":171024,"name":"Lake mix-layer temperature anomaly","shortname":"lmlta","description":"An anomaly is a difference from a defined long-term average. Positive/negative values of this parameter indicate that the mixed-layer temperature of inland water bodies (lakes, reservoirs and rivers) or coastal waters is higher/lower than the long-term average. The long-term average is typically derived from several decades of model data and will vary with location and time of year (see further information ).
The mixed-layer temperature is the temperature of the uppermost layer of a lake that is well mixed. The ECMWF Integrated Forecasting System represents inland water bodies and coastal waters with two layers in the vertical, the mixed layer above and the thermocline below, where temperature changes with depth. The upper boundary of the thermocline is located at the mixed layer bottom, and the lower boundary of the thermocline at the lake bottom.
Mixing can occur when the density of the surface (and near-surface) water is greater than that of the water below. Mixing can also occur through the action of wind on the surface of the lake.
ECMWF implemented a lake model in May 2015 to represent the water temperature and lake ice of all the world's major inland water bodies in the Integrated Forecasting System (IFS). The IFS differentiates between (i) ocean water, handled by the ocean model, and (ii) inland water (lakes, reservoirs and rivers) and coastal waters handled by the lake parametrisation. Lake depth and surface area (or fractional cover) are kept constant in time.","unit_id":2,"encoding_ids":["grib1"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":171025,"name":"Lake ice depth anomaly","shortname":"licda","description":"An anomaly is a difference from a defined long-term average. Positive/negative values of this parameter indicate that the ice thickness on inland water bodies (lakes, reservoirs and rivers) and coastal waters is higher/lower than the long-term average. The long-term average is typically derived from several decades of model data and will vary with location and time of year (see further information ).
The ECMWF Integrated Forecasting System represents the formation and melting of ice on inland water bodies. A single ice layer is represented. Lake ice depth is the thickness of that ice layer.
ECMWF implemented a lake model in May 2015 to represent the water temperature and lake ice of all the world's major inland water bodies in the Integrated Forecasting System (IFS). The IFS differentiates between (i) ocean water, handled by the ocean model, and (ii) inland water (lakes, reservoirs and rivers) and coastal waters handled by the lake parametrisation. Lake depth and surface area (or fractional cover) are kept constant in time.","unit_id":4,"encoding_ids":["grib1"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":171026,"name":"Lake cover anomaly","shortname":"cla","description":"","unit_id":3,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":171027,"name":"Low vegetation cover anomaly","shortname":"cvla","description":"","unit_id":3,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":171028,"name":"High vegetation cover anomaly","shortname":"cvha","description":"","unit_id":3,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":171029,"name":"Type of low vegetation anomaly","shortname":"tvla","description":"","unit_id":7,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":171030,"name":"Type of high vegetation anomaly","shortname":"tvha","description":"","unit_id":7,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":171031,"name":"Sea-ice cover anomaly","shortname":"sica","description":"An anomaly is a difference from a defined long-term average. Positive/negative values of this parameter indicate that the sea-ice cover is higher/lower than the long-term average. The long-term average is typically derived from several decades of model data and will vary with location and time of year (see further information ).
Sea-ice cover is the fraction of a grid box which is covered by sea-ice. Sea-ice can only occur in a grid box which is defined as ocean according to the land sea mask at the resolution being used. Sea-ice cover can also be known as sea-ice fraction or sea-ice concentration.
Sea-ice is frozen sea water which floats on the surface of the ocean. Sea-ice does not include ice which forms on land such as glaciers, icebergs and ice-sheets. It also excludes ice shelves which are anchored on land, but protrude out over the surface of the ocean. These phenomena are not modelled by the IFS.
Long-term monitoring of sea-ice cover is important for understanding climate change. Sea-ice cover also affects shipping routes through the polar regions.","unit_id":3,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":171032,"name":"Snow albedo anomaly","shortname":"asna","description":"","unit_id":3,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":171033,"name":"Snow density anomaly","shortname":"rsna","description":"An anomaly is a difference from a defined long-term average. Positive/negative values of this parameter indicate that the snow density is higher/lower than the long-term average. The long-term average is typically derived from several decades of model data and will vary with location and time of year (see further information ).
The ECMWF Integrated Forecast System represents snow as a single additional layer over the uppermost soil level. Snow density is assumed to be constant through the depth of the snow layer. Snow density changes with time due to the weight of snow and melt water in the snowpack.","unit_id":9,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":171034,"name":"Sea surface temperature anomaly","shortname":"ssta","description":"An anomaly is a difference from a defined long-term average. Positive/negative values of this parameter indicate that the temperature of sea water near the surface is higher/lower than the long-term average. The long-term average is typically derived from several decades of model data and will vary with location and time of year (see further information ).
Sea surface temperature (SST) is taken from various providers, who process the observational data in different ways. Each provider uses data from several different observational sources. For example, satellites measure SST in a layer a few microns thick in the uppermost mm of the ocean, drifting buoys measure SST at a depth of about 0.2-1.5m, whereas ships sample sea water down to about 10m, while the vessel is underway. Deeper measurements are not affected by changes that occur during a day, due to the rising and setting of the Sun (diurnal variations).
Sometimes SST is taken from a forecast made by coupling the NEMO ocean model to the ECMWF Integrated Forecasting System. In this case, the SST is the average temperature of the uppermost metre of the ocean and does exhibit diurnal variations.
See further SST documentation.","unit_id":2,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":171035,"name":"Ice surface temperature anomaly layer 1","shortname":"istal1","description":"","unit_id":2,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":171036,"name":"Ice surface temperature anomaly layer 2","shortname":"istal2","description":"","unit_id":2,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":171037,"name":"Ice surface temperature anomaly layer 3","shortname":"istal3","description":"","unit_id":2,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":171038,"name":"Ice surface temperature anomaly layer 4","shortname":"istal4","description":"","unit_id":2,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":171039,"name":"Volumetric soil water anomaly layer 1","shortname":"swval1","description":"An anomaly is a difference from a defined long-term average. Positive/negative values of this parameter indicate that the volumetric soil water is larger/smaller in layer 1 than the long-term average. The long-term average is typically derived from several decades of model data and will vary with location and time of year (see further information ).
Volumetric soil water is the volume of water in soil.
The ECMWF Integrated Forecasting System model has a four-layer representation of soil:
Layer 1: 0 - 7cm
Layer 2: 7 - 28cm
Layer 3: 28 - 100cm
Layer 4: 100 - 289cm
The volumetric soil water is associated with the soil texture (or classification), soil depth, and the underlying groundwater level.","unit_id":10,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":171040,"name":"Volumetric soil water anomaly layer 2","shortname":"swval2","description":"An anomaly is a difference from a defined long-term average. Positive/negative values of this parameter indicate that the volumetric soil water is larger/smaller in layer 2 than the long-term average. The long-term average is typically derived from several decades of model data and will vary with location and time of year (see further information ).
Volumetric soil water is the volume of water in soil.
The ECMWF Integrated Forecasting System model has a four-layer representation of soil:
Layer 1: 0 - 7cm
Layer 2: 7 - 28cm
Layer 3: 28 - 100cm
Layer 4: 100 - 289cm
The volumetric soil water is associated with the soil texture (or classification), soil depth, and the underlying groundwater level.","unit_id":10,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":171041,"name":"Volumetric soil water anomaly layer 3","shortname":"swval3","description":"An anomaly is a difference from a defined long-term average. Positive/negative values of this parameter indicate that the volumetric soil water is larger/smaller in layer 3 than the long-term average. The long-term average is typically derived from several decades of model data and will vary with location and time of year (see further information ).
Volumetric soil water is the volume of water in soil.
The ECMWF Integrated Forecasting System model has a four-layer representation of soil:
Layer 1: 0 - 7cm
Layer 2: 7 - 28cm
Layer 3: 28 - 100cm
Layer 4: 100 - 289cm
The volumetric soil water is associated with the soil texture (or classification), soil depth, and the underlying groundwater level.","unit_id":10,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":171042,"name":"Volumetric soil water anomaly layer 4","shortname":"swval4","description":"An anomaly is a difference from a defined long-term average. Positive/negative values of this parameter indicate that the volumetric soil water is larger/smaller in layer 4 than the long-term average. The long-term average is typically derived from several decades of model data and will vary with location and time of year (see further information ).
Volumetric soil water is the volume of water in soil.
The ECMWF Integrated Forecasting System model has a four-layer representation of soil:
Layer 1: 0 - 7cm
Layer 2: 7 - 28cm
Layer 3: 28 - 100cm
Layer 4: 100 - 289cm
The volumetric soil water is associated with the soil texture (or classification), soil depth, and the underlying groundwater level.","unit_id":10,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":171043,"name":"Soil type anomaly","shortname":"slta","description":"","unit_id":7,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":171044,"name":"Snow evaporation anomaly","shortname":"esa","description":"","unit_id":22,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":171045,"name":"Snowmelt anomaly","shortname":"smlta","description":"","unit_id":22,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":171046,"name":"Solar duration anomaly","shortname":"sdura","description":"","unit_id":12,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":171047,"name":"Direct solar radiation anomaly","shortname":"dsrpa","description":"","unit_id":6,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":171048,"name":"Magnitude of turbulent surface stress anomaly","shortname":"magssa","description":"","unit_id":14,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":171049,"name":"10 metre wind gust anomaly","shortname":"10fga","description":"An anomaly is a difference from a defined long-term average. Positive/negative values of this parameter indicate that the 10 metre wind gust is higher/lower than the long-term average. The long-term average is typically derived from several decades of model data and will vary with location and time of year (see further information).
The WMO defines a wind gust as the maximum of the wind averaged over 3 second intervals. This duration is shorter than a model time step, and so the ECMWF Integrated Forecasting System deduces the magnitude of a gust within each time step from the time-step-averaged surface stress, surface friction, wind shear and stability. Then, the maximum wind gust is selected from the gusts at each time step during a particular time period which depends on the data extracted.
This parameter is calculated at a height of ten metres above the surface of the Earth.
Care should be taken when comparing model parameters with observations, because observations are often local to a particular point in space and time, rather than representing averages over a model grid box and model time step.","unit_id":5,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":171050,"name":"Large-scale precipitation fraction anomaly","shortname":"lspfa","description":"","unit_id":12,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":171051,"name":"Maximum 2 metre temperature in the last 24 hours anomaly","shortname":"mx2t24a","description":"An anomaly is a difference from a defined long-term average. Positive/negative values of this parameter indicate that the maximum 2 metre temperature in the previous 24 hours is higher/lower than the long-term average. The long-term average is typically derived from several decades of model data and will vary with location and time of year (see further information).
2m temperature is calculated by interpolating between the lowest model level and the Earth's surface, taking account of the atmospheric conditions. See further information.","unit_id":2,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":171052,"name":"Minimum 2 metre temperature in the last 24 hours anomaly","shortname":"mn2t24a","description":"An anomaly is a difference from a defined long-term average. Positive/negative values of this parameter indicate that the minimum 2 metre temperature in the previous 24 hours is higher/lower than the long-term average. The long-term average is typically derived from several decades of model data and will vary with location and time of year (see further information).
2m temperature is calculated by interpolating between the lowest model level and the Earth's surface, taking account of the atmospheric conditions. See further information.","unit_id":2,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":171053,"name":"Montgomery potential anomaly","shortname":"monta","description":"","unit_id":15,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":171054,"name":"Pressure anomaly","shortname":"pa","description":"","unit_id":16,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":171055,"name":"Mean 2 metre temperature in the last 24 hours anomaly","shortname":"mean2t24a","description":"","unit_id":2,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":171056,"name":"Mean 2 metre dewpoint temperature in the last 24 hours anomaly","shortname":"mn2d24a","description":"","unit_id":2,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":171057,"name":"Downward UV radiation at the surface anomaly","shortname":"uvba","description":"","unit_id":6,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":171058,"name":"Photosynthetically active radiation at the surface anomaly","shortname":"para","description":"","unit_id":6,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":171059,"name":"Convective available potential energy anomaly","shortname":"capea","description":"","unit_id":17,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":171060,"name":"Potential vorticity anomaly","shortname":"pva","description":"","unit_id":18,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":171061,"name":"Total precipitation from observations anomaly","shortname":"tpoa","description":"","unit_id":35,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":171062,"name":"Observation count anomaly","shortname":"obcta","description":"","unit_id":7,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":171063,"name":"Start time for skin temperature difference anomaly","shortname":"stsktda","description":"","unit_id":12,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":171064,"name":"Finish time for skin temperature difference anomaly","shortname":"ftsktda","description":"","unit_id":12,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":171065,"name":"Skin temperature difference anomaly","shortname":"sktda","description":"","unit_id":2,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":171078,"name":"Total column liquid water anomaly","shortname":"tclwa","description":"An anomaly is a difference from a defined long-term average. Positive/negative values of this parameter indicate that the total amount of cloud liquid water (in a column extending from the surface of the Earth to the top of the atmosphere) is higher/lower than the long-term average. The long-term average is typically derived from several decades of model data and will vary with location and time of year (see further information).
This parameter represents the area averaged value for a grid box.
Clouds contain a continuum of different sized water droplets and ice particles. The ECMWF Integrated Forecasting System (IFS) cloud scheme simplifies this to represent a number of discrete cloud droplets/particles including: cloud water droplets, raindrops, ice crystals and snow (aggregated ice crystals). The processes of droplet formation, conversion and aggregation are also highly simplified in the IFS.","unit_id":22,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":171079,"name":"Total column ice water anomaly","shortname":"tciwa","description":"An anomaly is a difference from a defined long-term average. Positive/negative values of this parameter indicate that the total amount of cloud ice (in a column extending from the surface of the Earth to the top of the atmosphere) is higher/lower than the long-term average. The long-term average is typically derived from several decades of model data and will vary with location and time of year (see further information). This parameter does not include snow (i.e., precipitating ice).
This parameter represents the area averaged value for a grid box.
Clouds contain a continuum of different sized water droplets and ice particles. The ECMWF Integrated Forecasting System (IFS) cloud scheme simplifies this to represent a number of discrete cloud droplets/particles including: cloud water droplets, raindrops, ice crystals and snow (aggregated ice crystals). The processes of droplet formation, conversion and aggregation are also highly simplified in the IFS.","unit_id":22,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":171121,"name":"Maximum temperature at 2 metres in the last 6 hours anomaly","shortname":"mx2t6a","description":"An anomaly is a difference from a defined long-term average. Positive/negative values of this parameter indicate that the maximum 2 metre temperature in the previous 6 hours is higher/lower than the long-term average. The long-term average is typically derived from several decades of model data and will vary with location and time of year (see further information).
2m temperature is calculated by interpolating between the lowest model level and the Earth's surface, taking account of the atmospheric conditions. See further information.","unit_id":2,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":171122,"name":"Minimum temperature at 2 metres in the last 6 hours anomaly","shortname":"mn2t6a","description":"An anomaly is a difference from a defined long-term average. Positive/negative values of this parameter indicate that the minimum 2 metre temperature in the previous 6 hours is higher/lower than the long-term average. The long-term average is typically derived from several decades of model data and will vary with location and time of year (see further information ).
2m temperature is calculated by interpolating between the lowest model level and the Earth's surface, taking account of the atmospheric conditions. See further information.","unit_id":2,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":171125,"name":"Vertically integrated total energy anomaly","shortname":"vitea","description":"","unit_id":6,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":171126,"name":"Generic parameter for sensitive area prediction","shortname":"~","description":null,"unit_id":25,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":171127,"name":"Atmospheric tide anomaly","shortname":"ata","description":"","unit_id":7,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":171128,"name":"Budget values anomaly","shortname":"bva","description":"","unit_id":7,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":171129,"name":"Geopotential anomaly","shortname":"za","description":null,"unit_id":15,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":171130,"name":"Temperature anomaly","shortname":"ta","description":"An anomaly is a difference from a defined long-term average. Positive/negative values of this parameter indicate that temperature is higher/lower than the long-term average. The long-term average is typically derived from several decades of model data and will vary with location and time of year (see further information).
This parameter is available on multiple levels through the atmosphere.","unit_id":2,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":171131,"name":"U component of wind anomaly","shortname":"ua","description":"An anomaly is a difference from a defined long-term average. A positive anomaly indicates that the wind is more eastward (or less westward) than average. A negative anomaly indicates that the wind is more westward (or less eastward) than average. The long-term average is typically derived from several decades of model data and will vary with location and time of year (see further information).
The U component of wind is the eastward component of the wind. It is the horizontal speed of air moving towards the east, in metres per second. A negative U component of wind thus indicates air movement towards the west.","unit_id":5,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":171132,"name":"V component of wind anomaly","shortname":"va","description":"An anomaly is a difference from a defined long-term average. A positive anomaly indicates that the wind is more northward (or less southward) than average. A negative anomaly indicates that the wind is more southward (or less northward) than average. The long-term average is typically derived from several decades of model data and will vary with location and time of year (see further information).
The V component of wind is the northward component of the wind. It is the horizontal speed of air moving towards the north, in metres per second. A negative V component of wind thus indicates air movement towards the south.","unit_id":5,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":171133,"name":"Specific humidity anomaly","shortname":"qa","description":"An anomaly is a difference from a defined long-term average. Positive/negative values of this parameter indicate that the specific humidity is higher/lower than the long-term average. The long-term average is typically derived from several decades of model data and will vary with location and time of year (see further information ).
Specific humidity is the mass of water vapour per kilogram of moist air. The total mass of moist air is the sum of the dry air, water vapour, cloud liquid, cloud ice, rain and falling snow.","unit_id":21,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":171134,"name":"Surface pressure anomaly","shortname":"spa","description":"","unit_id":16,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":171135,"name":"Vertical velocity (pressure) anomaly","shortname":"wa","description":"","unit_id":26,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":171136,"name":"Total column water anomaly","shortname":"tcwa","description":"","unit_id":22,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":171137,"name":"Total column water vapour anomaly","shortname":"tcwva","description":"An anomaly is a difference from a defined long-term average. Positive/negative values of this parameter indicate that the total water vapour (in a column extending from the surface of the Earth to the top of the atmosphere) is higher/lower than the long-term average. The long-term average is typically derived from several decades of model data and will vary with location and time of year (see further information).
This parameter represents the area averaged value for a grid box.","unit_id":22,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":171138,"name":"Relative vorticity anomaly","shortname":"voa","description":"An anomaly is a difference from a defined long-term average. Positive/negative values of this parameter indicate that the relative vorticity is higher/lower than the long-term average. The long-term average is typically derived from several decades of model data and will vary with location and time of year (see further information).
Relative vorticity is a measure of the rotation of air in the horizontal, around a vertical axis, relative to a fixed point on the surface of the Earth.
On the scale of weather systems, low pressure systems (weather features that can include rain) are associated with anticlockwise rotation (in the northern hemisphere), and high pressure systems (weather features that bring light or still winds) are associated with clockwise rotation.
Adding the effect of rotation of the Earth, the Coriolis parameter, to the relative vorticity produces the absolute vorticity.","unit_id":8,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":171139,"name":"Soil temperature anomaly level 1","shortname":"stal1","description":"An anomaly is a difference from a defined long-term average. Positive/negative values of this parameter indicate that the soil temperature at level 1 (the middle of layer 1) is higher/lower than the long-term average. The long-term average is typically derived from several decades of model data and will vary with location and time of year (see further information ).
The ECMWF Integrated Forecasting System model has a four-layer representation of soil:
Layer 1: 0 - 7cm
Layer 2: 7 - 28cm
Layer 3: 28 - 100cm
Layer 4: 100 - 289cm
Soil temperature is set at the middle of each layer, and heat transfer is calculated at the interfaces between them. It is assumed that there is no heat transfer out of the bottom of the lowest layer.
This parameter has units of kelvin (K). Temperature measured in kelvin can be converted to degrees Celsius (°C) by subtracting 273.15.
See further information.","unit_id":2,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":171140,"name":"Soil wetness anomaly level 1","shortname":"swal1","description":"","unit_id":22,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":171141,"name":"Snow depth anomaly","shortname":"sda","description":"An anomaly is a difference from a defined long-term average. Positive/negative values of this parameter indicate that the snow depth is higher/lower than the long-term average. The long-term average is typically derived from several decades of model data and will vary with location and time of year (see further information ).
The ECMWF Integrated Forecast System represents snow as a single additional layer over the uppermost soil level. The snow may cover all or part of the grid box. Snow depth is the depth the water would have if the snow (from the snow-covered area of a grid box ) melted and was spread evenly over the whole grid box. Therefore, its units are metres of water equivalent.","unit_id":27,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":171142,"name":"Stratiform precipitation (Large-scale precipitation) anomaly","shortname":"lspa","description":"","unit_id":4,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":171143,"name":"Convective precipitation anomaly","shortname":"cpa","description":"","unit_id":4,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":171144,"name":"Snowfall (convective + stratiform) anomaly","shortname":"sfa","description":"","unit_id":27,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":171145,"name":"Boundary layer dissipation anomaly","shortname":"blda","description":"","unit_id":6,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":171146,"name":"Surface sensible heat flux anomaly","shortname":"sshfa","description":"","unit_id":6,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":171147,"name":"Surface latent heat flux anomaly","shortname":"slhfa","description":"","unit_id":6,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":171148,"name":"Charnock anomaly","shortname":"chnka","description":"","unit_id":7,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":171149,"name":"Surface net radiation anomaly","shortname":"snra","description":"","unit_id":6,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":171150,"name":"Top net radiation anomaly","shortname":"tnra","description":"","unit_id":7,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":171151,"name":"Mean sea level pressure anomaly","shortname":"msla","description":"An anomaly is a difference from a defined long-term average. Positive/negative values of this parameter indicate that the mean sea level pressure is higher/lower than the long-term average. The long-term average is typically derived from several decades of model data and will vary with location and time of year (see further information).
The mean sea level pressure is the pressure (force per unit area) of the atmosphere adjusted to the height of mean sea level. It is a measure of the weight that all the air in a column vertically above the area of Earth's surface would have at that point, if the point were located at the mean sea level. It is calculated over all surfaces - land, sea and in-land water.
Maps of mean sea level pressure are used to identify the locations of low and high pressure systems, often referred to as cyclones and anticyclones. Contours of mean sea level pressure also indicate the strength of the wind. Tightly packed contours show stronger winds.
The units of this parameter are pascals (Pa). Mean sea level pressure is often measured in hPa and sometimes is presented in the old units of millibars, mb (1 hPa = 1 mb = 100 Pa).","unit_id":16,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":171152,"name":"Logarithm of surface pressure anomaly","shortname":"lspa","description":"","unit_id":7,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":171153,"name":"Short-wave heating rate anomaly","shortname":"swhra","description":"","unit_id":2,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":171154,"name":"Long-wave heating rate anomaly","shortname":"lwhra","description":"","unit_id":2,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":171155,"name":"Relative divergence anomaly","shortname":"da","description":"An anomaly is a difference from a defined long-term average. Positive/negative values of this parameter indicate that the relative divergence is higher/lower than the long-term average. The long-term average is typically derived from several decades of model data and will vary with location and time of year (see further information).
The relative divergence, also called simply the divergence, is the horizontal divergence of velocity. It is the rate at which air is spreading out horizontally from a point, per square metre. This parameter is positive for air that is spreading out, or diverging, and negative for the opposite, for air that is concentrating, or converging (convergence).","unit_id":8,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":171156,"name":"Height anomaly","shortname":"gha","description":"An anomaly is a difference from a defined long-term average. Positive/negative values of this parameter indicate that geopotential height is higher/lower than the long-term average. The long-term average is typically derived from several decades of model data and will vary with location and time of year (see further information).
Geopotential height is a measure of the height of a point in the atmosphere in relation to its potential energy. It is calculated by dividing the geopotential by the Earth's mean gravitational acceleration, g (=9.80665 m s-2). The geopotential is the gravitational potential energy of a unit mass, at a particular location, relative to mean sea level. Geopotential is also the amount of work that would have to be done, against the force of gravity, to lift a unit mass to that location from mean sea level.
Geopotential height plays an important role in synoptic meteorology (analysis of weather patterns). Charts of geopotential height plotted at constant pressure levels (e.g., 300, 500 or 850 hPa) can be used to identify weather systems such as cyclones, anticyclones, troughs and ridges.
The units of this parameter are geopotential metres. A geopotential metre is 2% shorter than a dynamic metre (also called a geodynamic metre).","unit_id":4,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":171157,"name":"Relative humidity anomaly","shortname":"ra","description":"","unit_id":29,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":171158,"name":"Tendency of surface pressure anomaly","shortname":"tspa","description":"","unit_id":26,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":171159,"name":"Boundary layer height anomaly","shortname":"blha","description":"","unit_id":4,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":171160,"name":"Standard deviation of orography anomaly","shortname":"sdora","description":"","unit_id":4,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":171161,"name":"Anisotropy of sub-gridscale orography anomaly","shortname":"isora","description":"","unit_id":7,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":171162,"name":"Angle of sub-gridscale orography anomaly","shortname":"anora","description":"","unit_id":30,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":171163,"name":"Slope of sub-gridscale orography anomaly","shortname":"slora","description":"","unit_id":7,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":171164,"name":"Total cloud cover anomaly","shortname":"tcca","description":"An anomaly is a difference from a defined long-term average. Positive/negative values of this parameter indicate that total cloud cover is larger/smaller than the long-term average. The long-term average is typically derived from several decades of model data and will vary with location and time of year (see further information).
Total cloud cover is the proportion of a model grid box covered by cloud. Total cloud cover is a single level field calculated from the cloud occurring at different model levels through the atmosphere. Assumptions are made about the degree of overlap/randomness between the horizontal positioning of clouds at different heights.","unit_id":3,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":171165,"name":"10 metre U wind component anomaly","shortname":"10ua","description":"An anomaly is a difference from a defined long-term average. A positive anomaly indicates that the wind is more eastward (or less westward) than average. A negative anomaly indicates that the wind is more westward (or less eastward) than average. The long-term average is typically derived from several decades of model data and will vary with location and time of year (see further information).
The 10 metre U wind component is the eastward component of the 10 m wind. It is the horizontal speed of air moving towards the east, at a height of ten metres above the surface of the Earth, in metres per second.
Care should be taken when comparing model parameters with observations, because observations are often local to a particular point in space and time, rather than representing averages over a model grid box and model time step.","unit_id":5,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":171166,"name":"10 metre V wind component anomaly","shortname":"10va","description":"An anomaly is a difference from a defined long-term average. A positive anomaly indicates that the wind is more northward (or less southward) than average. A negative anomaly indicates that the wind is more southward (or less northward) than average. The long-term average is typically derived from several decades of model data and will vary with location and time of year (see further information).
The 10 metre V wind component is the northward component of the 10 m wind. It is the horizontal speed of air moving towards the north, at a height of ten metres above the surface of the Earth, in metres per second.
Care should be taken when comparing model parameters with observations, because observations are often local to a particular point in space and time, rather than representing averages over a model grid box and model time step.","unit_id":5,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":171167,"name":"2 metre temperature anomaly","shortname":"2ta","description":"An anomaly is a difference from a defined long-term average. Positive/negative values of this parameter indicate that the 2 metre temperature is higher/lower than the long-term average. The long-term average is typically derived from several decades of model data and will vary with location and time of year (see further information).
2m temperature is calculated by interpolating between the lowest model level and the Earth's surface, taking account of the atmospheric conditions. See further information.","unit_id":2,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":171168,"name":"2 metre dewpoint temperature anomaly","shortname":"2da","description":"An anomaly is a difference from a defined long-term average. Positive/negative values of this parameter indicate that the 2 metre dew point temperature is higher/lower than the long-term average. The long-term average is typically derived from several decades of model data and will vary with location and time of year (see further information).
Dew point temperature is the temperature to which the air would have to be cooled for saturation to occur. It is a measure of the humidity of the air. Combined with temperature and pressure, it can be used to calculate the relative humidity.
2m dew point temperature is calculated by interpolating between the lowest model level and the Earth's surface, taking account of the atmospheric conditions.See further information.","unit_id":2,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":171169,"name":"Surface solar radiation downwards anomaly","shortname":"ssrda","description":"An anomaly is a difference from a defined long-term average. Positive/negative values of this parameter indicate that the surface solar radiation downwards is higher/lower than the long-term average. The long-term average is typically derived from several decades of model data and will vary with location and time of year (see further information).
The surface solar radiation downwards is the amount of solar radiation (also known as shortwave radiation) reaching the surface of the Earth (both direct and diffuse). It is the amount of radiation passing through a horizontal plane, not a plane perpendicular to the direction of the Sun. It is accumulated over a particular time period which depends on the data extracted.
The ECMWF convention for vertical fluxes is positive downwards.","unit_id":6,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":171170,"name":"Soil temperature anomaly level 2","shortname":"stal2","description":"An anomaly is a difference from a defined long-term average. Positive/negative values of this parameter indicate that the soil temperature at level 2 (the middle of layer 2) is higher/lower than the long-term average. The long-term average is typically derived from several decades of model data and will vary with location and time of year (see further information ).
The ECMWF Integrated Forecasting System model has a four-layer representation of soil:
Layer 1: 0 - 7cm
Layer 2: 7 - 28cm
Layer 3: 28 - 100cm
Layer 4: 100 - 289cm
Soil temperature is set at the middle of each layer, and heat transfer is calculated at the interfaces between them. It is assumed that there is no heat transfer out of the bottom of the lowest layer.
This parameter has units of kelvin (K). Temperature measured in kelvin can be converted to degrees Celsius (°C) by subtracting 273.15.
See further information.","unit_id":2,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":171171,"name":"Soil wetness anomaly level 2","shortname":"swal2","description":"","unit_id":22,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":171173,"name":"Surface roughness anomaly","shortname":"sra","description":"","unit_id":4,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":171174,"name":"Albedo anomaly","shortname":"ala","description":"","unit_id":3,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":171175,"name":"Surface thermal radiation downwards anomaly","shortname":"strda","description":"","unit_id":6,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":171176,"name":"Surface net solar radiation anomaly","shortname":"ssra","description":"","unit_id":6,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":171177,"name":"Surface net thermal radiation anomaly","shortname":"stra","description":"","unit_id":6,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":171178,"name":"Top net solar radiation anomaly","shortname":"tsra","description":"","unit_id":6,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":171179,"name":"Top net thermal radiation anomaly","shortname":"ttra","description":"","unit_id":6,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":171180,"name":"East-West surface stress anomaly","shortname":"eqssa","description":"","unit_id":14,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":171181,"name":"North-South surface stress anomaly","shortname":"nsssa","description":"","unit_id":14,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":171182,"name":"Evaporation anomaly","shortname":"ea","description":"","unit_id":22,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":171183,"name":"Soil temperature anomaly level 3","shortname":"stal3","description":"An anomaly is a difference from a defined long-term average. Positive/negative values of this parameter indicate that the soil temperature at level 3 (the middle of layer 3) is higher/lower than the long-term average. The long-term average is typically derived from several decades of model data and will vary with location and time of year (see further information ).
The ECMWF Integrated Forecasting System model has a four-layer representation of soil:
Layer 1: 0 - 7cm
Layer 2: 7 - 28cm
Layer 3: 28 - 100cm
Layer 4: 100 - 289cm
Soil temperature is set at the middle of each layer, and heat transfer is calculated at the interfaces between them. It is assumed that there is no heat transfer out of the bottom of the lowest layer.
This parameter has units of kelvin (K). Temperature measured in kelvin can be converted to degrees Celsius (°C) by subtracting 273.15.
See further information.","unit_id":2,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":171184,"name":"Soil wetness anomaly level 3","shortname":"swal3","description":"","unit_id":22,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":171185,"name":"Convective cloud cover anomaly","shortname":"ccca","description":"","unit_id":3,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":171186,"name":"Low cloud cover anomaly","shortname":"lcca","description":"An anomaly is a difference from a defined long-term average. Positive/negative values of this parameter indicate that low cloud cover is larger/smaller than the long-term average. The long-term average is typically derived from several decades of model data and will vary with location and time of year (see further information).
Low cloud cover is the proportion of a model grid box covered by cloud occurring in the lower levels of the troposphere. Low cloud is a single level field calculated from cloud occurring on model levels with a pressure greater than 0.8 times the surface pressure. So, if the surface pressure is 1000 hPa (hectopascal), low cloud would be calculated using levels with a pressure greater than 800 hPa (below approximately 2 km (assuming a 'standard atmosphere')).
The low cloud cover parameter is calculated from cloud cover for the appropriate model levels as described above. Assumptions are made about the degree of overlap/randomness between the horizontal positioning of clouds in different model levels.","unit_id":3,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":171187,"name":"Medium cloud cover anomaly","shortname":"mcca","description":"","unit_id":3,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":171188,"name":"High cloud cover anomaly","shortname":"hcca","description":"","unit_id":3,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":171189,"name":"Sunshine duration anomaly","shortname":"sunda","description":null,"unit_id":12,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":171190,"name":"East-West component of sub-gridscale orographic variance anomaly","shortname":"ewova","description":"","unit_id":31,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":171191,"name":"North-South component of sub-gridscale orographic variance anomaly","shortname":"nsova","description":"","unit_id":31,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":171192,"name":"North-West/South-East component of sub-gridscale orographic variance anomaly","shortname":"nwova","description":"","unit_id":31,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":171193,"name":"North-East/South-West component of sub-gridscale orographic variance anomaly","shortname":"neova","description":"","unit_id":31,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":171194,"name":"Brightness temperature anomaly","shortname":"btmpa","description":"","unit_id":2,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":171195,"name":"Longitudinal component of gravity wave stress anomaly","shortname":"lgwsa","description":"","unit_id":14,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":171196,"name":"Meridional component of gravity wave stress anomaly","shortname":"mgwsa","description":"","unit_id":14,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":171197,"name":"Gravity wave dissipation anomaly","shortname":"gwda","description":"","unit_id":6,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":171198,"name":"Skin reservoir content anomaly","shortname":"srca","description":"","unit_id":22,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":171199,"name":"Vegetation fraction anomaly","shortname":"vfa","description":"","unit_id":3,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":171200,"name":"Variance of sub-gridscale orography anomaly","shortname":"vsoa","description":"","unit_id":31,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":171201,"name":"Maximum temperature at 2 metres anomaly","shortname":"mx2ta","description":null,"unit_id":2,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":171202,"name":"Minimum temperature at 2 metres anomaly","shortname":"mn2ta","description":null,"unit_id":2,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":171203,"name":"Ozone mass mixing ratio anomaly","shortname":"o3a","description":"An anomaly is a difference from a defined long-term average. Positive/negative values of this parameter indicate that ozone mass mixing ratio is higher/lower than the long-term average. The long-term average is typically derived from several decades of model data and will vary with location and time of year (see further information).
Ozone mass mixing ratio is the mass of ozone per kilogram of air.
In the ECMWF Integrated Forecasting System (IFS), there is a simplified representation of ozone chemistry (including representation of the chemistry which has caused the ozone hole). Ozone is also transported around in the atmosphere through the motion of air. See further documentation.
Naturally occurring ozone in the stratosphere helps protect organisms at the surface of the Earth from the harmful effects of ultraviolet (UV) radiation from the Sun. Ozone near the surface, often produced because of pollution, is harmful to organisms.
Most of the IFS chemical species are archived as mass mixing ratios [kg kg-1]. This link explains how to convert to concentration in terms of mass per unit volume.","unit_id":21,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":171204,"name":"Precipitation analysis weights anomaly","shortname":"pawa","description":"","unit_id":7,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":171205,"name":"Runoff anomaly","shortname":"roa","description":"","unit_id":4,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":171206,"name":"Total column ozone anomaly","shortname":"tco3a","description":"An anomaly is a difference from a defined long-term average. Positive/negative values of this parameter indicate that total column ozone is higher/lower than the long-term average. The long-term average is typically derived from several decades of model data and will vary with location and time of year (see further information).
Total column ozone is the total amount of ozone in a column of air extending from the surface of the Earth to the top of the (model) atmosphere. This parameter can also be referred to as total ozone, or vertically integrated ozone. The values are dominated by ozone within the stratosphere.
In the ECMWF Integrated Forecasting System (IFS), there is a simplified representation of ozone chemistry (including representation of the chemistry which has caused the ozone hole). Ozone is also transported around in the atmosphere through the motion of air. See further documentation.
Naturally occurring ozone in the stratosphere helps protect organisms at the surface of the Earth from the harmful effects of ultraviolet (UV) radiation from the Sun. Ozone near the surface, often produced because of pollution, is harmful to organisms.
In the IFS, the units for total ozone are kilograms per square metre, but before 12/06/2001 dobson units were used. Dobson units (DU) are still used extensively for total column ozone. 1 DU = 2.1415E-5 kg m-2.","unit_id":22,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":171207,"name":"10 metre wind speed anomaly","shortname":"10sia","description":"An anomaly is a difference from a defined long-term average. Positive/negative values of this parameter indicate that the 10 metre wind speed is higher/lower than the long-term average. The long-term average is typically derived from several decades of model data and will vary with location and time of year (see further information).
The 10 metre wind speed is the horizontal speed of the wind, or movement of air, at a height of ten metres above the surface of the Earth.
Care should be taken when comparing model parameters with observations, because observations are often local to a particular point in space and time, rather than representing averages over a model grid box and model time step.","unit_id":5,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":171208,"name":"Top net solar radiation clear sky anomaly","shortname":"tsrca","description":"","unit_id":6,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":171209,"name":"Top net thermal radiation clear sky anomaly","shortname":"ttrca","description":"","unit_id":6,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":171210,"name":"Surface net solar radiation clear sky anomaly","shortname":"ssrca","description":"","unit_id":6,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":171211,"name":"Surface net thermal radiation, clear sky anomaly","shortname":"strca","description":"","unit_id":6,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":171212,"name":"Solar insolation anomaly","shortname":"sia","description":"","unit_id":6,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":171214,"name":"Diabatic heating by radiation anomaly","shortname":"dhra","description":"","unit_id":2,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":171215,"name":"Diabatic heating by vertical diffusion anomaly","shortname":"dhvda","description":"","unit_id":2,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":171216,"name":"Diabatic heating by cumulus convection anomaly","shortname":"dhcca","description":"","unit_id":2,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":171217,"name":"Diabatic heating by large-scale condensation anomaly","shortname":"dhlca","description":"","unit_id":2,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":171218,"name":"Vertical diffusion of zonal wind anomaly","shortname":"vdzwa","description":"","unit_id":5,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":171219,"name":"Vertical diffusion of meridional wind anomaly","shortname":"vdmwa","description":"","unit_id":5,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":171220,"name":"East-West gravity wave drag tendency anomaly","shortname":"ewgda","description":"","unit_id":5,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":171221,"name":"North-South gravity wave drag tendency anomaly","shortname":"nsgda","description":"","unit_id":5,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":171222,"name":"Convective tendency of zonal wind anomaly","shortname":"ctzwa","description":"","unit_id":5,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":171223,"name":"Convective tendency of meridional wind anomaly","shortname":"ctmwa","description":"","unit_id":5,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":171224,"name":"Vertical diffusion of humidity anomaly","shortname":"vdha","description":"","unit_id":21,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":171225,"name":"Humidity tendency by cumulus convection anomaly","shortname":"htcca","description":"","unit_id":21,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":171226,"name":"Humidity tendency by large-scale condensation anomaly","shortname":"htlca","description":"","unit_id":21,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":171227,"name":"Change from removal of negative humidity anomaly","shortname":"crnha","description":"","unit_id":21,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":171228,"name":"Total precipitation anomaly","shortname":"tpa","description":"An anomaly is a difference from a defined long-term average. Positive/negative values of this parameter indicate that the total precipitation is higher/lower than the long-term average. The long-term average is typically derived from several decades of model data and will vary with location and time of year (see further information).
In the ECMWF Integrated Forecasting System (IFS), total precipitation is rain and snow that falls to the Earth's surface. It is the sum of large-scale precipitation and convective precipitation. Large-scale precipitation is generated by the cloud scheme in the ECMWF Integrated Forecasting System (IFS). The cloud scheme represents the formation and dissipation of clouds and large-scale precipitation due to changes in atmospheric quantities (such as pressure, temperature and moisture) predicted directly by the IFS at spatial scales of a grid box or larger. Convective precipitation is generated by the convection scheme in the IFS. The convection scheme represents convection at spatial scales smaller than the grid box. See further information. Precipitation parameters do not include fog, dew or the precipitation that evaporates in the atmosphere before it lands at the surface of the Earth.
This parameter is calculated from the total amount of water accumulated over a particular time period which depends on the data extracted.The units of precipitation are depth in metres. It is the depth the water would have if it were spread evenly over the grid box.
Care should be taken when comparing model parameters with observations, because observations are often local to a particular point in space and time, rather than representing averages over a model grid box and model time step.","unit_id":4,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":171229,"name":"Instantaneous X surface stress anomaly","shortname":"iewsa","description":"An anomaly is a difference from a defined long-term average. A positive anomaly indicates that the surface stress is more eastward (or less westward) than average. A negative anomaly indicates that the surface stress is more westward (or less eastward) than the average. The long-term average is typically derived from several decades of model data and will vary with location and time of year (see further information).
Air flowing over a surface exerts a stress that transfers momentum to the surface and slows the wind. The instantaneous X surface stress is the stress on the Earth's surface at the specified time in the eastward direction due to both the turbulent interactions between the atmosphere and the surface, and to turbulent orographic form drag.
The turbulent interactions between the atmosphere and the surface are due to the roughness of the surface.
The turbulent orographic form drag is the stress due to the valleys, hills and mountains on horizontal scales below 5km being derived from land surface data at about 1 km resolution. See further information.","unit_id":32,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":171230,"name":"Instantaneous Y surface stress anomaly","shortname":"inssa","description":"An anomaly is a difference from a defined long-term average. A positive anomaly indicates that the surface stress is more northward (or less southward) than average. A negative anomaly indicates that the surface stress is more southward (or less northward) than the average. The long-term average is typically derived from several decades of model data and will vary with location and time of year (see further information).
Air flowing over a surface exerts a stress that transfers momentum to the surface and slows the wind. The instantaneous Y surface stress is the stress on the Earth's surface at the specified time in the northward direction due to both the turbulent interactions between the atmosphere and the surface, and to turbulent orographic form drag.
The turbulent interactions between the atmosphere and the surface are due to the roughness of the surface.
The turbulent orographic form drag is the stress due to the valleys, hills and mountains on horizontal scales below 5km being derived from land surface data at about 1 km resolution. See further information.","unit_id":32,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":171231,"name":"Instantaneous surface heat flux anomaly","shortname":"ishfa","description":"","unit_id":6,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":171232,"name":"Instantaneous moisture flux anomaly","shortname":"iea","description":"","unit_id":36,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":171233,"name":"Apparent surface humidity anomaly","shortname":"asqa","description":"","unit_id":21,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":171234,"name":"Logarithm of surface roughness length for heat anomaly","shortname":"lsrha","description":"","unit_id":7,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":171235,"name":"Skin temperature anomaly","shortname":"skta","description":"","unit_id":2,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":171236,"name":"Soil temperature level 4 anomaly","shortname":"stal4","description":"An anomaly is a difference from a defined long-term average. Positive/negative values of this parameter indicate that the soil temperature at level 4 (the middle of layer 4) is higher/lower than the long-term average. The long-term average is typically derived from several decades of model data and will vary with location and time of year (see further information ).
The ECMWF Integrated Forecasting System model has a four-layer representation of soil:
Layer 1: 0 - 7cm
Layer 2: 7 - 28cm
Layer 3: 28 - 100cm
Layer 4: 100 - 289cm
Soil temperature is set at the middle of each layer, and heat transfer is calculated at the interfaces between them. It is assumed that there is no heat transfer out of the bottom of the lowest layer.
This parameter has units of kelvin (K). Temperature measured in kelvin can be converted to degrees Celsius (°C) by subtracting 273.15.
See further information.","unit_id":2,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":171237,"name":"Soil wetness level 4 anomaly","shortname":"swal4","description":"","unit_id":4,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":171238,"name":"Temperature of snow layer anomaly","shortname":"tsna","description":"","unit_id":2,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":171239,"name":"Convective snowfall anomaly","shortname":"csfa","description":"","unit_id":27,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":171240,"name":"Large scale snowfall anomaly","shortname":"lsfa","description":"","unit_id":27,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":171241,"name":"Accumulated cloud fraction tendency anomaly","shortname":"acfa","description":"","unit_id":34,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":171242,"name":"Accumulated liquid water tendency anomaly","shortname":"alwa","description":"","unit_id":34,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":171243,"name":"Forecast albedo anomaly","shortname":"fala","description":"An anomaly is a difference from a defined long-term average. Positive/negative values of this parameter indicate that the forecast albedo is higher/lower than the long-term average. The long-term average is typically derived from several decades of model data and will vary with location and time of year (see further information).
The forecast albedo is a measure of the reflectivity of the Earth's surface. It is the fraction of solar (shortwave) radiation reflected by Earth's surface, across the solar spectrum, for both direct and diffuse radiation. Typically, snow and ice have high reflectivity with albedo values of 0.8 and above, land has intermediate values between about 0.1 and 0.4 and the ocean has low values of 0.1 or less. See further documentation.
In the ECMWF Integrated Forecasting System (IFS), the model only modifies albedo values over water, ice and snow, elsewhere a background climatological albedo is used.","unit_id":3,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":171244,"name":"Forecast surface roughness anomaly","shortname":"fsra","description":"","unit_id":4,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":171245,"name":"Forecast logarithm of surface roughness for heat anomaly","shortname":"flsra","description":"","unit_id":7,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":171246,"name":"Cloud liquid water content anomaly","shortname":"clwca","description":"","unit_id":21,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":171247,"name":"Cloud ice water content anomaly","shortname":"ciwca","description":"","unit_id":21,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":171248,"name":"Cloud cover anomaly","shortname":"cca","description":"","unit_id":3,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":171249,"name":"Accumulated ice water tendency anomaly","shortname":"aiwa","description":"","unit_id":34,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":171250,"name":"Ice age anomaly","shortname":"iaa","description":"","unit_id":3,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":171251,"name":"Adiabatic tendency of temperature anomaly","shortname":"attea","description":"","unit_id":2,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":171252,"name":"Adiabatic tendency of humidity anomaly","shortname":"athea","description":"","unit_id":21,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":171253,"name":"Adiabatic tendency of zonal wind anomaly","shortname":"atzea","description":"","unit_id":5,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":171254,"name":"Adiabatic tendency of meridional wind anomaly","shortname":"atmwa","description":"","unit_id":5,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":171255,"name":"Indicates a missing value","shortname":"~","description":null,"unit_id":7,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":172008,"name":"Time-mean surface runoff rate","shortname":"msror","description":"Mean rate of accumulation. \nThe monthly mean is computed from the rate of accumulation of the field","unit_id":5,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":172009,"name":"Time-mean sub-surface runoff rate","shortname":"mssror","description":"Deep soil drainage. Mean rate of accumulation. \nThe monthly mean is computed from the rate of accumulation of the field","unit_id":5,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":172044,"name":"Time-mean snow evaporation rate","shortname":"esrate","description":null,"unit_id":78,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":172045,"name":"Time-mean snowmelt rate","shortname":"~","description":null,"unit_id":78,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":172050,"name":"Mean large-scale precipitation fraction","shortname":"mlspfr","description":"
This parameter is only available in GRIB1.
","unit_id":7,"encoding_ids":["grib1"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":172142,"name":"Time-mean large-scale precipitation rate","shortname":"mlsprt","description":null,"unit_id":5,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":172143,"name":"Time-mean convective precipitation rate","shortname":"cprate","description":null,"unit_id":5,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":172144,"name":"Time-mean total snowfall rate","shortname":"mtsfr","description":"This parameter is the mean rate of snowfall. It is accumulated snowfall divided by the length of the accumulation period, which depends on the data extracted.
This parameter is the sum of large-scale snowfall and convective snowfall. Large-scale snowfall is generated by the cloud scheme in the ECMWF Integrated Forecast System (IFS). The cloud scheme represents the formation and dissipation of clouds and large-scale snowfall due to changes in atmospheric quantities (such as pressure, temperature and moisture) predicted directly by the IFS at spatial scales of a grid box or larger. Convective snowfall is generated by the convection scheme in the IFS. The convection scheme represents convection at spatial scales smaller than the grid box. See further information.
The units are depth of water equivalent in metres which falls per second (i.e., the depth the melted snow would have if it were spread evenly over the grid box ).
Care should be taken when comparing model parameters with observations, because observations are often local to a particular point in space and time, rather than representing averages over a model grid box and model time step.","unit_id":78,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":172145,"name":"Boundary layer dissipation","shortname":"bldrate","description":"
Please use 235036 for the GRIB2 encoding of this parameter.
","unit_id":76,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":172176,"name":"Time-mean surface net short-wave (solar) radiation flux","shortname":"msnsrf","description":"
Please use 235037 for the GRIB2 encoding of this parameter.
","unit_id":76,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":172177,"name":"Time-mean surface net long-wave (thermal) radiation flux","shortname":"msntrf","description":"
Please use 235038 for the GRIB2 encoding of this parameter.
","unit_id":76,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":172178,"name":"Time-mean top net short-wave (solar) radiation flux","shortname":"mtnsrf","description":"
Please use 235039 for the GRIB2 encoding of this parameter.
","unit_id":76,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":172179,"name":"Time-mean top net long-wave (thermal) radiation flux","shortname":"mtntrf","description":"
Please use 235040 for the GRIB2 encoding of this parameter.
This parameter is the accumulated sunshine duration divided by the length of the accumulation period, which depends on the data extracted, giving the mean sunshine duration rate.
The sunshine duration is the length of time in which the direct solar (shortwave) radiation at the Earth's surface, falling on a plane perpendicular to the direction of the Sun, is greater than or equal to 120 W m-2.
The minimum solar intensity level of 120 W m-2 is defined by the World Meteorological Organisation and is consistent with observed values of sunshine duration from a Campbell-Stokes recorder (sometimes called a Stokes sphere) that can only measure moderately intense sunlight and brighter.
This parameter is only available in GRIB1.
","unit_id":204,"encoding_ids":["grib1"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":172195,"name":"Longitudinal component of gravity wave stress","shortname":"~","description":"
This parameter is only available in GRIB1.
","unit_id":32,"encoding_ids":["grib1"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":172196,"name":"Meridional component of gravity wave stress","shortname":"~","description":"
","unit_id":76,"encoding_ids":["grib1"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":172205,"name":"Time-mean runoff rate","shortname":"mrort","description":null,"unit_id":5,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":172208,"name":"Time-mean top net short-wave (solar) radiation flux, clear sky","shortname":"~","description":"
This parameter is only available in GRIB1.
","unit_id":76,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":172209,"name":"Time-mean top net long-wave (thermal) radiation flux, clear sky","shortname":"~","description":"
This parameter is only available in GRIB1.
","unit_id":76,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":172210,"name":"Time-mean surface net short-wave (solar) radiation flux, clear sky","shortname":"~","description":"
This parameter is only available in GRIB1.
","unit_id":76,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":172211,"name":"Time-mean surface net long-wave (thermal) radiation flux, clear sky","shortname":"~","description":"
","unit_id":76,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":172228,"name":"Time-mean total precipitation rate","shortname":"tprate","description":"This parameter is the mean rate of total precipitation. It is accumulated precipitation divided by the length of the accumulation period, which depends on the data extracted.
In the ECMWF Integrated Forecasting System (IFS), total precipitation is rain and snow that falls to the Earth's surface. It is the sum of large-scale precipitation and convective precipitation. Large-scale precipitation is generated by the cloud scheme in the IFS. The cloud scheme represents the formation and dissipation of clouds and large-scale precipitation due to changes in atmospheric quantities (such as pressure, temperature and moisture) predicted directly by the IFS at spatial scales of a grid box or larger. Convective precipitation is generated by the convection scheme in the IFS. The convection scheme represents convection at spatial scales smaller than the grid box. See further information. Precipitation parameters do not include fog, dew or the precipitation that evaporates in the atmosphere before it lands at the surface of the Earth.
The units are depth of water equivalent in metres which falls per second (i.e., the depth the water would have if it were spread evenly over the grid box).
Care should be taken when comparing model parameters with observations, because observations are often local to a particular point in space and time, rather than representing averages over a model grid box and model time step .","unit_id":5,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":172239,"name":"Time-mean convective snowfall rate","shortname":"~","description":null,"unit_id":78,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":172240,"name":"Time-mean large-scale snowfall rate","shortname":"~","description":null,"unit_id":78,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":172255,"name":"Indicates a missing value","shortname":"~","description":null,"unit_id":7,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":173008,"name":"Mean surface runoff rate anomaly","shortname":"msrora","description":"An anomaly is a difference from a defined long-term average. Positive/negative values of this parameter indicate that the mean surface runoff rate is higher/lower than the long-term average. The long-term average is typically derived from several decades of model data and will vary with location and time of year (see further information).
The mean surface runoff rate is the amount of water from rainfall or melting snow that is not absorbed by the soil and drains away over the surface. Water may also drain away under the ground. It is the accumulated amount of water, divided by the length of the accumulation period, which depends on the data extracted.
This quantity represents the depth this water would have if it were spread evenly over the grid box.
Care should be taken when comparing model parameters with observations, because observations are often local to a particular point in space and time, rather than representing averages over a model grid box and model time step","unit_id":78,"encoding_ids":["grib1"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":173009,"name":"Mean sub-surface runoff rate anomaly","shortname":"mssrora","description":"An anomaly is a difference from a defined long-term average. Positive/negative values of this parameter indicate that the mean sub-surface runoff rate is higher/lower than the long-term average. The long-term average is typically derived from several decades of model data and will vary with location and time of year (see further information).
The mean sub-surface runoff rate is the amount of water deep in the soil that drains away under the ground. Water may also drain away over the surface. It is the accumulated amount of water, divided by the length of the accumulation period, which depends on the data extracted.
This quantity represents the depth this water would have if it were spread evenly over the grid box.
Care should be taken when comparing model parameters with observations, because observations are often local to a particular point in space and time, rather than representing averages over a model grid box and model time step","unit_id":78,"encoding_ids":["grib1"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":173044,"name":"Time-mean snow evaporation anomalous rate of accumulation","shortname":"~","description":null,"unit_id":78,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":173045,"name":"Time-mean snowmelt anomalous rate of accumulation","shortname":"~","description":null,"unit_id":78,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":173048,"name":"Magnitude of turbulent surface stress anomaly","shortname":"~","description":null,"unit_id":32,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":173050,"name":"Large-scale precipitation fraction anomaly","shortname":"~","description":null,"unit_id":7,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":173142,"name":"Stratiform precipitation (Large-scale precipitation) anomalous rate of accumulation","shortname":"lspara","description":"An anomaly is a difference from a defined long-term average. Positive/negative values of this parameter indicate that the mean large-scale precipitation rate is higher/lower than the long-term average. The long-term average is typically derived from several decades of model data and will vary with location and time of year (see further information).
Mean large-scale precipitation rate is accumulated precipitation divided by the length of the accumulation period, which depends on the data extracted.
For this parameter, precipitation is made up of rain and snow that falls to the Earth's surface, generated by the cloud scheme in the ECMWF Integrated Forecasting System (IFS). The cloud scheme represents the formation and dissipation of clouds and large-scale precipitation due to changes in atmospheric quantities (such as pressure, temperature and moisture) predicted directly by the IFS at spatial scales of a grid box or larger. Precipitation can also be due to convection generated by the convection scheme in the IFS. The convection scheme represents convection at spatial scales smaller than the grid box. See further information.Precipitation parameters do not include fog, dew or the precipitation that evaporates in the atmosphere before it lands at the surface of the Earth.
The units include depth in metres of water equivalent. This is the depth the water would have if it were spread evenly over the grid box.
Care should be taken when comparing model parameters with observations, because observations are often local to a particular point in space and time, rather than representing averages over a model grid box and model time step.","unit_id":5,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":173143,"name":"Mean convective precipitation rate anomaly","shortname":"mcpra","description":"An anomaly is a difference from a defined long-term average. Positive/negative values of this parameter indicate that the mean convective precipitation rate is higher/lower than the long-term average. The long-term average is typically derived from several decades of model data and will vary with location and time of year (see further information ).
Mean convective precipitation rate is accumulated precipitation divided by the length the accumulation period, which depends on the data extracted.
For this parameter, precipitation is rain and snow that falls to the Earth's surface, generated by the convection scheme in the ECMWF Integrated Forecasting System (IFS). The convection scheme represents convection at spatial scales smaller than the grid box. Total precipitation is made up of convective and large-scale precipitation. Large-scale precipitation is generated by the cloud scheme in the IFS. The cloud scheme represents the formation and dissipation of clouds and large-scale precipitation due to changes in atmospheric quantities (such as pressure, temperature and moisture) predicted directly by the IFS at spatial scales of a grid box or larger. See further information.
The units include depth, in metres of water equivalent. This is the depth the water would have if it were spread evenly over the grid box. Care should be taken when comparing model parameters with observations, because observations are often local to a particular point in space and time, rather than representing averages over a model grid box and model time step .","unit_id":5,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":173144,"name":"Snowfall (convective + stratiform) anomalous rate of accumulation","shortname":"sfara","description":"An anomaly is a difference from a defined long-term average. Positive/negative values of this parameter indicate that the mean snowfall rate is higher/lower than the long-term average. The long-term average is typically derived from several decades of model data and will vary with location and time of year (see further information ).
The mean snowfall rate is the accumulated snowfall divided by the length of the accumulation period, which depends on the data extracted.
Snowfall is the sum of large-scale snowfall and convective snowfall. Large-scale snowfall is generated by the cloud scheme in the ECMWF Integrated Forecast System. The cloud scheme represents the formation and dissipation of clouds and large-scale snowfall due to changes in atmospheric quantities (such as pressure, temperature and moisture) predicted directly by the IFS at spatial scales of a grid box or larger. Convective snowfall is generated by the convection scheme in the IFS. The convection scheme represents convection at spatial scales smaller than the grid box. See further information.
The units are depth of water equivalent in metres which falls per second (i.e., the depth the melted snow would have if it were spread evenly over the grid box ).
Care should be taken when comparing model parameters with observations, because observations are often local to a particular point in space and time, rather than representing averages over a model grid box and model time step.","unit_id":78,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":173145,"name":"Boundary layer dissipation anomaly","shortname":"~","description":null,"unit_id":6,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":173146,"name":"Surface sensible heat flux anomalous rate of accumulation","shortname":"sshfara","description":"An anomaly is a difference from a defined long-term average. Since the ECMWF convention for vertical fluxes is positive downwards, a positive anomaly means either a larger downward mean surface sensible heat flux or a smaller upward flux, compared with the long-term average. A negative anomaly means either a smaller downward flux or a larger upward flux. The long-term average is typically derived from several decades of model data and will vary with location and time of year (see further information).
Surface sensible heat flux is the transfer of heat between the Earth's surface and the atmosphere through the effects of turbulent air motion (but excluding any heat transfer resulting from condensation or evaporation). The mean flux is the accumulated flux divided by the length of the accumulation period, which depends on the data extracted.","unit_id":6,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":173147,"name":"Surface latent heat flux anomalous rate of accumulation","shortname":"slhfara","description":"An anomaly is a difference from a defined long-term average. Since the ECMWF convention for vertical fluxes is positive downwards, a positive anomaly means either a larger downward mean surface latent heat flux or a smaller upward flux, compared with the long-term average. A negative anomaly means either a smaller downward flux or a larger upward flux. The long-term average is typically derived from several decades of model data and will vary with location and time of year (see further information).
The surface latent heat flux is the transfer of latent heat (resulting from evaporation, condensation and other moisture phase changes) between the Earth's surface and the atmosphere through the effects of turbulent air motion. Evaporation from the Earth's surface represents a transfer of energy from the surface to the atmosphere. The mean latent heat flux is the accumulated flux divided by the length of the accumulation period, which depends on the data extracted.","unit_id":6,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":173149,"name":"Surface net radiation anomaly","shortname":"~","description":null,"unit_id":6,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":173153,"name":"Short-wave heating rate anomaly","shortname":"~","description":null,"unit_id":37,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":173154,"name":"Long-wave heating rate anomaly","shortname":"~","description":null,"unit_id":37,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":173169,"name":"Surface solar radiation downwards anomalous rate of accumulation","shortname":"ssrdara","description":null,"unit_id":6,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":173175,"name":"Surface thermal radiation downwards anomalous rate of accumulation","shortname":"strdara","description":"An anomaly is a difference from a defined long-term average. Positive/negative values of this parameter indicate that the mean flux of surface thermal radiation downwards is higher/lower than the long-term average. The long-term average is typically derived from several decades of model data and will vary with location and time of year (see further information).
Surface thermal radiation downwards is the amount of thermal (also known as longwave or terrestrial) radiation emitted by the atmosphere and clouds that reaches the Earth's surface. It is the amount of radiation passing through a horizontal plane. The mean flux is the accumulated flux divided by the length of the accumulation period, which depends on the data extracted.
The ECMWF convention for vertical fluxes is positive downwards.","unit_id":6,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":173176,"name":"Surface solar radiation anomalous rate of accumulation","shortname":"ssrara","description":"An anomaly is a difference from a defined long-term average. Positive/negative values of this parameter indicate that the mean net surface solar radiation flux is higher/lower than the long-term average. The long-term average is typically derived from several decades of model data and will vary with location and time of year (see further information).
The net surface solar radiation flux is the amount of solar radiation (also known as shortwave radiation) reaching the surface of the Earth (both direct and diffuse) minus the amount reflected by the Earth's surface (which is governed by the albedo). It is the amount of radiation passing through a horizontal plane, not a plane perpendicular to the direction of the Sun. The mean flux is the accumulated flux divided by the length of the accumulation period, which depends on the data extracted.
The ECMWF convention for vertical fluxes is positive downwards.","unit_id":6,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":173177,"name":"Surface thermal radiation anomalous rate of accumulation","shortname":"strara","description":"An anomaly is a difference from a defined long-term average. Since the ECMWF convention for vertical fluxes is positive downwards, a positive anomaly means either a larger downward mean net surface thermal radiation flux or a smaller upward flux, compared with the long-term average. A negative anomaly means either a smaller downward flux or a larger upward flux. The long-term average is typically derived from several decades of model data and will vary with location and time of year (see further information).
Thermal radiation (also known as longwave or terrestrial radiation) refers to radiation emitted by the atmosphere, clouds and the surface of the Earth. The net surface thermal radiation flux is the difference between downward and upward thermal radiation at the surface of the Earth. It is the amount of radiation passing through a horizontal plane.
The atmosphere and clouds emit thermal radiation in all directions, some of which reaches the surface as downward thermal radiation. The upward thermal radiation at the surface consists of thermal radiation emitted by the surface plus the fraction of downwards thermal radiation reflected upward by the surface. See further documentation
The mean flux is the accumulated flux divided by the length of the accumulation period, which depends on the data extracted.","unit_id":6,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":173178,"name":"Top solar radiation anomalous rate of accumulation","shortname":"tsrara","description":"An anomaly is a difference from a defined long-term average. Positive/negative values of this parameter indicate that the mean net flux of solar radiation at the top of the atmosphere is higher/lower than the long-term average. The long-term average is typically derived from several decades of model data and will vary with location and time of year (see further information).
The net flux of solar radiation (also known as shortwave radiation) at the top of the atmosphere is the incoming solar radiation minus the outgoing solar radiation. It is the amount of radiation passing through a horizontal plane. The incoming solar radiation is the amount received from the Sun. The outgoing solar radiation is the amount reflected and scattered by the Earth's atmosphere and surface. See further documentation.
The mean flux is the accumulated flux divided by the length of the accumulation period, which depends on the data extracted.
The ECMWF convention for vertical fluxes is positive downwards.","unit_id":6,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":173179,"name":"Top thermal radiation anomalous rate of accumulation","shortname":"ttrara","description":"An anomaly is a difference from a defined long-term average. The ECMWF convention for vertical fluxes is positive downwards and the mean flux of thermal radiation at the top of the atmosphere can only be upwards (i.e., negative). Therefore, a positive anomaly means a smaller upward flux of thermal radiation and a negative anomaly means a larger upward flux, compared with the long-term average. The long-term average is typically derived from several decades of model data and will vary with location and time of year (see further information).
The mean flux of thermal radiation (also known as longwave or terrestrial) is the thermal radiation emitted to space at the top of the atmosphere. See further documentation. The mean flux is the accumulated flux divided by the length of the accumulation period, which depends on the data extracted.
The thermal radiation emitted to space at the top of the atmosphere is commonly known as the Outgoing Longwave Radiation (OLR) (but taking a flux from the atmosphere to space as positive).","unit_id":6,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":173180,"name":"East-West surface stress anomalous rate of accumulation","shortname":"ewssara","description":"An anomaly is a difference from a defined long-term average. A positive anomaly indicates that the mean East-West surface stress is more eastward (or less westward) than average. A negative anomaly indicates that the mean East-West surface stress is more westward (or less eastward) than the average. The long-term average is typically derived from several decades of model data and will vary with location and time of year (see further information).
Air flowing over a surface exerts a stress that transfers momentum to the surface and slows the wind. The mean East-West surface stress is the accumulated eastward surface stress divided by the length of the accumulation period, which depends on the data extracted.
The East-West surface stress is the stress on the Earth's surface in the eastward direction due to both the turbulent interactions between the atmosphere and the surface, and to turbulent orographic form drag. The turbulent interactions between the atmosphere and the surface are due to the roughness of the surface. The turbulent orographic form drag is the stress due to the valleys, hills and mountains on horizontal scales below 5km being derived from land surface data at about 1 km resolution. See further information.","unit_id":32,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":173181,"name":"North-South surface stress anomalous rate of accumulation","shortname":"nsssara","description":"An anomaly is a difference from a defined long-term average. A positive anomaly indicates that the mean North-South surface stress is more northward (or less southward) than average. A negative anomaly indicates that the mean North-South surface stress is more southward (or less northward) than the average. The long-term average is typically derived from several decades of model data and will vary with location and time of year (see further information).
Air flowing over a surface exerts a stress that transfers momentum to the surface and slows the wind. The mean North-South surface stress is the accumulated northward surface stress divided by the length of the accumulation period, which depends on the data extracted.
The North-South surface stress is the stress on the Earth's surface in the northward direction due to both the turbulent interactions between the atmosphere and the surface, and to turbulent orographic form drag. The turbulent interactions between the atmosphere and the surface are due to the roughness of the surface. The turbulent orographic form drag is the stress due to the valleys, hills and mountains on horizontal scales below 5km being derived from land surface data at about 1 km resolution. See further information.","unit_id":32,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":173182,"name":"Time-mean evaporation anomalous rate of accumulation","shortname":"evara","description":"
An anomaly is a difference from a defined long-term average. The ECMWF Integrated Forecasting System convention is that downward fluxes are positive. Therefore a positive anomaly means either a larger downward mean evaporation flux (more condensation) or a smaller upward flux (less evaporation), compared with the long-term average. A negative anomaly means either a smaller downward flux or a larger upward flux. The long-term average is typically derived from several decades of model data and will vary with location and time of year (see further information).
Evaporation is the amount of water that has evaporated from the Earth's surface, including a simplified representation of transpiration (from vegetation), into vapour in the air above.The mean evaporation rate is the accumulated evaporation divided by the length of the accumulation period, which depends on the data extracted.
","unit_id":78,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":173189,"name":"Sunshine duration anomalous rate of accumulation","shortname":"sundara","description":"An anomaly is a difference from a defined long-term average. Positive/negative values of this parameter indicate that the mean sunshine duration rate is higher/lower than the long-term average. The long-term average is typically derived from several decades of model data and will vary with location and time of year (see further information).
The mean sunshine duration rate is the accumulated sunshine duration divided by the length of the accumulation period, which depends on the data extracted.
The sunshine duration is the length of time in which the direct solar (shortwave) radiation at the Earth's surface, falling on a plane perpendicular to the direction of the Sun, is greater than or equal to 120 W m-2.
The minimum solar intensity level of 120 W m-2 is defined by the World Meteorological Organisation and is consistent with observed values of sunshine duration from a Campbell-Stokes recorder (sometimes called a Stokes sphere) that can only measure moderately intense sunlight and brighter.","unit_id":23,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":173195,"name":"Longitudinal component of gravity wave stress anomaly","shortname":"~","description":"","unit_id":32,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":173196,"name":"Meridional component of gravity wave stress anomaly","shortname":"~","description":null,"unit_id":32,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":173197,"name":"Gravity wave dissipation anomaly","shortname":"~","description":null,"unit_id":6,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":173205,"name":"Runoff anomalous rate of accumulation","shortname":"roara","description":"An anomaly is a difference from a defined long-term average. Positive/negative values of this parameter indicate that the mean runoff rate is higher/lower than the long-term average. The long-term average is typically derived from several decades of model data and will vary with location and time of year (see further information).
The mean runoff rate is the total amount of water from rainfall, melting snow, or deep in the soil, that drains away over the surface and under the ground. It is the accumulated amount of water, divided by the length of the accumulation period, which depends on the data extracted.
This quantity represents the depth this water would have if it were spread evenly over the grid box.
Care should be taken when comparing model parameters with observations, because observations are often local to a particular point in space and time, rather than representing averages over a model grid box and model time step.","unit_id":5,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":173208,"name":"Top net solar radiation, clear sky anomaly","shortname":"~","description":null,"unit_id":6,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":173209,"name":"Top net thermal radiation, clear sky anomaly","shortname":"~","description":null,"unit_id":6,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":173210,"name":"Surface net solar radiation, clear sky anomaly","shortname":"~","description":null,"unit_id":6,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":173211,"name":"Surface net thermal radiation, clear sky anomaly","shortname":"~","description":null,"unit_id":6,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":173212,"name":"Solar insolation anomalous rate of accumulation","shortname":"soiara","description":"An anomaly is a difference from a defined long-term average. Positive/negative values of this parameter indicate that the mean solar insolation is higher/lower than the long-term average. The long-term average is typically derived from several decades of model data and will vary with location and time of year (see further information).
Solar insolation is the incoming radiation from the Sun (also known as solar or shortwave radiation) at the top of the atmosphere (TOA). It is the amount of radiation passing through a horizontal plane, not a plane perpendicular to the direction of the Sun.
Solar insolation has a diurnal cycle (as it is defined into a horizontal plane and not a plane perpendicular to the Sun), as well as an annual cycle due to the change in Sun-Earth distance, and the approximately 11-year solar cycle. Solar insolation at the TOA has experienced no absorption, scattering or reflection within the atmosphere (e.g., from clouds, water vapour, ozone, trace gases and aerosol).
The mean flux is the accumulated flux divided by the length of the accumulation period, which depends on the data extracted. The ECMWF convention for vertical fluxes is positive downwards.","unit_id":79,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":173228,"name":"Total precipitation anomalous rate of accumulation","shortname":"tpara","description":"An anomaly is a difference from a defined long-term average. Positive/negative values of this parameter indicate that the mean precipitation rate is higher/lower than the long-term average. The long-term average is typically derived from several decades of model data and will vary with location and time of year (see further information).
The mean precipitation rate is the accumulated precipitation divided by the length of the accumulation period, which depends on the data extracted.
In the ECMWF Integrated Forecasting System (IFS), total precipitation is rain and snow that falls to the Earth's surface. It is the sum of large-scale precipitation and convective precipitation. Large-scale precipitation is generated by the cloud scheme in the IFS. The cloud scheme represents the formation and dissipation of clouds and large-scale precipitation due to changes in atmospheric quantities (such as pressure, temperature and moisture) predicted directly by the IFS at spatial scales of a grid box or larger. Convective precipitation is generated by the convection scheme in the IFS. The convection scheme represents convection at spatial scales smaller than the grid box. See further information. Precipitation parameters do not include fog, dew or the precipitation that evaporates in the atmosphere before it lands at the surface of the Earth.
The units are depth of water equivalent in metres which falls per second. It is the depth the water would have if it were spread evenly over the grid box.
Care should be taken when comparing model parameters with observations, because observations are often local to a particular point in space and time, rather than representing averages over a model grid box and model time step .","unit_id":5,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":173239,"name":"Convective snowfall anomaly","shortname":"~","description":null,"unit_id":78,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":173240,"name":"Large scale snowfall anomaly","shortname":"~","description":null,"unit_id":78,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":173255,"name":"Indicates a missing value","shortname":"~","description":null,"unit_id":7,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":174006,"name":"Total soil moisture","shortname":"~","description":null,"unit_id":4,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":174008,"name":"Surface runoff","shortname":"sro","description":"Lateral water flow occurring at the surface\n [This GRIB2 encoding is only to be used in CARRA/CERRA, S2S and UERRA. Please use paramId 231010 otherwise.]","unit_id":22,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":174010,"name":"Clear-sky (II) down surface sw flux","shortname":"sswcsdown","description":"","unit_id":76,"encoding_ids":["grib1"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":174013,"name":"Clear-sky (II) up surface sw flux","shortname":"sswcsup","description":"","unit_id":76,"encoding_ids":["grib1"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":174025,"name":"Visibility at 1.5m","shortname":"vis15","description":"","unit_id":4,"encoding_ids":["grib1"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":174031,"name":"Fraction of sea-ice in sea","shortname":"~","description":null,"unit_id":3,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":174034,"name":"Open-sea surface temperature","shortname":"~","description":null,"unit_id":2,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":174039,"name":"Volumetric soil water layer 1","shortname":"~","description":null,"unit_id":10,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":174040,"name":"Volumetric soil water layer 2","shortname":"~","description":null,"unit_id":10,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":174041,"name":"Volumetric soil water layer 3","shortname":"~","description":null,"unit_id":10,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":174042,"name":"Volumetric soil water layer 4","shortname":"~","description":null,"unit_id":10,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":174049,"name":"10 metre wind gust in the last 24 hours","shortname":"~","description":"","unit_id":5,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":174050,"name":"Minimum temperature at 1.5m since previous post-processing","shortname":"mn15t","description":"","unit_id":2,"encoding_ids":["grib1"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":174051,"name":"Maximum temperature at 1.5m since previous post-processing","shortname":"mx15t","description":"","unit_id":2,"encoding_ids":["grib1"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":174052,"name":"Relative humidity at 1.5m","shortname":"rhum","description":"","unit_id":21,"encoding_ids":["grib1"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":174055,"name":"1.5m temperature - mean in the last 24 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These fields are for internal use by ECMWF and will not be disseminated. The SPP fields as well as the SPPT fields are required by the perturbed ensemble members to propagate information about the state of the model uncertainty scheme from one model integration to another.","unit_id":23,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":213129,"name":"Random pattern 29 for SPP scheme","shortname":"spp29","description":"Pattern 29 for Stochastically Perturbed Parametrisation (SPP) scheme.
These fields are for internal use by ECMWF and will not be disseminated. The SPP fields as well as the SPPT fields are required by the perturbed ensemble members to propagate information about the state of the model uncertainty scheme from one model integration to another.","unit_id":23,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":213130,"name":"Random pattern 30 for SPP scheme","shortname":"spp30","description":"Pattern 30 for Stochastically Perturbed Parametrisation (SPP) scheme.
These fields are for internal use by ECMWF and will not be disseminated. The SPP fields as well as the SPPT fields are required by the perturbed ensemble members to propagate information about the state of the model uncertainty scheme from one model integration to another.","unit_id":23,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":213131,"name":"Random pattern 31 for SPP scheme","shortname":"spp31","description":"Pattern 31 for Stochastically Perturbed Parametrisation (SPP) scheme.
These fields are for internal use by ECMWF and will not be disseminated. The SPP fields as well as the SPPT fields are required by the perturbed ensemble members to propagate information about the state of the model uncertainty scheme from one model integration to another.","unit_id":23,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":213132,"name":"Random pattern 32 for SPP scheme","shortname":"spp32","description":"Pattern 32 for Stochastically Perturbed Parametrisation (SPP) scheme.
These fields are for internal use by ECMWF and will not be disseminated. The SPP fields as well as the SPPT fields are required by the perturbed ensemble members to propagate information about the state of the model uncertainty scheme from one model integration to another.","unit_id":23,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":213133,"name":"Random pattern 33 for SPP scheme","shortname":"spp33","description":"Pattern 33 for Stochastically Perturbed Parametrisation (SPP) scheme.
These fields are for internal use by ECMWF and will not be disseminated. The SPP fields as well as the SPPT fields are required by the perturbed ensemble members to propagate information about the state of the model uncertainty scheme from one model integration to another.","unit_id":23,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":213134,"name":"Random pattern 34 for SPP scheme","shortname":"spp34","description":"Pattern 34 for Stochastically Perturbed Parametrisation (SPP) scheme.
These fields are for internal use by ECMWF and will not be disseminated. The SPP fields as well as the SPPT fields are required by the perturbed ensemble members to propagate information about the state of the model uncertainty scheme from one model integration to another.","unit_id":23,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":213135,"name":"Random pattern 35 for SPP scheme","shortname":"spp35","description":"Pattern 35 for Stochastically Perturbed Parametrisation (SPP) scheme.
These fields are for internal use by ECMWF and will not be disseminated. The SPP fields as well as the SPPT fields are required by the perturbed ensemble members to propagate information about the state of the model uncertainty scheme from one model integration to another.","unit_id":23,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":213136,"name":"Random pattern 36 for SPP scheme","shortname":"spp36","description":"Pattern 36 for Stochastically Perturbed Parametrisation (SPP) scheme.
These fields are for internal use by ECMWF and will not be disseminated. The SPP fields as well as the SPPT fields are required by the perturbed ensemble members to propagate information about the state of the model uncertainty scheme from one model integration to another.","unit_id":23,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":213137,"name":"Random pattern 37 for SPP scheme","shortname":"spp37","description":"Pattern 37 for Stochastically Perturbed Parametrisation (SPP) scheme.
These fields are for internal use by ECMWF and will not be disseminated. The SPP fields as well as the SPPT fields are required by the perturbed ensemble members to propagate information about the state of the model uncertainty scheme from one model integration to another.","unit_id":23,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":213138,"name":"Random pattern 38 for SPP scheme","shortname":"spp38","description":"Pattern 38 for Stochastically Perturbed Parametrisation (SPP) scheme.
These fields are for internal use by ECMWF and will not be disseminated. The SPP fields as well as the SPPT fields are required by the perturbed ensemble members to propagate information about the state of the model uncertainty scheme from one model integration to another.","unit_id":23,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":213139,"name":"Random pattern 39 for SPP scheme","shortname":"spp39","description":"Pattern 39 for Stochastically Perturbed Parametrisation (SPP) scheme.
These fields are for internal use by ECMWF and will not be disseminated. The SPP fields as well as the SPPT fields are required by the perturbed ensemble members to propagate information about the state of the model uncertainty scheme from one model integration to another.","unit_id":23,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":213140,"name":"Random pattern 40 for SPP scheme","shortname":"spp40","description":"Pattern 40 for Stochastically Perturbed Parametrisation (SPP) scheme.
These fields are for internal use by ECMWF and will not be disseminated. The SPP fields as well as the SPPT fields are required by the perturbed ensemble members to propagate information about the state of the model uncertainty scheme from one model integration to another.","unit_id":23,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":213141,"name":"Random pattern 41 for SPP scheme","shortname":"spp41","description":"Pattern 41 for Stochastically Perturbed Parametrisation (SPP) scheme.
These fields are for internal use by ECMWF and will not be disseminated. The SPP fields as well as the SPPT fields are required by the perturbed ensemble members to propagate information about the state of the model uncertainty scheme from one model integration to another.","unit_id":23,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":213142,"name":"Random pattern 42 for SPP scheme","shortname":"spp42","description":"Pattern 42 for Stochastically Perturbed Parametrisation (SPP) scheme.
These fields are for internal use by ECMWF and will not be disseminated. The SPP fields as well as the SPPT fields are required by the perturbed ensemble members to propagate information about the state of the model uncertainty scheme from one model integration to another.","unit_id":23,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":213143,"name":"Random pattern 43 for SPP scheme","shortname":"spp43","description":"Pattern 43 for Stochastically Perturbed Parametrisation (SPP) scheme.
These fields are for internal use by ECMWF and will not be disseminated. The SPP fields as well as the SPPT fields are required by the perturbed ensemble members to propagate information about the state of the model uncertainty scheme from one model integration to another.","unit_id":23,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":213144,"name":"Random pattern 44 for SPP scheme","shortname":"spp44","description":"Pattern 44 for Stochastically Perturbed Parametrisation (SPP) scheme.
These fields are for internal use by ECMWF and will not be disseminated. The SPP fields as well as the SPPT fields are required by the perturbed ensemble members to propagate information about the state of the model uncertainty scheme from one model integration to another.","unit_id":23,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":213145,"name":"Random pattern 45 for SPP scheme","shortname":"spp45","description":"Pattern 45 for Stochastically Perturbed Parametrisation (SPP) scheme.
These fields are for internal use by ECMWF and will not be disseminated. The SPP fields as well as the SPPT fields are required by the perturbed ensemble members to propagate information about the state of the model uncertainty scheme from one model integration to another.","unit_id":23,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":213146,"name":"Random pattern 46 for SPP scheme","shortname":"spp46","description":"Pattern 46 for Stochastically Perturbed Parametrisation (SPP) scheme.
These fields are for internal use by ECMWF and will not be disseminated. The SPP fields as well as the SPPT fields are required by the perturbed ensemble members to propagate information about the state of the model uncertainty scheme from one model integration to another.","unit_id":23,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":213147,"name":"Random pattern 47 for SPP scheme","shortname":"spp47","description":"Pattern 47 for Stochastically Perturbed Parametrisation (SPP) scheme.
These fields are for internal use by ECMWF and will not be disseminated. The SPP fields as well as the SPPT fields are required by the perturbed ensemble members to propagate information about the state of the model uncertainty scheme from one model integration to another.","unit_id":23,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":213148,"name":"Random pattern 48 for SPP scheme","shortname":"spp48","description":"Pattern 48 for Stochastically Perturbed Parametrisation (SPP) scheme.
These fields are for internal use by ECMWF and will not be disseminated. The SPP fields as well as the SPPT fields are required by the perturbed ensemble members to propagate information about the state of the model uncertainty scheme from one model integration to another.","unit_id":23,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":213149,"name":"Random pattern 49 for SPP scheme","shortname":"spp49","description":"Pattern 49 for Stochastically Perturbed Parametrisation (SPP) scheme.
These fields are for internal use by ECMWF and will not be disseminated. The SPP fields as well as the SPPT fields are required by the perturbed ensemble members to propagate information about the state of the model uncertainty scheme from one model integration to another.","unit_id":23,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":213150,"name":"Random pattern 50 for SPP scheme","shortname":"spp50","description":"Pattern 50 for Stochastically Perturbed Parametrisation (SPP) scheme.
These fields are for internal use by ECMWF and will not be disseminated. The SPP fields as well as the SPPT fields are required by the perturbed ensemble members to propagate information about the state of the model uncertainty scheme from one model integration to another.","unit_id":23,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":213151,"name":"Random pattern 51 for SPP scheme","shortname":"spp51","description":"Pattern 51 for Stochastically Perturbed Parametrisation (SPP) scheme.\r\n\r\nThese fields are for internal use by ECMWF and will not be disseminated.\r\nThe SPP fields as well as the SPPT fields are required by the perturbed ensemble members to propagate information about the state of the model uncertainty scheme from one model integration to another","unit_id":23,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":213152,"name":"Random pattern 52 for SPP scheme","shortname":"spp52","description":"Pattern 52 for Stochastically Perturbed Parametrisation (SPP) scheme.\r\n\r\nThese fields are for internal use by ECMWF and will not be disseminated.\r\nThe SPP fields as well as the SPPT fields are required by the perturbed ensemble members to propagate information about the state of the model uncertainty scheme from one model integration to another","unit_id":23,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":213153,"name":"Random pattern 53 for SPP scheme","shortname":"spp53","description":"Pattern 53 for Stochastically Perturbed Parametrisation (SPP) scheme.\r\n\r\nThese fields are for internal use by ECMWF and will not be disseminated.\r\nThe SPP fields as well as the SPPT fields are required by the perturbed ensemble members to propagate information about the state of the model uncertainty scheme from one model integration to another","unit_id":23,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":213154,"name":"Random pattern 54 for SPP scheme","shortname":"spp54","description":"Pattern 54 for Stochastically Perturbed Parametrisation (SPP) scheme.\r\n\r\nThese fields are for internal use by ECMWF and will not be disseminated.\r\nThe SPP fields as well as the SPPT fields are required by the perturbed ensemble members to propagate information about the state of the model uncertainty scheme from one model integration to another","unit_id":23,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":213155,"name":"Random pattern 55 for SPP scheme","shortname":"spp55","description":"Pattern 55 for Stochastically Perturbed Parametrisation (SPP) scheme.\r\n\r\nThese fields are for internal use by ECMWF and will not be disseminated.\r\nThe SPP fields as well as the SPPT fields are required by the perturbed ensemble members to propagate information about the state of the model uncertainty scheme from one model integration to another","unit_id":23,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":213156,"name":"Random pattern 56 for SPP scheme","shortname":"spp56","description":"Pattern 56 for Stochastically Perturbed Parametrisation (SPP) scheme.\r\n\r\nThese fields are for internal use by ECMWF and will not be disseminated.\r\nThe SPP fields as well as the SPPT fields are required by the perturbed ensemble members to propagate information about the state of the model uncertainty scheme from one model integration to another","unit_id":23,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":213157,"name":"Random pattern 57 for SPP scheme","shortname":"spp57","description":"Pattern 57 for Stochastically Perturbed Parametrisation (SPP) scheme.\r\n\r\nThese fields are for internal use by ECMWF and will not be disseminated.\r\nThe SPP fields as well as the SPPT fields are required by the perturbed ensemble members to propagate information about the state of the model uncertainty scheme from one model integration to another","unit_id":23,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":213158,"name":"Random pattern 58 for SPP scheme","shortname":"spp58","description":"Pattern 58 for Stochastically Perturbed Parametrisation (SPP) scheme.\r\n\r\nThese fields are for internal use by ECMWF and will not be disseminated.\r\nThe SPP fields as well as the SPPT fields are required by the perturbed ensemble members to propagate information about the state of the model uncertainty scheme from one model integration to another","unit_id":23,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":213159,"name":"Random pattern 59 for SPP scheme","shortname":"spp59","description":"Pattern 59 for Stochastically Perturbed Parametrisation (SPP) scheme.\r\n\r\nThese fields are for internal use by ECMWF and will not be disseminated.\r\nThe SPP fields as well as the SPPT fields are required by the perturbed ensemble members to propagate information about the state of the model uncertainty scheme from one model integration to another","unit_id":23,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":213160,"name":"Random pattern 60 for SPP scheme","shortname":"spp60","description":"Pattern 60 for Stochastically Perturbed Parametrisation (SPP) scheme.\r\n\r\nThese fields are for internal use by ECMWF and will not be disseminated.\r\nThe SPP fields as well as the SPPT fields are required by the perturbed ensemble members to propagate information about the state of the model uncertainty scheme from one model integration to another","unit_id":23,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":213161,"name":"Random pattern 61 for SPP scheme","shortname":"spp61","description":"Pattern 61 for Stochastically Perturbed Parametrisation (SPP) scheme.\r\n\r\nThese fields are for internal use by ECMWF and will not be disseminated.\r\nThe SPP fields as well as the SPPT fields are required by the perturbed ensemble members to propagate information about the state of the model uncertainty scheme from one model integration to another","unit_id":23,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":213162,"name":"Random pattern 62 for SPP scheme","shortname":"spp62","description":"Pattern 62 for Stochastically Perturbed Parametrisation (SPP) scheme.\r\n\r\nThese fields are for internal use by ECMWF and will not be disseminated.\r\nThe SPP fields as well as the SPPT fields are required by the perturbed ensemble members to propagate information about the state of the model uncertainty scheme from one model integration to another","unit_id":23,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":213163,"name":"Random pattern 63 for SPP scheme","shortname":"spp63","description":"Pattern 63 for Stochastically Perturbed Parametrisation (SPP) scheme.\r\n\r\nThese fields are for internal use by ECMWF and will not be disseminated.\r\nThe SPP fields as well as the SPPT fields are required by the perturbed ensemble members to propagate information about the state of the model uncertainty scheme from one model integration to another","unit_id":23,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":213164,"name":"Random pattern 64 for SPP scheme","shortname":"spp64","description":"Pattern 64 for Stochastically Perturbed Parametrisation (SPP) scheme.\r\n\r\nThese fields are for internal use by ECMWF and will not be disseminated.\r\nThe SPP fields as well as the SPPT fields are required by the perturbed ensemble members to propagate information about the state of the model uncertainty scheme from one model integration to another","unit_id":23,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":213165,"name":"Random pattern 65 for SPP scheme","shortname":"spp65","description":"Pattern 65 for Stochastically Perturbed Parametrisation (SPP) scheme.\r\n\r\nThese fields are for internal use by ECMWF and will not be disseminated.\r\nThe SPP fields as well as the SPPT fields are required by the perturbed ensemble members to propagate information about the state of the model uncertainty scheme from one model integration to another","unit_id":23,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":213166,"name":"Random pattern 66 for SPP scheme","shortname":"spp66","description":"Pattern 66 for Stochastically Perturbed Parametrisation (SPP) scheme.\r\n\r\nThese fields are for internal use by ECMWF and will not be disseminated.\r\nThe SPP fields as well as the SPPT fields are required by the perturbed ensemble members to propagate information about the state of the model uncertainty scheme from one model integration to another","unit_id":23,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":213167,"name":"Random pattern 67 for SPP scheme","shortname":"spp67","description":"Pattern 67 for Stochastically Perturbed Parametrisation (SPP) scheme.\r\n\r\nThese fields are for internal use by ECMWF and will not be disseminated.\r\nThe SPP fields as well as the SPPT fields are required by the perturbed ensemble members to propagate information about the state of the model uncertainty scheme from one model integration to another","unit_id":23,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":213168,"name":"Random pattern 68 for SPP scheme","shortname":"spp68","description":"Pattern 68 for Stochastically Perturbed Parametrisation (SPP) scheme.\r\n\r\nThese fields are for internal use by ECMWF and will not be disseminated.\r\nThe SPP fields as well as the SPPT fields are required by the perturbed ensemble members to propagate information about the state of the model uncertainty scheme from one model integration to another","unit_id":23,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":213169,"name":"Random pattern 69 for SPP scheme","shortname":"spp69","description":"Pattern 69 for Stochastically Perturbed Parametrisation (SPP) scheme.\r\n\r\nThese fields are for internal use by ECMWF and will not be disseminated.\r\nThe SPP fields as well as the SPPT fields are required by the perturbed ensemble members to propagate information about the state of the model uncertainty scheme from one model integration to another","unit_id":23,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":213170,"name":"Random pattern 70 for SPP scheme","shortname":"spp70","description":"Pattern 70 for Stochastically Perturbed Parametrisation (SPP) scheme.\r\n\r\nThese fields are for internal use by ECMWF and will not be disseminated.\r\nThe SPP fields as well as the SPPT fields are required by the perturbed ensemble members to propagate information about the state of the model uncertainty scheme from one model integration to another","unit_id":23,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":213171,"name":"Random pattern 71 for SPP scheme","shortname":"spp71","description":"Pattern 71 for Stochastically Perturbed Parametrisation (SPP) scheme.\r\n\r\nThese fields are for internal use by ECMWF and will not be disseminated.\r\nThe SPP fields as well as the SPPT fields are required by the perturbed ensemble members to propagate information about the state of the model uncertainty scheme from one model integration to another","unit_id":23,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":213172,"name":"Random pattern 72 for SPP scheme","shortname":"spp72","description":"Pattern 72 for Stochastically Perturbed Parametrisation (SPP) scheme.\r\n\r\nThese fields are for internal use by ECMWF and will not be disseminated.\r\nThe SPP fields as well as the SPPT fields are required by the perturbed ensemble members to propagate information about the state of the model uncertainty scheme from one model integration to another","unit_id":23,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":213173,"name":"Random pattern 73 for SPP scheme","shortname":"spp73","description":"Pattern 73 for Stochastically Perturbed Parametrisation (SPP) scheme.\r\n\r\nThese fields are for internal use by ECMWF and will not be disseminated.\r\nThe SPP fields as well as the SPPT fields are required by the perturbed ensemble members to propagate information about the state of the model uncertainty scheme from one model integration to another","unit_id":23,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":213174,"name":"Random pattern 74 for SPP scheme","shortname":"spp74","description":"Pattern 74 for Stochastically Perturbed Parametrisation (SPP) scheme.\r\n\r\nThese fields are for internal use by ECMWF and will not be disseminated.\r\nThe SPP fields as well as the SPPT fields are required by the perturbed ensemble members to propagate information about the state of the model uncertainty scheme from one model integration to another","unit_id":23,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":213175,"name":"Random pattern 75 for SPP scheme","shortname":"spp75","description":"Pattern 75 for Stochastically Perturbed Parametrisation (SPP) scheme.\r\n\r\nThese fields are for internal use by ECMWF and will not be disseminated.\r\nThe SPP fields as well as the SPPT fields are required by the perturbed ensemble members to propagate information about the state of the model uncertainty scheme from one model integration to another","unit_id":23,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":213176,"name":"Random pattern 76 for SPP scheme","shortname":"spp76","description":"Pattern 76 for Stochastically Perturbed Parametrisation (SPP) scheme.\r\n\r\nThese fields are for internal use by ECMWF and will not be disseminated.\r\nThe SPP fields as well as the SPPT fields are required by the perturbed ensemble members to propagate information about the state of the model uncertainty scheme from one model integration to another","unit_id":23,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":213177,"name":"Random pattern 77 for SPP scheme","shortname":"spp77","description":"Pattern 77 for Stochastically Perturbed Parametrisation (SPP) scheme.\r\n\r\nThese fields are for internal use by ECMWF and will not be disseminated.\r\nThe SPP fields as well as the SPPT fields are required by the perturbed ensemble members to propagate information about the state of the model uncertainty scheme from one model integration to another","unit_id":23,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":213178,"name":"Random pattern 78 for SPP scheme","shortname":"spp78","description":"Pattern 78 for Stochastically Perturbed Parametrisation (SPP) scheme.\r\n\r\nThese fields are for internal use by ECMWF and will not be disseminated.\r\nThe SPP fields as well as the SPPT fields are required by the perturbed ensemble members to propagate information about the state of the model uncertainty scheme from one model integration to another","unit_id":23,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":213179,"name":"Random pattern 79 for SPP scheme","shortname":"spp79","description":"Pattern 79 for Stochastically Perturbed Parametrisation (SPP) scheme.\r\n\r\nThese fields are for internal use by ECMWF and will not be disseminated.\r\nThe SPP fields as well as the SPPT fields are required by the perturbed ensemble members to propagate information about the state of the model uncertainty scheme from one model integration to another","unit_id":23,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":213180,"name":"Random pattern 80 for SPP scheme","shortname":"spp80","description":"Pattern 80 for Stochastically Perturbed Parametrisation (SPP) scheme.\r\n\r\nThese fields are for internal use by ECMWF and will not be disseminated.\r\nThe SPP fields as well as the SPPT fields are required by the perturbed ensemble members to propagate information about the state of the model uncertainty scheme from one model integration to another","unit_id":23,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":213181,"name":"Random pattern 81 for SPP scheme","shortname":"spp81","description":"Pattern 81 for Stochastically Perturbed Parametrisation (SPP) scheme.\r\n\r\nThese fields are for internal use by ECMWF and will not be disseminated.\r\nThe SPP fields as well as the SPPT fields are required by the perturbed ensemble members to propagate information about the state of the model uncertainty scheme from one model integration to another","unit_id":23,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":213182,"name":"Random pattern 82 for SPP scheme","shortname":"spp82","description":"Pattern 82 for Stochastically Perturbed Parametrisation (SPP) scheme.\r\n\r\nThese fields are for internal use by ECMWF and will not be disseminated.\r\nThe SPP fields as well as the SPPT fields are required by the perturbed ensemble members to propagate information about the state of the model uncertainty scheme from one model integration to another","unit_id":23,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":213183,"name":"Random pattern 83 for SPP scheme","shortname":"spp83","description":"Pattern 83 for Stochastically Perturbed Parametrisation (SPP) scheme.\r\n\r\nThese fields are for internal use by ECMWF and will not be disseminated.\r\nThe SPP fields as well as the SPPT fields are required by the perturbed ensemble members to propagate information about the state of the model uncertainty scheme from one model integration to another","unit_id":23,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":213184,"name":"Random pattern 84 for SPP scheme","shortname":"spp84","description":"Pattern 84 for Stochastically Perturbed Parametrisation (SPP) scheme.\r\n\r\nThese fields are for internal use by ECMWF and will not be disseminated.\r\nThe SPP fields as well as the SPPT fields are required by the perturbed ensemble members to propagate information about the state of the model uncertainty scheme from one model integration to another","unit_id":23,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":213185,"name":"Random pattern 85 for SPP scheme","shortname":"spp85","description":"Pattern 85 for Stochastically Perturbed Parametrisation (SPP) scheme.\r\n\r\nThese fields are for internal use by ECMWF and will not be disseminated.\r\nThe SPP fields as well as the SPPT fields are required by the perturbed ensemble members to propagate information about the state of the model uncertainty scheme from one model integration to another","unit_id":23,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":213186,"name":"Random pattern 86 for SPP scheme","shortname":"spp86","description":"Pattern 86 for Stochastically Perturbed Parametrisation (SPP) scheme.\r\n\r\nThese fields are for internal use by ECMWF and will not be disseminated.\r\nThe SPP fields as well as the SPPT fields are required by the perturbed ensemble members to propagate information about the state of the model uncertainty scheme from one model integration to another","unit_id":23,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":213187,"name":"Random pattern 87 for SPP scheme","shortname":"spp87","description":"Pattern 87 for Stochastically Perturbed Parametrisation (SPP) scheme.\r\n\r\nThese fields are for internal use by ECMWF and will not be disseminated.\r\nThe SPP fields as well as the SPPT fields are required by the perturbed ensemble members to propagate information about the state of the model uncertainty scheme from one model integration to another","unit_id":23,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":213188,"name":"Random pattern 88 for SPP scheme","shortname":"spp88","description":"Pattern 88 for Stochastically Perturbed Parametrisation (SPP) scheme.\r\n\r\nThese fields are for internal use by ECMWF and will not be disseminated.\r\nThe SPP fields as well as the SPPT fields are required by the perturbed ensemble members to propagate information about the state of the model uncertainty scheme from one model integration to another","unit_id":23,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":213189,"name":"Random pattern 89 for SPP scheme","shortname":"spp89","description":"Pattern 89 for Stochastically Perturbed Parametrisation (SPP) scheme.\r\n\r\nThese fields are for internal use by ECMWF and will not be disseminated.\r\nThe SPP fields as well as the SPPT fields are required by the perturbed ensemble members to propagate information about the state of the model uncertainty scheme from one model integration to another","unit_id":23,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":213190,"name":"Random pattern 90 for SPP scheme","shortname":"spp90","description":"Pattern 90 for Stochastically Perturbed Parametrisation (SPP) scheme.\r\n\r\nThese fields are for internal use by ECMWF and will not be disseminated.\r\nThe SPP fields as well as the SPPT fields are required by the perturbed ensemble members to propagate information about the state of the model uncertainty scheme from one model integration to another","unit_id":23,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":213191,"name":"Random pattern 91 for SPP scheme","shortname":"spp91","description":"Pattern 91 for Stochastically Perturbed Parametrisation (SPP) scheme.\r\n\r\nThese fields are for internal use by ECMWF and will not be disseminated.\r\nThe SPP fields as well as the SPPT fields are required by the perturbed ensemble members to propagate information about the state of the model uncertainty scheme from one model integration to another","unit_id":23,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":213192,"name":"Random pattern 92 for SPP scheme","shortname":"spp92","description":"Pattern 92 for Stochastically Perturbed Parametrisation (SPP) scheme.\r\n\r\nThese fields are for internal use by ECMWF and will not be disseminated.\r\nThe SPP fields as well as the SPPT fields are required by the perturbed ensemble members to propagate information about the state of the model uncertainty scheme from one model integration to another","unit_id":23,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":213193,"name":"Random pattern 93 for SPP scheme","shortname":"spp93","description":"Pattern 93 for Stochastically Perturbed Parametrisation (SPP) scheme.\r\n\r\nThese fields are for internal use by ECMWF and will not be disseminated.\r\nThe SPP fields as well as the SPPT fields are required by the perturbed ensemble members to propagate information about the state of the model uncertainty scheme from one model integration to another","unit_id":23,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":213194,"name":"Random pattern 94 for SPP scheme","shortname":"spp94","description":"Pattern 94 for Stochastically Perturbed Parametrisation (SPP) scheme.\r\n\r\nThese fields are for internal use by ECMWF and will not be disseminated.\r\nThe SPP fields as well as the SPPT fields are required by the perturbed ensemble members to propagate information about the state of the model uncertainty scheme from one model integration to another","unit_id":23,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":213195,"name":"Random pattern 95 for SPP scheme","shortname":"spp95","description":"Pattern 95 for Stochastically Perturbed Parametrisation (SPP) scheme.\r\n\r\nThese fields are for internal use by ECMWF and will not be disseminated.\r\nThe SPP fields as well as the SPPT fields are required by the perturbed ensemble members to propagate information about the state of the model uncertainty scheme from one model integration to another","unit_id":23,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":213196,"name":"Random pattern 96 for SPP scheme","shortname":"spp96","description":"Pattern 96 for Stochastically Perturbed Parametrisation (SPP) scheme.\r\n\r\nThese fields are for internal use by ECMWF and will not be disseminated.\r\nThe SPP fields as well as the SPPT fields are required by the perturbed ensemble members to propagate information about the state of the model uncertainty scheme from one model integration to another","unit_id":23,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":213197,"name":"Random pattern 97 for SPP scheme","shortname":"spp97","description":"Pattern 97 for Stochastically Perturbed Parametrisation (SPP) scheme.\r\n\r\nThese fields are for internal use by ECMWF and will not be disseminated.\r\nThe SPP fields as well as the SPPT fields are required by the perturbed ensemble members to propagate information about the state of the model uncertainty scheme from one model integration to another","unit_id":23,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":213198,"name":"Random pattern 98 for SPP scheme","shortname":"spp98","description":"Pattern 98 for Stochastically Perturbed Parametrisation (SPP) scheme.\r\n\r\nThese fields are for internal use by ECMWF and will not be disseminated.\r\nThe SPP fields as well as the SPPT fields are required by the perturbed ensemble members to propagate information about the state of the model uncertainty scheme from one model integration to another","unit_id":23,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":213199,"name":"Random pattern 99 for SPP scheme","shortname":"spp99","description":"Pattern 99 for Stochastically Perturbed Parametrisation (SPP) scheme.\r\n\r\nThese fields are for internal use by ECMWF and will not be disseminated.\r\nThe SPP fields as well as the SPPT fields are required by the perturbed ensemble members to propagate information about the state of the model uncertainty scheme from one model integration to another","unit_id":23,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":213200,"name":"Random pattern 100 for SPP scheme","shortname":"spp100","description":"Pattern 100 for Stochastically Perturbed Parametrisation (SPP) scheme.\r\n\r\nThese fields are for internal use by ECMWF and will not be disseminated.\r\nThe SPP fields as well as the SPPT fields are required by the perturbed ensemble members to propagate information about the state of the model uncertainty scheme from one model integration to another","unit_id":23,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":213201,"name":"Random pattern 101 for SPP scheme","shortname":"spp101","description":"Pattern 101 for Stochastically Perturbed Parametrisation (SPP) scheme.\r\n\r\nThese fields are for internal use by ECMWF and will not be disseminated.\r\nThe SPP fields as well as the SPPT fields are required by the perturbed ensemble members to propagate information about the state of the model uncertainty scheme from one model integration to another","unit_id":23,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":213202,"name":"Random pattern 102 for SPP scheme","shortname":"spp102","description":"Pattern 102 for Stochastically Perturbed Parametrisation (SPP) scheme.\r\n\r\nThese fields are for internal use by ECMWF and will not be disseminated.\r\nThe SPP fields as well as the SPPT fields are required by the perturbed ensemble members to propagate information about the state of the model uncertainty scheme from one model integration to another","unit_id":23,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":213203,"name":"Random pattern 103 for SPP scheme","shortname":"spp103","description":"Pattern 103 for Stochastically Perturbed Parametrisation (SPP) scheme.\r\n\r\nThese fields are for internal use by ECMWF and will not be disseminated.\r\nThe SPP fields as well as the SPPT fields are required by the perturbed ensemble members to propagate information about the state of the model uncertainty scheme from one model integration to another","unit_id":23,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":213204,"name":"Random pattern 104 for SPP scheme","shortname":"spp104","description":"Pattern 104 for Stochastically Perturbed Parametrisation (SPP) scheme.\r\n\r\nThese fields are for internal use by ECMWF and will not be disseminated.\r\nThe SPP fields as well as the SPPT fields are required by the perturbed ensemble members to propagate information about the state of the model uncertainty scheme from one model integration to another","unit_id":23,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":213205,"name":"Random pattern 105 for SPP scheme","shortname":"spp105","description":"Pattern 105 for Stochastically Perturbed Parametrisation (SPP) scheme.\r\n\r\nThese fields are for internal use by ECMWF and will not be disseminated.\r\nThe SPP fields as well as the SPPT fields are required by the perturbed ensemble members to propagate information about the state of the model uncertainty scheme from one model integration to another","unit_id":23,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":213206,"name":"Random pattern 106 for SPP scheme","shortname":"spp106","description":"Pattern 106 for Stochastically Perturbed Parametrisation (SPP) scheme.\r\n\r\nThese fields are for internal use by ECMWF and will not be disseminated.\r\nThe SPP fields as well as the SPPT fields are required by the perturbed ensemble members to propagate information about the state of the model uncertainty scheme from one model integration to another","unit_id":23,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":213207,"name":"Random pattern 107 for SPP scheme","shortname":"spp107","description":"Pattern 107 for Stochastically Perturbed Parametrisation (SPP) scheme.\r\n\r\nThese fields are for internal use by ECMWF and will not be disseminated.\r\nThe SPP fields as well as the SPPT fields are required by the perturbed ensemble members to propagate information about the state of the model uncertainty scheme from one model integration to another","unit_id":23,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":213208,"name":"Random pattern 108 for SPP scheme","shortname":"spp108","description":"Pattern 108 for Stochastically Perturbed Parametrisation (SPP) scheme.\r\n\r\nThese fields are for internal use by ECMWF and will not be disseminated.\r\nThe SPP fields as well as the SPPT fields are required by the perturbed ensemble members to propagate information about the state of the model uncertainty scheme from one model integration to another","unit_id":23,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":213209,"name":"Random pattern 109 for SPP scheme","shortname":"spp109","description":"Pattern 109 for Stochastically Perturbed Parametrisation (SPP) scheme.\r\n\r\nThese fields are for internal use by ECMWF and will not be disseminated.\r\nThe SPP fields as well as the SPPT fields are required by the perturbed ensemble members to propagate information about the state of the model uncertainty scheme from one model integration to another","unit_id":23,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":213210,"name":"Random pattern 110 for SPP scheme","shortname":"spp110","description":"Pattern 110 for Stochastically Perturbed Parametrisation (SPP) scheme.\r\n\r\nThese fields are for internal use by ECMWF and will not be disseminated.\r\nThe SPP fields as well as the SPPT fields are required by the perturbed ensemble members to propagate information about the state of the model uncertainty scheme from one model integration to another","unit_id":23,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":213211,"name":"Random pattern 111 for SPP scheme","shortname":"spp111","description":"Pattern 111 for Stochastically Perturbed Parametrisation (SPP) scheme.\r\n\r\nThese fields are for internal use by ECMWF and will not be disseminated.\r\nThe SPP fields as well as the SPPT fields are required by the perturbed ensemble members to propagate information about the state of the model uncertainty scheme from one model integration to another","unit_id":23,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":213212,"name":"Random pattern 112 for SPP scheme","shortname":"spp112","description":"Pattern 112 for Stochastically Perturbed Parametrisation (SPP) scheme.\r\n\r\nThese fields are for internal use by ECMWF and will not be disseminated.\r\nThe SPP fields as well as the SPPT fields are required by the perturbed ensemble members to propagate information about the state of the model uncertainty scheme from one model integration to another","unit_id":23,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":213213,"name":"Random pattern 113 for SPP scheme","shortname":"spp113","description":"Pattern 113 for Stochastically Perturbed Parametrisation (SPP) scheme.\r\n\r\nThese fields are for internal use by ECMWF and will not be disseminated.\r\nThe SPP fields as well as the SPPT fields are required by the perturbed ensemble members to propagate information about the state of the model uncertainty scheme from one model integration to another","unit_id":23,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":213214,"name":"Random pattern 114 for SPP scheme","shortname":"spp114","description":"Pattern 114 for Stochastically Perturbed Parametrisation (SPP) scheme.\r\n\r\nThese fields are for internal use by ECMWF and will not be disseminated.\r\nThe SPP fields as well as the SPPT fields are required by the perturbed ensemble members to propagate information about the state of the model uncertainty scheme from one model integration to another","unit_id":23,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":213215,"name":"Random pattern 115 for SPP scheme","shortname":"spp115","description":"Pattern 115 for Stochastically Perturbed Parametrisation (SPP) scheme.\r\n\r\nThese fields are for internal use by ECMWF and will not be disseminated.\r\nThe SPP fields as well as the SPPT fields are required by the perturbed ensemble members to propagate information about the state of the model uncertainty scheme from one model integration to another","unit_id":23,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":213216,"name":"Random pattern 116 for SPP scheme","shortname":"spp116","description":"Pattern 116 for Stochastically Perturbed Parametrisation (SPP) scheme.\r\n\r\nThese fields are for internal use by ECMWF and will not be disseminated.\r\nThe SPP fields as well as the SPPT fields are required by the perturbed ensemble members to propagate information about the state of the model uncertainty scheme from one model integration to another","unit_id":23,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":213217,"name":"Random pattern 117 for SPP scheme","shortname":"spp117","description":"Pattern 117 for Stochastically Perturbed Parametrisation (SPP) scheme.\r\n\r\nThese fields are for internal use by ECMWF and will not be disseminated.\r\nThe SPP fields as well as the SPPT fields are required by the perturbed ensemble members to propagate information about the state of the model uncertainty scheme from one model integration to another","unit_id":23,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":213218,"name":"Random pattern 118 for SPP scheme","shortname":"spp118","description":"Pattern 118 for Stochastically Perturbed Parametrisation (SPP) scheme.\r\n\r\nThese fields are for internal use by ECMWF and will not be disseminated.\r\nThe SPP fields as well as the SPPT fields are required by the perturbed ensemble members to propagate information about the state of the model uncertainty scheme from one model integration to another","unit_id":23,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":213219,"name":"Random pattern 119 for SPP scheme","shortname":"spp119","description":"Pattern 119 for Stochastically Perturbed Parametrisation (SPP) scheme.\r\n\r\nThese fields are for internal use by ECMWF and will not be disseminated.\r\nThe SPP fields as well as the SPPT fields are required by the perturbed ensemble members to propagate information about the state of the model uncertainty scheme from one model integration to another","unit_id":23,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":213220,"name":"Random pattern 120 for SPP scheme","shortname":"spp120","description":"Pattern 120 for Stochastically Perturbed Parametrisation (SPP) scheme.\r\n\r\nThese fields are for internal use by ECMWF and will not be disseminated.\r\nThe SPP fields as well as the SPPT fields are required by the perturbed ensemble members to propagate information about the state of the model uncertainty scheme from one model integration to another","unit_id":23,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":213221,"name":"Random pattern 121 for SPP scheme","shortname":"spp121","description":"Pattern 121 for Stochastically Perturbed Parametrisation (SPP) scheme.\r\n\r\nThese fields are for internal use by ECMWF and will not be disseminated.\r\nThe SPP fields as well as the SPPT fields are required by the perturbed ensemble members to propagate information about the state of the model uncertainty scheme from one model integration to another","unit_id":23,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":214001,"name":"Cosine of solar zenith 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Ammonium","shortname":"acc_wet_depm_NH4","description":null,"unit_id":22,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":223022,"name":"Time-integrated wet deposition mass flux of Methane sulfonic acid","shortname":"acc_wet_depm_MSA","description":null,"unit_id":22,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":223023,"name":"Time-integrated wet deposition mass flux of Methyl glyoxal","shortname":"acc_wet_depm_CH3COCHO","description":null,"unit_id":22,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":223025,"name":"Time-integrated wet deposition mass flux of Carbon monoxide","shortname":"acc_wet_depm_CO","description":null,"unit_id":22,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":223026,"name":"Time-integrated wet deposition mass flux of Lead","shortname":"acc_wet_depm_Pb","description":null,"unit_id":22,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":223027,"name":"Time-integrated wet deposition mass flux of Nitrogen monoxide","shortname":"acc_wet_depm_NO","description":null,"unit_id":22,"encoding_ids":["grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":223028,"name":"Time-integrated wet deposition mass flux of Hydroperoxy radical","shortname":"acc_wet_depm_HO2","description":null,"unit_id":22,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":223029,"name":"Time-integrated wet deposition mass flux of Methylperoxy radical","shortname":"acc_wet_depm_CH3O2","description":null,"unit_id":22,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":223031,"name":"Time-integrated wet deposition mass flux of Nitrogen dioxide","shortname":"acc_wet_depm_NO2","description":null,"unit_id":22,"encoding_ids":["grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":223032,"name":"Time-integrated wet deposition mass flux of Nitrate radical","shortname":"acc_wet_depm_NO3","description":null,"unit_id":22,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":223033,"name":"Time-integrated wet deposition mass flux of Dinitrogen pentoxide","shortname":"acc_wet_depm_N2O5","description":null,"unit_id":22,"encoding_ids":["grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":223034,"name":"Time-integrated wet deposition mass flux of Pernitric acid","shortname":"acc_wet_depm_HO2NO2","description":null,"unit_id":22,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":223042,"name":"Time-integrated wet deposition mass flux of Methanol","shortname":"acc_wet_depm_CH3OH","description":null,"unit_id":22,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":223043,"name":"Time-integrated wet deposition mass flux of Formic acid","shortname":"acc_wet_depm_HCOOH","description":null,"unit_id":22,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":223044,"name":"Time-integrated wet deposition mass flux of Methacrylic acid","shortname":"acc_wet_depm_MCOOH","description":null,"unit_id":22,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":223045,"name":"Time-integrated wet deposition mass flux of Ethane","shortname":"acc_wet_depm_C2H6","description":null,"unit_id":22,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":223046,"name":"Time-integrated wet deposition mass flux of Ethanol","shortname":"acc_wet_depm_C2H5OH","description":null,"unit_id":22,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":223050,"name":"Time-integrated wet deposition mass flux of Methacrolein","shortname":"acc_wet_depm_ISPD","description":null,"unit_id":22,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":223051,"name":"Time-integrated wet deposition mass flux of Nitrate","shortname":"acc_wet_depm_NO3_A","description":null,"unit_id":22,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":223052,"name":"Time-integrated wet deposition mass flux of Acetone","shortname":"acc_wet_depm_CH3COCH3","description":null,"unit_id":22,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":223064,"name":"Time-integrated wet deposition mass flux of Chlorine nitrate","shortname":"acc_wet_depm_CLONO2","description":null,"unit_id":22,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":223065,"name":"Time-integrated wet deposition mass flux of Hypochlorous acid","shortname":"acc_wet_depm_HOCL","description":null,"unit_id":22,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":223068,"name":"Time-integrated wet deposition mass flux of Hydrogen bromide","shortname":"acc_wet_depm_HBR","description":null,"unit_id":22,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":223070,"name":"Time-integrated wet deposition mass flux of Hypobromous acid","shortname":"acc_wet_depm_HOBR","description":null,"unit_id":22,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":223086,"name":"Time-integrated wet deposition mass flux of Nitrous acid","shortname":"acc_wet_depm_HONO","description":null,"unit_id":22,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":223099,"name":"Time-integrated wet deposition mass flux of Toluene and less reactive aromatics","shortname":"acc_wet_depm_TOL","description":null,"unit_id":22,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":223100,"name":"Time-integrated wet deposition mass flux of Xylene and more reactive aromatics","shortname":"acc_wet_depm_XYL","description":null,"unit_id":22,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":223101,"name":"Time-integrated wet deposition mass flux of Glycolaldehyde","shortname":"acc_wet_depm_GLYALD","description":null,"unit_id":22,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":223107,"name":"Time-integrated wet deposition mass flux of Glyoxal","shortname":"acc_wet_depm_GLY","description":null,"unit_id":22,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":223118,"name":"Time-integrated wet deposition mass flux of Hydroxyacetone","shortname":"acc_wet_depm_HYAC","description":null,"unit_id":22,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":223161,"name":"Time-integrated wet deposition mass flux of all hydroxy-peroxides products of the reaction of hydroxy-isoprene adducts with O2","shortname":"acc_wet_depm_ISOPOOH","description":null,"unit_id":22,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":223186,"name":"Time-integrated wet deposition mass flux of Condensable gas type 1","shortname":"acc_wet_depm_SOG1","description":null,"unit_id":22,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":223187,"name":"Time-integrated wet deposition mass flux of Condensable gas type 2a","shortname":"acc_wet_depm_SOG2A","description":null,"unit_id":22,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":223188,"name":"Time-integrated wet deposition mass flux of Condensable gas type 2b","shortname":"acc_wet_depm_SOG2B","description":null,"unit_id":22,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":223194,"name":"Time-integrated wet deposition mass flux of Bromine nitrate","shortname":"acc_wet_depm_BRONO2","description":null,"unit_id":22,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":223200,"name":"Time-integrated wet deposition mass flux of Hydrogen chloride","shortname":"acc_wet_depm_HCL","description":null,"unit_id":22,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":223224,"name":"Time-integrated wet deposition mass flux of Acetonitrile","shortname":"acc_wet_depm_CH3CN","description":null,"unit_id":22,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":223226,"name":"Time-integrated wet deposition mass flux of Hydrogen cyanide","shortname":"acc_wet_depm_HCN","description":null,"unit_id":22,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":223227,"name":"Time-integrated wet deposition mass flux of Hydroperoxy aldehydes type 1","shortname":"acc_wet_depm_HPALD1","description":null,"unit_id":22,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":223228,"name":"Time-integrated wet deposition mass flux of Hydroperoxy aldehydes type 2","shortname":"acc_wet_depm_HPALD2","description":null,"unit_id":22,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":228001,"name":"Convective inhibition","shortname":"cin","description":"This parameter is a measure of the amount of energy required for convection to commence. If the value of this parameter is too high, then deep, moist convection is unlikely to occur even if the convective available potential energy or convective available potential energy shear are large. CIN values greater than 200 J kg-1 would be considered high.
An atmospheric layer where temperature increases with height (known as a temperature inversion) would inhibit convective uplift and is a situation in which convective inhibition would be large.","unit_id":17,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":228002,"name":"Orography","shortname":"orog","description":null,"unit_id":4,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":228003,"name":"Friction velocity","shortname":"zust","description":"Air flowing over a surface exerts a stress that transfers momentum to the surface and slows the wind. This parameter is a theoretical wind speed at the Earth's surface that expresses the magnitude of stress. It is calculated by dividing the surface stress by air density and taking its square root. For turbulent flow, the friction velocity is approximately constant in the lowest few metres of the atmosphere.
This parameter increases with the roughness of the surface. It is used to calculate the way wind changes with height in the lowest levels of the atmosphere.","unit_id":5,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":228004,"name":"Time-mean 2 metre temperature","shortname":"avg_2t","description":null,"unit_id":2,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":228005,"name":"Time-mean 10 metre wind speed","shortname":"avg_10ws","description":null,"unit_id":5,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":228006,"name":"Mean total cloud cover","shortname":"meantcc","description":null,"unit_id":3,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":228007,"name":"Lake total depth","shortname":"dl","description":"This parameter is the mean depth of inland water bodies (lakes, reservoirs and rivers) and coastal waters. This field is specified from in-situ measurements and indirect estimates and is constant in time.
ECMWF implemented a lake model in May 2015 to represent the water temperature and lake ice of all the world's major inland water bodies in the Integrated Forecasting System (IFS). The IFS differentiates between (i) ocean water, handled by the ocean model, and (ii) inland water (lakes, reservoirs and rivers) and coastal waters handled by the lake parametrisation. Lake depth and surface area (or fractional cover) are kept constant in time.","unit_id":4,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":228008,"name":"Lake mix-layer temperature","shortname":"lmlt","description":"This parameter is the temperature of the uppermost layer of inland water bodies (lakes, reservoirs and rivers) or coastal waters, that is well mixed and has a near constant temperature with depth (i.e., a uniform distribution of temperature with depth).
The ECMWF Integrated Forecasting System represents inland water bodies and coastal waters with two layers in the vertical, the mixed layer above and the thermocline below. The upper boundary of the thermocline is located at the mixed layer bottom, and the lower boundary of the thermocline at the lake bottom.
Mixing within the mixed layer can occur when the density of the surface (and near-surface) water is greater than that of the water below. Mixing can also occur through the action of wind on the surface of the lake.
This parameter has units of kelvin (K). Temperature measured in kelvin can be converted to degrees Celsius (°C) by subtracting 273.15.
ECMWF implemented a lake model in May 2015 to represent the water temperature and lake ice of all the world's major inland water bodies in the Integrated Forecasting System (IFS). The IFS differentiates between (i) ocean water, handled by the ocean model, and (ii) inland water (lakes, reservoirs and rivers) and coastal waters handled by the lake parametrisation. Lake depth and surface area (or fractional cover) are kept constant in time.","unit_id":2,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":228009,"name":"Lake mix-layer depth","shortname":"lmld","description":"This parameter is the thickness of the uppermost layer of inland water bodies (lakes, reservoirs and rivers) or coastal waters, that is well mixed and has a near constant temperature with depth (i.e., a uniform distribution of temperature with depth).
The ECMWF Integrated Forecasting System represents inland water bodies and coastal waters with two layers in the vertical, the mixed layer above and the thermocline below, where temperature changes with depth. The upper boundary of the thermocline is located at the mixed layer bottom, and the lower boundary of the thermocline at the lake bottom.
Mixing within the mixed layer can occur when the density of the surface (and near-surface) water is greater than that of the water below. Mixing can also occur through the action of wind on the surface of the lake.
ECMWF implemented a lake model in May 2015 to represent the water temperature and lake ice of all the world's major inland water bodies in the Integrated Forecasting System (IFS). The IFS differentiates between (i) ocean water, handled by the ocean model, and (ii) inland water (lakes, reservoirs and rivers) and coastal waters handled by the lake parametrisation. Lake depth and surface area (or fractional cover) are kept constant in time.","unit_id":4,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":228010,"name":"Lake bottom temperature","shortname":"lblt","description":"This parameter is the temperature of water at the bottom of inland water bodies (lakes, reservoirs, rivers) and coastal waters.
This parameter has units of kelvin (K). Temperature measured in kelvin can be converted to degrees Celsius (°C) by subtracting 273.15.
ECMWF implemented a lake model in May 2015 to represent the water temperature and lake ice of all the world's major inland water bodies in the Integrated Forecasting System (IFS). The IFS differentiates between (i) ocean water, handled by the ocean model, and (ii) inland water (lakes, reservoirs and rivers) and coastal waters handled by the lake parametrisation. Lake depth and surface area (or fractional cover) are kept constant in time.","unit_id":2,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":228011,"name":"Lake total layer temperature","shortname":"ltlt","description":"This parameter is the mean temperature of the total water column in inland water bodies (lakes, reservoirs and rivers) and coastal waters.
The ECMWF Integrated Forecasting System represents inland water bodies and coastal waters with two layers in the vertical, the mixed layer above and the thermocline below, where temperature changes with depth. This parameter is the mean over the two layers.
The upper boundary of the thermocline is located at the mixed layer bottom, and the lower boundary of the thermocline at the lake bottom.
This parameter has units of kelvin (K). Temperature measured in kelvin can be converted to degrees Celsius (°C) by subtracting 273.15.
ECMWF implemented a lake model in May 2015 to represent the water temperature and lake ice of all the world's major inland water bodies in the Integrated Forecasting System (IFS). The IFS differentiates between (i) ocean water, handled by the ocean model, and (ii) inland water (lakes, reservoirs and rivers) and coastal waters handled by the lake parametrisation. Lake depth and surface area (or fractional cover) are kept constant in time.","unit_id":2,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":228012,"name":"Lake shape factor","shortname":"lshf","description":"This parameter describes the way that temperature changes with depth in the thermocline layer of inland water bodies (lakes, reservoirs and rivers) and coastal waters (i.e., it describes the shape of the vertical temperature profile). It is used to calculate the lake bottom temperature and other lake-related parameters.
The ECMWF Integrated Forecasting System represents inland water bodies and coastal waters with two layers in the vertical, the mixed layer above and the thermocline below, where temperature changes with depth. The upper boundary of the thermocline is located at the mixed layer bottom, and the lower boundary of the thermocline at the lake bottom.
ECMWF implemented a lake model in May 2015 to represent the water temperature and lake ice of all the world's major inland water bodies in the Integrated Forecasting System (IFS). The IFS differentiates between (i) ocean water, handled by the ocean model, and (ii) inland water (lakes, reservoirs and rivers) and coastal waters handled by the lake parametrisation. Lake depth and surface area (or fractional cover) are kept constant in time.","unit_id":23,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":228013,"name":"Lake ice surface temperature","shortname":"lict","description":"This parameter is the temperature of the uppermost surface of ice on inland water bodies (lakes, reservoirs, and rivers) and coastal waters. That is the temperature at the ice/atmosphere or ice/snow interface.
The ECMWF Integrated Forecasting System represents the formation and melting of ice on lakes. A single ice layer is represented.
This parameter has units of kelvin (K). Temperature measured in kelvin can be converted to degrees Celsius (°C) by subtracting 273.15.
ECMWF implemented a lake model in May 2015 to represent the water temperature and lake ice of all the world's major inland water bodies in the Integrated Forecasting System (IFS). The IFS differentiates between (i) ocean water, handled by the ocean model, and (ii) inland water (lakes, reservoirs and rivers) and coastal waters handled by the lake parametrisation. Lake depth and surface area (or fractional cover) are kept constant in time.","unit_id":2,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":228014,"name":"Lake ice total depth","shortname":"licd","description":"This parameter is the thickness of ice on inland water bodies (lakes, reservoirs and rivers) and coastal waters.
The ECMWF Integrated Forecasting System represents the formation and melting of ice on inland water bodies. A single ice layer is represented. This parameter is the thickness of that ice layer.
ECMWF implemented a lake model in May 2015 to represent the water temperature and lake ice of all the world's major inland water bodies in the Integrated Forecasting System (IFS). The IFS differentiates between (i) ocean water, handled by the ocean model, and (ii) inland water (lakes, reservoirs and rivers) and coastal waters handled by the lake parametrisation. Lake depth and surface area (or fractional cover) are kept constant in time.","unit_id":4,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":228015,"name":"Minimum vertical gradient of refractivity inside trapping layer","shortname":"dndzn","description":"Minimum vertical gradient of atmospheric refractivity inside trapping layer. A duct layer is an atmospheric layer with a refractivity which leads to a trapping of electromagnetic waves. In a trapping layer the refractivity leads to a bending of EM waves, which is stronger than the earth's curvature.","unit_id":86,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":228016,"name":"Mean vertical gradient of refractivity inside trapping layer","shortname":"dndza","description":"Minimum vertical gradient of atmospheric refractivity\r\ninside trapping layer. A duct layer is an atmospheric layer with a refractivity which leads to a trapping of electromagnetic waves. In a trapping layer the refractivity leads to a bending of EM waves, which is stronger than the earth's curvature.","unit_id":86,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":228017,"name":"Duct base height","shortname":"dctb","description":"Duct base height as diagnosed from vertical gradient of atmospheric refractivity. A duct layer is an atmospheric layer with a refractivity which leads to a trapping of electromagnetic waves. In a trapping layer the refractivity leads to a bending of EM waves, which is stronger than the earth's curvature.","unit_id":4,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":228018,"name":"Trapping layer base height","shortname":"tplb","description":"Trapping layer base height as diagnosed from vertical\r\ngradient of atmospheric refractivity. A duct layer is an atmospheric layer with a refractivity which leads to a trapping of electromagnetic waves. In a trapping layer the refractivity leads to a bending of EM waves, which is stronger than the earth's curvature.","unit_id":4,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":228019,"name":"Trapping layer top height","shortname":"tplt","description":"Trapping layer top height as diagnosed from vertical\r\ngradient of atmospheric refractivity. A duct layer is an atmospheric layer with a refractivity which leads to a trapping of electromagnetic waves. In a trapping layer the refractivity leads to a bending of EM waves, which is stronger than the earth's curvature.","unit_id":4,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":228020,"name":"Geometric height of -10 degrees C atmospheric isothermal level above ground","shortname":"degm10l","description":"The height above the Earth's surface where the temperature crosses the -10 degree isotherm. If more than one crossing is encountered, then the -10 degree level corresponds to the top of the second atmospheric layer.\r\nThis parameter is set to zero when the temperature in the whole atmosphere is below -10 degrees C.","unit_id":4,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":228021,"name":"Surface direct short-wave (solar) radiation","shortname":"fdir","description":"
This parameter is the amount of direct solar radiation (also known as shortwave radiation) reaching the surface of the Earth. It is the amount of radiation passing through a horizontal plane, not a plane perpendicular to the direction of the Sun.
Solar radiation at the surface can be direct or diffuse. Solar radiation can be scattered in all directions by particles in the atmosphere, some of which reaches the surface (diffuse solar radiation). Some solar radiation reaches the surface without being scattered (direct solar radiation). See further documentation.
This parameter is accumulated over a particular time period which depends on the data extracted. The units are joules per square metre (J m-2). To convert to watts per square metre (W m-2), the accumulated values should be divided by the accumulation period expressed in seconds.
The ECMWF convention for vertical fluxes is positive downwards.
","unit_id":6,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":228022,"name":"Surface direct short-wave radiation, clear sky","shortname":"cdir","description":"This parameter is the amount of direct radiation from the Sun (also known as solar or shortwave radiation) reaching the surface of the Earth, assuming clear-sky (cloudless) conditions. It is the amount of radiation passing through a horizontal plane, not a plane perpendicular to the direction of the Sun.
Solar radiation at the surface can be direct or diffuse. Solar radiation can be scattered in all directions by particles in the atmosphere, some of which reaches the surface (diffuse solar radiation). Some solar radiation reaches the surface without being scattered (direct solar radiation). See further documentation.
Clear-sky radiation quantities are computed for exactly the same atmospheric conditions of temperature, humidity, ozone, trace gases and aerosol as the corresponding total-sky quantities (clouds included), but assuming that the clouds are not there.
This parameter is accumulated over a particular time period which depends on the data extracted. The units are joules per square metre (J m-2). To convert to watts per square metre (W m-2), the accumulated values should be divided by the accumulation period expressed in seconds.
The ECMWF convention for vertical fluxes is positive downwards.","unit_id":6,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":228023,"name":"Cloud base height","shortname":"cbh","description":"The height above the Earth's surface of the base of the lowest cloud layer, at the specified time.
This parameter is calculated by searching from the second lowest model level upwards, to the height of the level where cloud fraction becomes greater than 1% and condensate content greater than 1.E-6 kg kg-1. Fog (i.e., cloud in the lowest model layer) is not considered when defining cloud base height.","unit_id":4,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":228024,"name":"Geometric height of 0 degrees C atmospheric isothermal level above ground","shortname":"deg0l","description":"The height above the Earth's surface where the temperature passes from positive to negative values, corresponding to the top of a warm layer, at the specified time. This parameter can be used to help forecast snow.
If more than one warm layer is encountered, then the zero degree level corresponds to the top of the second atmospheric layer.
This parameter is set to zero when the temperature in the whole atmosphere is below 0℃.","unit_id":4,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":228025,"name":"Horizontal visibility","shortname":"hvis","description":"","unit_id":4,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":228026,"name":"Maximum temperature at 2 metres in the last 3 hours","shortname":"mx2t3","description":"The highest value of 2 metre temperature in the previous 3 hour period.
2m temperature is calculated by interpolating between the lowest model level and the Earth's surface, taking account of the atmospheric conditions. See further information .
This parameter has units of kelvin (K). Temperature measured in kelvin can be converted to degrees Celsius (°C) by subtracting 273.15.","unit_id":2,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":228027,"name":"Minimum temperature at 2 metres in the last 3 hours","shortname":"mn2t3","description":"The lowest value of 2 metre temperature in the previous 3 hour period.
2m temperature is calculated by interpolating between the lowest model level and the Earth's surface, taking account of the atmospheric conditions. See further information.
This parameter has units of kelvin (K). Temperature measured in kelvin can be converted to degrees Celsius (°C) by subtracting 273.15.","unit_id":2,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":228028,"name":"Maximum 10 metre wind gust in the last 3 hours","shortname":"10fg3","description":"This parameter is the maximum wind gust in the last 3 hours at a height of ten metres above the surface of the Earth.
The WMO defines a wind gust as the maximum of the wind averaged over 3 second intervals. This duration is shorter than a model time step, and so the ECMWF Integrated Forecasting System deduces the magnitude of a gust within each time step from the time-step-averaged surface stress, surface friction, wind shear and stability. Then, the maximum wind gust is selected from the gusts at each time step during the last 3 hours.
Care should be taken when comparing model parameters with observations, because observations are often local to a particular point in space and time, rather than representing averages over a model grid box and model time step.","unit_id":5,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":228029,"name":"Instantaneous 10 metre wind gust","shortname":"i10fg","description":"This parameter is the maximum wind gust at the specified time, at a height of ten metres above the surface of the Earth.
The WMO defines a wind gust as the maximum of the wind averaged over 3 second intervals. This duration is shorter than a model time step , and so the ECMWF Integrated Forecasting System deduces the magnitude of a gust within each time step from the time-step-averaged surface stress, surface friction, wind shear and stability.
Care should be taken when comparing model parameters with observations, because observations are often local to a particular point in space and time, rather than representing averages over a model grid box and model time step.","unit_id":5,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":228030,"name":"Relative humidity with respect to water","shortname":"rhw","description":"The relative humidity with respect to water of moist air at pressure p and temperature T is the ratio in per cent of the vapour mole fraction xv to the vapour mole fraction xvw which the air would have if it were saturated with respect to water at the same pressure p and temperature T","unit_id":29,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":228031,"name":"Relative humidity with respect to ice","shortname":"rhi","description":"The relative humidity with respect to ice of moist air at pressure p and temperature T is the ratio in per cent of the vapour mole fraction xv to the vapour mole fraction xvi which the air would have if it were saturated with respect to ice at the same pressure p and temperature T","unit_id":29,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":228032,"name":"Snow albedo","shortname":"asn","description":"The broadband albedo of snow.\n [NOTE: See 32 for the equivalent parameter in \"(0-1)\"]","unit_id":29,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":228034,"name":"Fraction of convective precipitation cover","shortname":"fcpc","description":"Horizontal fraction of the grid box covered by convective precipitation","unit_id":105,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":228035,"name":"Maximum CAPE in the last 6 hours","shortname":"mxcape6","description":"
From 48r1 this parameter is based on most unstable CAPE rather than the previously used surface based CAPE.
The maximum CAPE (convective available potential energy) value that has occurred over the last 6 hours.
CAPE is an indication of the instability (or stability) of the atmosphere and can be used to assess the potential for the development of deep convection. When air rises through a large depth of the atmosphere, extensive condensation can occur and heavy rainfall, thunderstorms and other severe weather can result.
Care should be taken when comparing model parameters with observations, because observations are often local to a particular point in space and time, rather than representing averages over a model grid box and model time step.
","unit_id":17,"encoding_ids":["grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":228036,"name":"Maximum CAPES in the last 6 hours","shortname":"mxcapes6","description":"
From 48r1 this parameter is based on most unstable CAPE rather than the previously used surface based CAPE.
The maximum CAPES (convective available potential energy shear) value that has occurred over the last 6 hours.
High values of CAPES indicate where deep, organised convection is more likely to occur, if it is initiated. When air rises through a large depth of the atmosphere, extensive condensation can occur and heavy rainfall, thunderstorms and other severe weather can result.
Care should be taken when comparing model parameters with observations, because observations are often local to a particular point in space and time, rather than representing averages over a model grid box and model time step.
","unit_id":15,"encoding_ids":["grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":228037,"name":"2 metre relative humidity with respect to water","shortname":"2rhw","description":"See 228030","unit_id":29,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":228038,"name":"Liquid water content in snow pack","shortname":"lwcs","description":"This parameter represent the liquid water content in snow pack, i.e. the amount of water in its liquid form (not frozen/snowflake/etc). This is an indicator of how \"wet\" the snow is.","unit_id":22,"encoding_ids":["grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":228039,"name":"Soil moisture","shortname":"sm","description":"
This GRIB2 encoding is only to be used in TIGGE as it is WMO deprecated. Please use paramId 260368 otherwise.
","unit_id":9,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":228040,"name":"Soil wetness index in layer 1","shortname":"swi1","description":"","unit_id":23,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":228041,"name":"Soil wetness index in layer 2","shortname":"swi2","description":"","unit_id":23,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":228042,"name":"Soil wetness index in layer 3","shortname":"swi3","description":"","unit_id":23,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":228043,"name":"Soil wetness index in layer 4","shortname":"swi4","description":"","unit_id":23,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":228044,"name":"Convective available potential energy shear","shortname":"capes","description":"
From 48r1 this parameter is based on most unstable CAPE rather than the previously used surface based CAPE.
High values of this parameter indicate where deep, organised convection is more likely to occur, if it is initiated. When air rises through a large depth of the atmosphere, extensive condensation can occur and heavy rainfall, thunderstorms and other severe weather can result.
The likelihood of severe weather and its level of intensity tend to increase with increasing organisation of convection. Convective supercells are the most prominent example. Such organised areas of convection tend to occur where wind (intensity and/or direction) changes rapidly with height i.e., areas with strong vertical wind shear.
This parameter is the product of wind shear and the square root of convective available potential energy (CAPE). The wind shear denotes bulk shear which is a vector difference of winds at two different heights in the atmosphere (925 hPa and 500 hPa). The square root of CAPE is proportional to the maximum vertical velocity in convective updraughts.
To help determine whether deep, moist convection will be initiated or not, the probability forecast for precipitation (for example) can be used, in conjunction with this parameter.
","unit_id":15,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":228045,"name":"Tropopause pressure","shortname":"trpp","description":"This parameter uses a stability-based definition of the tropopause. The use of this parameter is recommended for the tropical belt (typically +-30 degrees). Outside of this belt the pressure of the surface PV=2 (Potential Vorticity = 2 PV units) provides a more appropriate measure of the tropopause height.","unit_id":16,"encoding_ids":["grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":228046,"name":"Height of convective cloud top","shortname":"hcct","description":"The height above the Earth's surface of the top of convective cloud produced by the ECMWF Integrated Forecasting System convection scheme, at the specified time. The convection scheme represents convection at spatial scales smaller than the grid box. See further information.","unit_id":4,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":228047,"name":"Height of zero-degree wet-bulb temperature","shortname":"hwbt0","description":"The height above the Earth's surface where the wet-bulb temperature drops to 0℃, at the specified time. This parameter can be used to help forecast snow.
The wet-bulb temperature is the temperature to which the air must drop to become saturated with moisture (keeping pressure constant and accounting only for latent heat). It can also be defined as the temperature recorded by a thermometer with its bulb covered by a wet cloth or wick. The greater the difference between the dry-bulb and wet-bulb temperature, the lower the humidity.
This parameter is set to zero when the wet bulb temperature in the whole atmosphere is below 0℃.\r\n\r\nSee here for further information.","unit_id":4,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":228048,"name":"Height of one-degree wet-bulb temperature","shortname":"hwbt1","description":"The height above the Earth's surface where the wet-bulb temperature drops to 1℃, at the specified time. This parameter can be used to help forecast snow.
The wet-bulb temperature is the temperature to which the air must drop to become saturated with moisture (keeping pressure constant and accounting only for latent heat). It can also be defined as the temperature recorded by a thermometer with its bulb covered by a wet cloth or wick. The greater the difference between the dry-bulb and wet-bulb temperature, the lower the humidity.
This parameter is set to zero when the wet bulb temperature in the whole atmosphere is below 1℃.\r\n\r\nSee here for further information.","unit_id":4,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":228050,"name":"Instantaneous total lightning flash density","shortname":"litoti","description":"This parameter gives the total lightning flash rate at the specified time. Users should be aware that it is prone to large errors, e.g. due to any spatial and temporal discrepancies between model convection and observed convection.
Note that this parameter has units of flashes per square kilometre per day. Conversion of this parameter to units of flashes per 100 square kilometres per hour can give values that are easier to interpret.
This parameter accounts for cloud-to-ground flashes (between the the cloud and the Earth's surface) and intra-cloud flashes (between two cloud regions of opposite electric charge). In the ECMWF Integrated Forecasting System, the total lightning flash density is calculated using an empirical formula involving convective cloud and precipitation information, convective available potential energy (CAPE) and convective cloud base height, which are diagnosed by the convection scheme. ","unit_id":107,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":228051,"name":"Averaged total lightning flash density in the last hour","shortname":"litota1","description":"Averaged total (cloud-to-cloud and cloud-to-ground) lightning flash density in the last hour.","unit_id":107,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":228052,"name":"Instantaneous cloud-to-ground lightning flash density","shortname":"licgi","description":"Instantaneous value of cloud-to-ground lightning flash density.","unit_id":107,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":228053,"name":"Averaged cloud-to-ground lightning flash density in the last hour","shortname":"licga1","description":"Averaged cloud-to-ground lightning flash density in the last hour.","unit_id":107,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":228054,"name":"Unbalanced component of specific humidity","shortname":"ucq","description":"Unbalanced component of grid-box mean specific humidity.
\nResidual resulting from subtracting from specific humidity (mass of water vapour / mass of moist air) an\napproximate \"balanced\" value derived from relevant variable(s)","unit_id":21,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":228055,"name":"Unbalanced component of specific cloud liquid water content","shortname":"ucclwc","description":"Unbalanced component of grid-box mean specific cloud liquid water content.
\nResidual resulting from subtracting from specific cloud liquid water content (mass of condensate / mass of moist air) an approximate \"balanced\"\nvalue derived from relevant variable(s)","unit_id":21,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":228056,"name":"Unbalanced component of specific cloud ice water content","shortname":"ucciwc","description":"Unbalanced component of grid-box mean specific cloud ice water content.
\nResidual resulting from subtracting from specific cloud ice water content (mass of condensate / mass of moist air)\nan approximate \"balanced\" value derived from relevant variable(s)","unit_id":21,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":228057,"name":"Averaged total lightning flash density in the last 3 hours","shortname":"litota3","description":"This parameter gives the total lightning flash rate averaged over the last 3 hours.
Note that this parameter has units of flashes per square kilometre per day. Conversion of this parameter to units of flashes per 100 square kilometres per hour can give values that are easier to interpret.
This parameter accounts for cloud-to-ground flashes (between the cloud and the Earth's surface ) and intra-cloud flashes (between two cloud regions of opposite electric charge). In the ECMWF Integrated Forecasting System, the total lightning flash density is calculated using an empirical formula involving convective cloud and precipitation information, convective available potential energy (CAPE) and convective cloud base height, which are diagnosed by the convection scheme.","unit_id":107,"encoding_ids":["grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":228058,"name":"Averaged total lightning flash density in the last 6 hours","shortname":"litota6","description":"This parameter gives the total lightning flash rate averaged over the last 6 hours.
Note that this parameter has units of flashes per square kilometre per day. Conversion of this parameter to units of flashes per 100 square kilometres per hour can give values that are easier to interpret.
This parameter accounts for cloud-to-ground flashes (between the cloud and the Earth's surface ) and intra-cloud flashes (between two cloud regions of opposite electric charge). In the ECMWF Integrated Forecasting System, the total lightning flash density is calculated using an empirical formula involving convective cloud and precipitation information, convective available potential energy (CAPE) and convective cloud base height, which are diagnosed by the convection scheme. ","unit_id":107,"encoding_ids":["grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":228059,"name":"Averaged cloud-to-ground lightning flash density in the last 3 hours","shortname":"licga3","description":"Averaged cloud-to-ground lightning flash density in the last 3 hours.","unit_id":107,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":228060,"name":"Averaged cloud-to-ground lightning flash density in the last 6 hours","shortname":"licga6","description":"Averaged cloud-to-ground lightning flash density in the last 6 hours.","unit_id":107,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":228070,"name":"SMOS observed soil moisture retrieved using neural network","shortname":"smnnob","description":"Observed soil moisture retrieved from passive microwave using neural network","unit_id":10,"encoding_ids":["grib1"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":228071,"name":"SMOS observed soil moisture uncertainty retrieved using neural network","shortname":"smnner","description":"Observed soil moisture uncertainty retrieved from passive microwave using neural network","unit_id":10,"encoding_ids":["grib1"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":228072,"name":"SMOS radio frequency interference probability","shortname":"smnnrfi","description":"Frequency Interference probability in the observed passive microwave","unit_id":29,"encoding_ids":["grib1"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":228073,"name":"SMOS number of observations per grid point","shortname":"smnnnb","description":"Number of soil moisture observations per grid point","unit_id":23,"encoding_ids":["grib1"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":228074,"name":"SMOS observation time for the satellite soil moisture data","shortname":"smnntim","description":"Observation time for the satellite soil moisture data","unit_id":217,"encoding_ids":["grib1"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":228078,"name":"GPP coefficient from Biogenic Flux Adjustment System","shortname":"gppbfas","description":"The two parameters \"gppbfas\" and \"recbfas\" are dimensionless re-scaling factors which are applied to the\nCO2 ecosystem fluxes from the Carbon module (CTESSEL) in the IFS:\n
\r\n
gppbfas is applied to the Gross Primary Production (GPP)
\r\n
recbfas is applied to the ecosystem Respiration (Reco)
\n
\r\nThe factors are used in order to reduce the biases of the CO2 ecosystem fluxes which are used in the operational CAMS CO2 forecast/analysis.\r\nThey are currently computed before the beginning of the forecast by comparing the Net Ecosystem Exchange budget of the model (NEE=GPP+Reco) within a 10-day window and a reference climatology (based on optimized fluxes) plus/minus the NEE budget anomaly of the model.\r\nIn the long term, these factors will be adjusted by the data assimilation system using flux and/or atmospheric CO2 observations.","unit_id":23,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":228079,"name":"Rec coefficient from Biogenic Flux Adjustment System","shortname":"recbfas","description":"The two parameters \"gppbfas\" and \"recbfas\" are dimensionless re-scaling factors which are applied to the\nCO2 ecosystem fluxes from the Carbon module (CTESSEL) in the IFS:\n
\n
gppbfas is applied to the Gross Primary Production (GPP)
\n
recbfas is applied to the ecosystem Respiration (Reco)
\n
\nThe factors are used in order to reduce the biases of the CO2 ecosystem fluxes which are used in the operational CAMS CO2 forecast/analysis.\nThey are currently computed before the beginning of the forecast by comparing the Net Ecosystem Exchange budget of the model (NEE=GPP+Reco) within a 10-day window and a reference climatology (based on optimized fluxes) plus/minus the NEE budget anomaly of the model.\nIn the long term, these factors will be adjusted by the data assimilation system using flux and/or atmospheric CO2 observations.","unit_id":23,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":228080,"name":"Accumulated Carbon Dioxide Net Ecosystem Exchange","shortname":"aco2nee","description":"","unit_id":22,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":228081,"name":"Accumulated Carbon Dioxide Gross Primary Production","shortname":"aco2gpp","description":"","unit_id":22,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":228082,"name":"Accumulated Carbon Dioxide Ecosystem Respiration","shortname":"aco2rec","description":"","unit_id":22,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":228083,"name":"Carbon dioxide net ecosystem exchange flux","shortname":"fco2nee","description":"","unit_id":33,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":228084,"name":"Carbon dioxide gross primary production flux","shortname":"fco2gpp","description":"","unit_id":33,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":228085,"name":"Carbon dioxide ecosystem respiration flux","shortname":"fco2rec","description":"","unit_id":33,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":228086,"name":"Soil moisture top 20 cm","shortname":"sm20","description":"
The volumetric soil moisture on the top 20cm of the soil layer
Please note that the encodings listed here for s2s are for Time-mean soil moisture top 20 cm. The specific encoding for Time-mean soil moisture top 20 cm can be found in 235113.
","unit_id":9,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":228087,"name":"Soil moisture top 100 cm","shortname":"sm100","description":"
The volumetric soil moisture on the top 100cm of the soil layer.
Please note that the encodings listed here for s2s are for Time-mean soil moisture top 100 cm. The specific encoding for Time-mean soil moisture top 100 cm can be found in 235114.
","unit_id":9,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":228088,"name":"Total column supercooled liquid water","shortname":"tcslw","description":"This parameter is the total amount of supercooled water in a column extending from the surface of the Earth to the top of the atmosphere. Supercooled water is water that exists in liquid form below 0oC. It is common in cold clouds and is important in the formation of precipitation. Also, supercooled water in clouds extending to the surface (i.e., fog) can cause icing/riming of various structures.
This parameter represents the area averaged value for a grid box.
Clouds contain a continuum of different sized water droplets and ice particles. The ECMWF Integrated Forecasting System (IFS) cloud scheme simplifies this to represent a number of discrete cloud droplets/particles including: cloud water droplets, raindrops, ice crystals and snow (aggregated ice crystals). The processes of droplet formation, conversion and aggregation are also highly simplified in the IFS.","unit_id":22,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":228089,"name":"Total column rain water","shortname":"tcrw","description":"This parameter is the total amount of water in droplets of raindrop size (which can fall to the surface as precipitation) in a column extending from the surface of the Earth to the top of the atmosphere.
This parameter represents the area averaged value for a grid box.
Clouds contain a continuum of different sized water droplets and ice particles. The ECMWF Integrated Forecasting System (IFS) cloud scheme simplifies this to represent a number of discrete cloud droplets/particles including: cloud water droplets, raindrops, ice crystals and snow (aggregated ice crystals). The processes of droplet formation, conversion and aggregation are also highly simplified in the IFS.","unit_id":22,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":228090,"name":"Total column snow water","shortname":"tcsw","description":"This parameter is the total amount of water in the form of snow (aggregated ice crystals which can fall to the surface as precipitation) in a column extending from the surface of the Earth to the top of the atmosphere.
This parameter represents the area averaged value for a grid box.
Clouds contain a continuum of different sized water droplets and ice particles. The ECMWF Integrated Forecasting System (IFS) cloud scheme simplifies this to represent a number of discrete cloud droplets/particles including: cloud water droplets, raindrops, ice crystals and snow (aggregated ice crystals). The processes of droplet formation, conversion and aggregation are also highly simplified in the IFS.","unit_id":22,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":228091,"name":"Canopy cover fraction","shortname":"ccf","description":"","unit_id":3,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":228092,"name":"Soil texture fraction","shortname":"stf","description":"","unit_id":3,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":228093,"name":"Volumetric soil moisture","shortname":"swv","description":"","unit_id":10,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":228094,"name":"Ice temperature","shortname":"ist","description":"","unit_id":2,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":228095,"name":"Soil temperature top 20 cm","shortname":"st20","description":"
The average soil temperature on the top 20cm of the soil layer.
Please note that the encodings listed here for S2S are for Time-mean soil temperature top 20 cm. The specific encoding for Time-mean soil temperature top 20 cm can be found in 235115.
","unit_id":2,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":228096,"name":"Soil temperature top 100 cm","shortname":"st100","description":"
The average soil temperature on the top 100cm of the soil layer
Please note that the encodings listed here for S2S are for Time-mean soil temperature top 100 cm. The specific encoding for Time-mean soil temperature top 100 cm can be found in 235116.
","unit_id":2,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":228100,"name":"Evaporation from the top of canopy","shortname":"evatc","description":"The amount of evaporation from the canopy interception reservoir","unit_id":27,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":228101,"name":"Evaporation from bare soil","shortname":"evabs","description":"The amount of evaporation from bare soil","unit_id":27,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":228102,"name":"Evaporation from open water surfaces excluding oceans","shortname":"evaow","description":"Amount of evaporation from surface water storage like lakes and inundated areas but excluding oceans","unit_id":27,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":228103,"name":"Evaporation from vegetation transpiration","shortname":"evavt","description":"Amount of evaporation from vegetation transpiration. This has the same meaning as root extraction i.e. the amount of water extracted from the different soil layers","unit_id":27,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":228104,"name":"Atmosphere emission mass flux of Methane from Wetlands","shortname":"e_WLCH4","description":null,"unit_id":33,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":228105,"name":"Solar induced Chlorophyll fluorescence at 740nm","shortname":"sif740","description":null,"unit_id":11,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":228106,"name":"Solar induced Chlorophyll fluorescence at 755nm","shortname":"sif755","description":null,"unit_id":11,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":228107,"name":"Solar induced Chlorophyll fluorescence at 771nm","shortname":"sif771","description":null,"unit_id":11,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":228108,"name":"Solar induced Chlorophyll fluorescence at 757nm","shortname":"sif757","description":null,"unit_id":11,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":228109,"name":"Accumulated mass emission of methane from Wetlands","shortname":"acc_e_WLCH4","description":"","unit_id":22,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":228129,"name":"Surface short-wave (solar) radiation downward clear-sky","shortname":"ssrdc","description":"clear-sky downward shortwave radiation flux at surface computed from the model radiation scheme ","unit_id":6,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":228130,"name":"Surface long-wave (thermal) radiation downward clear-sky","shortname":"strdc","description":"clear-sky downward longwave radiation flux at surface computed from the model radiation scheme ","unit_id":6,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":228131,"name":"10 metre u-component of neutral wind","shortname":"u10n","description":"This parameter is the eastward component of the 'neutral wind', at a height of 10 metres above the surface of the Earth.
The neutral wind is calculated from the surface stress and the corresponding roughness length by assuming that the air is neutrally stratified. The neutral wind is slower than the actual wind in stable conditions, and faster in unstable conditions. The neutral wind is, by definition, in the direction of the surface stress. The size of the roughness length depends on land surface properties or the sea state. ","unit_id":5,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":228132,"name":"10 metre v-component of neutral wind","shortname":"v10n","description":"This parameter is the northward component of the 'neutral wind', at a height of 10 metres above the surface of the Earth.
The neutral wind is calculated from the surface stress and the corresponding roughness length by assuming that the air is neutrally stratified. The neutral wind is slower than the actual wind in stable conditions, and faster in unstable conditions. The neutral wind is, by definition, in the direction of the surface stress. The size of the roughness length depends on land surface properties or the sea state. ","unit_id":5,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":228134,"name":"V-tendency from non-orographic wave drag","shortname":"vtnowd","description":null,"unit_id":46,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":228136,"name":"U-tendency from non-orographic wave drag","shortname":"utnowd","description":null,"unit_id":46,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":228139,"name":"Soil temperature","shortname":"st","description":"
This GRIB2 encoding is only to be used in TIGGE as it is WMO deprecated. Please use paramId 260360 otherwise.
","unit_id":2,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":228141,"name":"Snow depth water equivalent","shortname":"sd","description":"
Snow depth water equivalent in kg m**-2 (mm) water equivalent.
Please note that the encodings listed here for s2s & uerra (which includes carra/cerra) include entries for Time-mean snow depth water equivalent. The specific encoding for Time-mean snow depth water equivalent can be found in 235078.
[NOTE: See 141 for the equivalent parameter in \"m of water equivalent\"]
","unit_id":22,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":228143,"name":"Convective precipitation","shortname":"cp","description":"Precipitation produced by the convection scheme. Accumulated from the beginning of the forecast.\n [NOTE: See 143 for the equivalent parameter in \"m\"]","unit_id":22,"encoding_ids":["grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":228144,"name":"Snowfall water equivalent","shortname":"sf","description":"[NOTE: See 144 for the equivalent parameter in \"m of water equivalent\"]","unit_id":22,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":228164,"name":"Total Cloud Cover","shortname":"tcc","description":"[NOTE: See 164 for the equivalent parameter in \"(0-1)\"]","unit_id":29,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":228170,"name":"Field capacity","shortname":"cap","description":null,"unit_id":9,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":228171,"name":"Wilting point","shortname":"wilt","description":null,"unit_id":9,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":228205,"name":"Water runoff and drainage","shortname":"ro","description":"Soil total column lateral water flow and bottom soil drainage","unit_id":22,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":228216,"name":"Accumulated freezing rain","shortname":"fzra","description":"This parameter is the total amount of precipitation falling as freezing rain, accumulated over a particular time period which depends on the data extracted.
Freezing rain occurs when supercooled water droplets (below 0°C but still in liquid form) immediately freeze as they hit the ground (and other surfaces) to form a coating or glaze of clear ice. Freezing rain creates hazardous, extremely slippery surface conditions and can cause disruption to road, rail and air transport. If prolonged, it can damage vegetation and crops and can accumulate on power lines, causing them to collapse.
The units are depth in metres of liquid water equivalent. It is the depth the liquid water would have if it were spread evenly over the grid box. Care should be taken when comparing model parameters with observations, because observations are often local to a particular point in space and time, rather than representing averages over a model grid box and model time step \n[NOTE: See 231001 for the equivalent parameter in \"kg m-2\"]","unit_id":4,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":228217,"name":"Instantaneous large-scale precipitation fraction","shortname":"ilspf","description":"
Large-scale precipitation is rain and snow that falls to the Earth's surface, and is generated by the cloud scheme in the ECMWF Integrated Forecasting System (IFS). The cloud scheme represents the formation and dissipation of clouds and large-scale precipitation due to changes in atmospheric quantities (such as pressure, temperature and moisture) predicted directly by the IFS at spatial scales of a grid box or larger. Precipitation can also be due to convection generated by the convection scheme in the IFS. The convection scheme represents convection at spatial scales smaller than the grid box. See further information.
","unit_id":105,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":228218,"name":"Convective rain rate","shortname":"crr","description":"This parameter is the rate of rainfall (rainfall intensity), at the specified time , generated by the convection scheme in the ECMWF Integrated Forecasting System (IFS). The convection scheme represents convection at spatial scales smaller than the grid box.
Total rainfall is made up of convective and large-scale rainfall. Large-scale rainfall is generated by the cloud scheme in the IFS. The cloud scheme represents the formation and dissipation of clouds and large-scale rainfall due to changes in atmospheric quantities (such as pressure, temperature and moisture) predicted directly by the IFS at spatial scales of a grid boxor larger. See further information. Rainfall is one component of precipitation. In the IFS, precipitation is rain and snow that falls to the Earth's surface.
1 kg of water spread over 1 square metre of surface is 1 mm deep (neglecting the effects of temperature on the density of water), therefore the units are equivalent to mm per second.
Care should be taken when comparing model parameters with observations, because observations are often local to a particular point in space and time, rather than representing averages over a model grid box and model time step.","unit_id":33,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":228219,"name":"Large scale rain rate","shortname":"lsrr","description":"This parameter is the rate of rainfall (rainfall intensity), at the specified time, generated by the cloud scheme in the ECMWF Integrated Forecasting System (IFS). The cloud scheme represents the formation and dissipation of clouds and large-scale precipitation due to changes in atmospheric quantities (such as pressure, temperature and moisture) predicted directly by the IFS at spatial scales of a grid box or larger.
Rainfall can also be due to convection generated by the convection scheme in the IFS. The convection scheme represents convection at spatial scales smaller than the grid box. See further information. Rainfall is one component of precipitation. In the IFS, precipitation is rain and snow that falls to the Earth's surface.
1 kg of water spread over 1 square metre of surface is 1 mm deep (neglecting the effects of temperature on the density of water), therefore the units are equivalent to mm per second.
Care should be taken when comparing model parameters with observations, because observations are often local to a particular point in space and time, rather than representing averages over a model grid box and model time step.","unit_id":33,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":228220,"name":"Convective snowfall rate water equivalent","shortname":"csfr","description":"This parameter is the rate of snowfall (snowfall intensity), at the specified time, generated by the convection scheme in the ECMWF Integrated Forecasting System (IFS). The convection scheme represents convection at spatial scales smaller than the grid box.
Total snowfall is made up of convective and large-scale snowfall. Large-scale snowfall is generated by the cloud scheme in the IFS. The cloud scheme represents the formation and dissipation of clouds and large-scale snowfall due to changes in atmospheric quantities (such as pressure, temperature and moisture) predicted directly by the IFS at spatial scales of a grid box or larger. See further information. Snowfall is one component of precipitation. In the IFS, precipitation is rain and snow that falls to the Earth's surface
Snowfall rate is considered here in terms of its water equivalent. Since 1 kg of water spread over 1 square metre of surface is 1 mm thick (neglecting the effects of temperature on the density of water), the units are equivalent to mm (of liquid water) per second.
Care should be taken when comparing model parameters with observations, because observations are often local to a particular point in space and time, rather than representing averages over a model grid box and model time step.","unit_id":33,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":228221,"name":"Large scale snowfall rate water equivalent","shortname":"lssfr","description":"This parameter is the rate of snowfall (snowfall intensity), at the specified time, generated by the cloud scheme in the ECMWF Integrated Forecasting System (IFS). The cloud scheme represents the formation and dissipation of clouds and large-scale snowfall due to changes in atmospheric quantities (such as pressure, temperature and moisture) predicted directly by the IFS at spatial scales of a grid box or larger.
Snowfall can also be due to convection generated by the convection scheme in the IFS. The convection scheme represents convection at spatial scales smaller than the grid box. See further information. Snowfall is one component of precipitation. In the IFS, precipitation is rain and snow that falls to the Earth's surface
Snowfall rate is considered here in terms of its water equivalent. Since 1 kg of water spread over 1 square metre of surface is 1 mm thick (neglecting the effects of temperature on the density of water), the units are equivalent to mm (of liquid water) per second.
Care should be taken when comparing model parameters with observations, because observations are often local to a particular point in space and time, rather than representing averages over a model grid box and model time step.","unit_id":33,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":228222,"name":"Maximum total precipitation rate in the last 3 hours","shortname":"mxtpr3","description":"The maximum total precipitation rate in the previous 3 hour period. The maximum is calculated from the precipitation rate at each model time step.
In the ECMWF Integrated Forecasting System (IFS), total precipitation is rain and snow that falls to the Earth's surface. It is the sum of large-scale precipitation and convective precipitation. Large-scale precipitation is generated by the cloud scheme in the IFS. The cloud scheme represents the formation and dissipation of clouds and large-scale precipitation due to changes in atmospheric quantities (such as pressure, temperature and moisture) predicted directly by the IFS at spatial scales of a grid box or larger. Convective precipitation is generated by the convection scheme in the IFS. The convection scheme represents convection at spatial scales smaller than the grid box. See further information .
1 kg of water spread over 1 square metre of surface is 1 mm deep (neglecting the effects of temperature on the density of water), therefore the units are equivalent to mm per second.
Care should be taken when comparing model parameters with observations, because observations are often local to a particular point in space and time, rather than representing averages over a model grid box and model time step.","unit_id":33,"encoding_ids":["grib1"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":228223,"name":"Minimum total precipitation rate in the last 3 hours","shortname":"mntpr3","description":"The minimum total precipitation rate in the previous 3 hour period. The minimum is calculated from the precipitation rate at each model time step.
In the ECMWF Integrated Forecasting System (IFS), total precipitation is rain and snow that falls to the Earth's surface. It is the sum of large-scale precipitation and convective precipitation. Large-scale precipitation is generated by the cloud scheme in the IFS. The cloud scheme represents the formation and dissipation of clouds and large-scale precipitation due to changes in atmospheric quantities (such as pressure, temperature and moisture) predicted directly by the IFS at spatial scales of a grid box or larger. Convective precipitation is generated by the convection scheme in the IFS. The convection scheme represents convection at spatial scales smaller than the grid box. See further information .
1 kg of water spread over 1 square metre of surface is 1 mm deep (neglecting the effects of temperature on the density of water), therefore the units are equivalent to mm per second.
Care should be taken when comparing model parameters with observations, because observations are often local to a particular point in space and time, rather than representing averages over a model grid box and model time step.","unit_id":33,"encoding_ids":["grib1"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":228224,"name":"Maximum total precipitation rate in the last 6 hours","shortname":"mxtpr6","description":"The maximum total precipitation rate in the previous 6 hour period. The maximum is calculated from the precipitation rate at each model time step.
In the ECMWF Integrated Forecasting System (IFS), total precipitation is rain and snow that falls to the Earth's surface. It is the sum of large-scale precipitation and convective precipitation. Large-scale precipitation is generated by the cloud scheme in the IFS. The cloud scheme represents the formation and dissipation of clouds and large-scale precipitation due to changes in atmospheric quantities (such as pressure, temperature and moisture) predicted directly by the IFS at spatial scales of a grid box or larger. Convective precipitation is generated by the convection scheme in the IFS. The convection scheme represents convection at spatial scales smaller than the grid box. See further information.
1 kg of water spread over 1 square metre of surface is 1 mm deep (neglecting the effects of temperature on the density of water), therefore the units are equivalent to mm per second.
Care should be taken when comparing model parameters with observations, because observations are often local to a particular point in space and time, rather than representing averages over a model grid box and model time step.","unit_id":33,"encoding_ids":["grib1"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":228225,"name":"Minimum total precipitation rate in the last 6 hours","shortname":"mntpr6","description":"The minimum total precipitation rate in the previous 6 hour period. The minimum is calculated from the precipitation rate at each model time step.
In the ECMWF Integrated Forecasting System (IFS), total precipitation is rain and snow that falls to the Earth's surface. It is the sum of large-scale precipitation and convective precipitation. Large-scale precipitation is generated by the cloud scheme in the IFS. The cloud scheme represents the formation and dissipation of clouds and large-scale precipitation due to changes in atmospheric quantities (such as pressure, temperature and moisture) predicted directly by the IFS at spatial scales of a grid box or larger. Convective precipitation is generated by the convection scheme in the IFS. The convection scheme represents convection at spatial scales smaller than the grid box. See further information.
1 kg of water spread over 1 square metre of surface is 1 mm deep (neglecting the effects of temperature on the density of water), therefore the units are equivalent to mm per second.
Care should be taken when comparing model parameters with observations, because observations are often local to a particular point in space and time, rather than representing averages over a model grid box and model time step.","unit_id":33,"encoding_ids":["grib1"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":228226,"name":"Maximum total precipitation rate since previous post-processing","shortname":"mxtpr","description":"The total precipitation is calculated from the combined large-scale and convective rainfall and snowfall rates every time step and the maximum is kept since the last postprocessing","unit_id":33,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":228227,"name":"Minimum total precipitation rate since previous post-processing","shortname":"mntpr","description":"The total precipitation is calculated from the combined large-scale and convective rainfall and snowfall rates every time step and the minimum is kept since the last postprocessing","unit_id":33,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":228228,"name":"Total Precipitation","shortname":"tp","description":"[NOTE: See 228 for the equivalent parameter in \"m\"]","unit_id":22,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":228229,"name":"SMOS first Brightness Temperature Bias Correction parameter","shortname":"smos_tb_cdfa","description":"","unit_id":2,"encoding_ids":["grib1"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":228230,"name":"SMOS second Brightness Temperature Bias Correction parameter","shortname":"smos_tb_cdfb","description":"","unit_id":23,"encoding_ids":["grib1"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":228231,"name":"Mixed-layer CAPE in the lowest 50 hPa","shortname":"mlcape50","description":"Convective Available Potential Energy (CAPE) is a measure of the amount of energy available for convection. It is related to the maximum potential vertical velocity in the updraught. MLCAPE50 refers to CAPE of a pseudoadiabatically ascending air parcel representing the mean conditions in the lowest 50 hPa of the atmosphere.","unit_id":17,"encoding_ids":["grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":228232,"name":"Mixed-layer CIN in the lowest 50 hPa","shortname":"mlcin50","description":"Convective Inhibition (CIN) is a measure of the amount of energy needed to be overcome for storm initiation. CIN reflects the strength of the capping inversion. MLCIN50 refers to CIN of a pseudoadiabatically ascending air parcel representing the mean conditions in the lowest 50 hPa of the atmosphere.","unit_id":17,"encoding_ids":["grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":228233,"name":"Mixed-layer CAPE in the lowest 100 hPa","shortname":"mlcape100","description":"Convective Available Potential Energy (CAPE) is a measure of the amount of energy available for convection. It is related to the maximum potential vertical velocity in the updraught. MLCAPE100 refers to CAPE of a pseudoadiabatically ascending air parcel representing the mean conditions in the lowest 100 hPa of the atmosphere.","unit_id":17,"encoding_ids":["grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":228234,"name":"Mixed-layer CIN in the lowest 100 hPa","shortname":"mlcin100","description":"Convective Inhibition (CIN) is a measure of the amount of energy needed to be overcome for storm initiation. CIN reflects the strength of the capping inversion. MLCIN100 refers to CIN of a pseudoadiabatically ascending air parcel representing the mean conditions in the lowest 100 hPa of the atmosphere.","unit_id":17,"encoding_ids":["grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":228235,"name":"Most-unstable CAPE","shortname":"mucape","description":"Convective Available Potential Energy (CAPE) is a measure of the amount of energy available for convection. It is related to the maximum potential vertical velocity in the updraught. In the IFS MUCAPE refers to the most unstable parcel (the parcel with the largest CAPE) found in the atmosphere from the surface up to 350 hPa. For all the model levels in the lowest 60 hPa, 30-hPa mixed-layer parameters are used.","unit_id":17,"encoding_ids":["grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":228236,"name":"Most-unstable CIN","shortname":"mucin","description":"Convective Inhibition (CIN) is a measure of the amount of energy needed to be overcome for storm initiation. CIN reflects the strength of the capping inversion. In the IFS MUCIN refers to the most unstable parcel (the parcel with the largest CAPE) found in the atmosphere from the surface up to 350 hPa. For all the model levels in the lowest 60 hPa, 30-hPa mixed-layer parameters are used.","unit_id":17,"encoding_ids":["grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":228237,"name":"Departure level of the most unstable parcel expressed as Pressure","shortname":"mudlp","description":"This represents the vertical level expressed as pressure from which the most unstable parcel (the parcel with the largest CAPE) starts rising.","unit_id":16,"encoding_ids":["grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":228239,"name":"200 metre U wind component","shortname":"200u","description":"","unit_id":5,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":228240,"name":"200 metre V wind component","shortname":"200v","description":"","unit_id":5,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":228241,"name":"200 metre wind speed","shortname":"200si","description":"","unit_id":5,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":228242,"name":"Surface solar radiation diffuse total sky","shortname":"fdif","description":"Total sky surface flux of diffuse shortwave radiation flux computed from the model radiation scheme","unit_id":6,"encoding_ids":["grib1"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":228243,"name":"Surface solar radiation diffuse clear-sky","shortname":"cdif","description":"Clear-sky surface flux of diffuse shortwave radiation flux computed from the model radiation scheme","unit_id":6,"encoding_ids":["grib1"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":228244,"name":"Surface albedo of direct radiation","shortname":"aldr","description":"Surface albedo for direct radiation integrated by the radiation scheme computed from the model radiation scheme","unit_id":3,"encoding_ids":["grib1"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":228245,"name":"Surface albedo of diffuse radiation","shortname":"aldf","description":"Surface albedo for diffuse radiation integrated by the radiation scheme computed from the model radiation scheme","unit_id":3,"encoding_ids":["grib1"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":228246,"name":"100 metre U wind component","shortname":"100u","description":"This parameter is the eastward component of the 100 m wind. It is the horizontal speed of air moving towards the east, at a height of 100 metres above the surface of the Earth, in metres per second.
Care should be taken when comparing model parameters with observations, because observations are often local to a particular point in space and time, rather than representing averages over a model grid box and model time step.
This parameter can be combined with the northward component to give the speed and direction of the horizontal 100 m wind.","unit_id":5,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":228247,"name":"100 metre V wind component","shortname":"100v","description":"This parameter is the northward component of the 100 m wind. It is the horizontal speed of air moving towards the north, at a height of 100 metres above the surface of the Earth, in metres per second.
Care should be taken when comparing model parameters with observations, because observations are often local to a particular point in space and time, rather than representing averages over a model grid box and model time step.
This parameter can be combined with the eastward component to give the speed and direction of the horizontal 100 m wind.","unit_id":5,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":228248,"name":"Surface short wave-effective total cloudiness","shortname":"tccsw","description":"Let SSRD and STRD be the surface downward short-wave and long-wave radiation at the surface, and SSRDC and STRDC the surface clear-sky downward short-wave and long-wave radiation at the surface.\r\n\r\nThe short-wave and long-wave radiation-effective total cloudiness are\r\nthe equivalent cloud fractions of the sky that would give the surface\r\ndownward radiation, without reference to any cloud overlap assumption,\r\nany specification (liquid droplets or ice particles) of cloud particles,\r\nand related cloud optical properties.\r\nIn particular, TCCSW, the surface short-wave-effective total cloudiness\r\nis what might be the closest to what the \"person in the street\" could\r\nthink of as total cloudiness.\r\n\r\nComputationally speaking, TCCSW = 1 - SSRD / SSRDC\r\nand TCCLW = 1 - STRDC / STRD\r\n\r\n(the difference in the ratios is due to the fact that, w.r.t. to clear\r\nsky conditions, clouds decrease the amount of short-wave radiation\r\nusually available at the surface, whereas clouds actually increase the\r\namount of long-wave radiation available at the surface).","unit_id":23,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":228249,"name":"100 metre wind speed","shortname":"100si","description":"This parameter is the horizontal speed of the wind, or movement of air, at a height of 100 m above the surface of the Earth.
Care should be taken when comparing model parameters with observations, because observations are often local to a particular point in space and time, rather than representing averages over a model grid box and model time step.
Two other parameters, the eastward and northward components, can be used to give the direction of the horizontal 100 m wind.","unit_id":5,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":228250,"name":"Irrigation fraction","shortname":"irrfr","description":"","unit_id":105,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":228251,"name":"Potential evaporation","shortname":"pev","description":"This parameter is a measure of the extent to which near-surface atmospheric conditions are conducive to the process of evaporation. It is usually considered to be the amount of evaporation, under existing atmospheric conditions, from a surface of pure water which has the temperature of the lowest layer of the atmosphere and gives an indication of the maximum possible evaporation.
Potential evaporation in the current ECMWF Integrated Forecasting System is based on surface energy balance calculations with the vegetation parameters set to 'crops/mixed farming' and assuming 'no stress from soil moisture'. In other words, evaporation is computed for agricultural land as if it is well watered and assuming that the atmosphere is not affected by this artificial surface condition. The latter may not always be realistic. Although potential evaporation is meant to provide an estimate of irrigation requirements, the method can give unrealistic results in arid conditions due to too strong evaporation forced by dry air.
This parameter is accumulated over a particular time period which depends on the data extracted.\n [NOTE: See 231005 for the equivalent parameter in \"kg m-2\"]","unit_id":4,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":228252,"name":"Irrigation","shortname":"irr","description":"","unit_id":4,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":228253,"name":"ASCAT first soil moisture CDF matching parameter","shortname":"ascat_sm_cdfa","description":null,"unit_id":10,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":228254,"name":"ASCAT second soil moisture CDF matching parameter","shortname":"ascat_sm_cdfb","description":null,"unit_id":23,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":228255,"name":"Surface long wave-effective total cloudiness","shortname":"tcclw","description":"Let SSRD and STRD be the surface downward short-wave and long-wave radiation at the surface, and SSRDC and STRDC the surface clear-sky downward short-wave and long-wave radiation at the surface.\r\n\r\nThe short-wave and long-wave radiation-effective total cloudiness are\r\nthe equivalent cloud fractions of the sky that would give the surface\r\ndownward radiation, without reference to any cloud overlap assumption,\r\nany specification (liquid droplets or ice particles) of cloud particles,\r\nand related cloud optical properties.\r\nIn particular, TCCSW, the surface short-wave-effective total cloudiness\r\nis what might be the closest to what the \"person in the street\" could\r\nthink of as total cloudiness.\r\n\r\nComputationally speaking, TCCSW = 1 - SSRD / SSRDC\r\nand TCCLW = 1 - STRDC / STRD\r\n\r\n(the difference in the ratios is due to the fact that, w.r.t. to clear\r\nsky conditions, clouds decrease the amount of short-wave radiation\r\nusually available at the surface, whereas clouds actually increase the\r\namount of long-wave radiation available at the surface).","unit_id":23,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":229001,"name":"Urban cover","shortname":"cur","description":"This parameter is the fraction of the grid box (0-1) that is covered with an urban surface.\r\nThis parameter includes all impervious and\r\nartificial surfaces (e.g. roads, buildings, parking lots, etc.).","unit_id":3,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":229002,"name":"Road Cover","shortname":"cro","description":"This parameter is the fraction of the grid box (0-1) that is covered with a flat impervious surface (including paved areas and bridges).\r\n","unit_id":3,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":229003,"name":"Building cover","shortname":"cbu","description":"This parameter is the fraction of the grid box (0-1) that is covered with an elevated impervious surface (e.g. buildings).\r\n","unit_id":3,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":229004,"name":"Building height","shortname":"bldh","description":"This parameter contains the mean building height.","unit_id":4,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":229005,"name":"Vertical-to-horizontal area ratio","shortname":"hwr","description":"This parameter is the ratio of total building wall area to the plan area of urban cover.","unit_id":19,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":229006,"name":"Standard deviation of building height","shortname":"bhstd","description":"This parameter is the standard deviation of building heights of the grid box","unit_id":4,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":229007,"name":"Wetland cover","shortname":"cwe","description":"This parameter is the fraction of the grid box (0-1) which is inundated. This includes marshes, fens, bogs and swamps but excludes lakes, reservoirs, rivers and coral reefs.","unit_id":3,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":229008,"name":"Wetland type","shortname":"twe","description":"This parameter indicates the 12 types of wetlands recognised by the ECMWF IFS wetland emissions model. They are used to calculate the wetland methane fluxes:\r\n1 - Bog\r\n2 - Drained\r\n3 - Fen\r\n4 - Floodplain\r\n5 - Mangrove\r\n6 - Marsh\r\n7 - Rice\r\n8 - Riverine\r\n9 - Salt Marsh\r\n10 - Swamp\r\n11 - Upland\r\n12 - Wet Tundra","unit_id":81,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":229009,"name":"Irrigation cover","shortname":"cirr","description":"This parameter is the fraction of the grid box (0-1) that is subject to irrigation","unit_id":3,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":229010,"name":"C4 crop cover","shortname":"c4cr","description":"This parameter is the fraction of the grid box (0-1) with C4 crops.","unit_id":3,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":229011,"name":"C4 grass cover","shortname":"c4gr","description":"This parameter is the fraction of the grid box (0-1) with C4 grass.","unit_id":3,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":230008,"name":"Surface runoff (variable resolution)","shortname":"srovar","description":"","unit_id":4,"encoding_ids":["grib1"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":230009,"name":"Sub-surface runoff (variable resolution)","shortname":"ssrovar","description":"","unit_id":4,"encoding_ids":["grib1"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":230020,"name":"Clear sky surface photosynthetically active radiation (variable resolution)","shortname":"parcsvar","description":"0.44-0.70 um accumulated field","unit_id":6,"encoding_ids":["grib1"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":230021,"name":"Total sky direct solar radiation at surface (variable resolution)","shortname":"fdirvar","description":"","unit_id":6,"encoding_ids":["grib1"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":230022,"name":"Clear-sky direct solar radiation at surface (variable resolution)","shortname":"cdirvar","description":"","unit_id":6,"encoding_ids":["grib1"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":230044,"name":"Snow evaporation (variable resolution)","shortname":"esvar","description":"Evaporation from snow averaged over the grid box (to find flux over snow, divide by snow fraction) ","unit_id":22,"encoding_ids":["grib1"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":230045,"name":"Snowmelt (variable resolution)","shortname":"smltvar","description":"Melting of snow averaged over the grid box (to find melt over snow, divide by snow fraction) ","unit_id":22,"encoding_ids":["grib1"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":230046,"name":"Solar duration (variable resolution)","shortname":"sdurvar","description":null,"unit_id":12,"encoding_ids":["grib1"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":230047,"name":"Direct solar radiation (variable resolution)","shortname":"dsrpvar","description":"Incident on a plane perpendicular to the Sun's direction. 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Accumulated field.","unit_id":12,"encoding_ids":["grib1"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":230057,"name":"Downward UV radiation at the surface (variable resolution)","shortname":"uvbvar","description":null,"unit_id":6,"encoding_ids":["grib1"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":230058,"name":"Photosynthetically active radiation at the surface (variable resolution)","shortname":"parvar","description":null,"unit_id":6,"encoding_ids":["grib1"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":230080,"name":"Accumulated Carbon Dioxide Net Ecosystem Exchange (variable resolution)","shortname":"aco2neevar","description":"","unit_id":22,"encoding_ids":["grib1"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":230081,"name":"Accumulated Carbon Dioxide Gross Primary Production (variable 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","unit_id":6,"encoding_ids":["grib1"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":230178,"name":"Top net solar radiation (variable resolution)","shortname":"tsrvar","description":"Net solar radiation at the top of the atmosphere ","unit_id":6,"encoding_ids":["grib1"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":230179,"name":"Top net thermal radiation (variable resolution)","shortname":"ttrvar","description":"Net thermal radiation at the top of the atmosphere ","unit_id":6,"encoding_ids":["grib1"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":230180,"name":"East-West surface stress (variable resolution)","shortname":"ewssvar","description":"East-West surface stress due to to turbulent processes ","unit_id":14,"encoding_ids":["grib1"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":230181,"name":"North-South surface stress (variable 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","unit_id":14,"encoding_ids":["grib1"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":230196,"name":"Meridional component of gravity wave stress (variable resolution)","shortname":"mgwsvar","description":"North-South component of surface stress due to gravity waves and orographic blocking ","unit_id":14,"encoding_ids":["grib1"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":230197,"name":"Gravity wave dissipation (variable resolution)","shortname":"gwdvar","description":"Conversion of kinetic energy of the mean flow into heat due gravity waves and orographic blocking ","unit_id":6,"encoding_ids":["grib1"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":230198,"name":"Skin reservoir content (variable resolution)","shortname":"srcvar","description":"Amount of water in interception reservoir ","unit_id":22,"encoding_ids":["grib1"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":230205,"name":"Runoff (variable resolution)","shortname":"rovar","description":"Amount of water that is lost from the soil through surface runoff and deep soil drainage ","unit_id":4,"encoding_ids":["grib1"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":230208,"name":"Top net solar radiation, clear sky (variable resolution)","shortname":"tsrcvar","description":"Clear sky part of the net solar radiation at the top of the atmosphere ","unit_id":6,"encoding_ids":["grib1"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":230209,"name":"Top net thermal radiation, clear sky (variable resolution)","shortname":"ttrcvar","description":"Clear sky part of the net thermal radiation at the top of the atmosphere ","unit_id":6,"encoding_ids":["grib1"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":230210,"name":"Surface net solar radiation, clear sky (variable resolution)","shortname":"ssrcvar","description":"Clear sky part of the net solar radiation at the surface ","unit_id":6,"encoding_ids":["grib1"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":230211,"name":"Surface net thermal radiation, clear sky (variable resolution)","shortname":"strcvar","description":"Clear sky part of the net thermal radiation at the surface ","unit_id":6,"encoding_ids":["grib1"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":230212,"name":"TOA incident solar radiation (variable resolution)","shortname":"tisrvar","description":null,"unit_id":6,"encoding_ids":["grib1"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":230213,"name":"Vertically integrated moisture divergence (variable 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Some water from rainfall, melting snow, or deep in the soil, stays stored in the soil. Otherwise, the water drains away, either over the surface (surface runoff), or under the ground (sub-surface runoff) and the sum of these two is simply called 'runoff'. This parameter is the total amount of water accumulated over a particular time period which depends on the data extracted. Care should be taken when comparing model parameters with observations, because observations are often local to a particular point rather than averaged over a grid square area. Observations are also often taken in different units, such as mm/day, rather than the accumulated quantity produced here.
Runoff is a measure of the availability of water in the soil, and can, for example, be used as an indicator of drought or flood. More information about how runoff is calculated is given in the IFS Physical Processes documentation.
[NOTE: See 205 for the equivalent parameter in \"m\"]
","unit_id":22,"encoding_ids":["grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":231003,"name":"Snow evaporation water equivalent","shortname":"eswe","description":"[NOTE: See 44 for the equivalent parameter in \"m of water equivalent\"]","unit_id":22,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":231004,"name":"Potential evaporation rate","shortname":"pevr","description":null,"unit_id":33,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":231005,"name":"Potential evaporation","shortname":"peva","description":"[NOTE: See 228251 for the equivalent parameter in \"m\"]","unit_id":22,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":231006,"name":"Tile 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The root zone is the maximum depth at which plants can extract water from the soil. Voids are empty spaces in the soil column that can be filled with water or air.","unit_id":106,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":231027,"name":"Soil wetness index (layer)","shortname":"swil","description":"The volume of water over the total volume of voids in the soil, expressed as an index with values between 0 (residual soil moisture) and 1 (saturation), representing the lower and upper soil moisture limits of the specific soil layer.","unit_id":106,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":231028,"name":"Distance downward from roof surface","shortname":"ddrf","description":null,"unit_id":4,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":231029,"name":"Distance inward from outer wall 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in the river channel (wet area).\nThe channel cross section area multiplied by the mean velocity of the flow gives the discharge (instant)","unit_id":31,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":240012,"name":"Side flow into river channel","shortname":"chside","description":"Rate of runoff that enters the river channel in each grid cell. The runoff consists of the contributions from surface runoff, outflow from ground water, additional runoff from rivers and reservoirs. Calculated as a flow (m3/s) per m river length. The value is the mean rate over the timestep","unit_id":208,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":240013,"name":"Discharge from rivers or streams","shortname":"dis","description":"The instantaneous volume rate of water flow, including sediments, chemical and biological material, in the river channel through a cross section.","unit_id":49,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":240014,"name":"River storage of water","shortname":"rivsto","description":"The amount of water storage in the river network within a grid cell; this does not include the floodplain. The term storage refers to the total volume of water. This value is instantaneous.","unit_id":207,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":240015,"name":"Floodplain storage of water","shortname":"fldsto","description":"The amount of water storage on the floodplain within a grid cell.The term storage refers to the total volume of water.\r\nA floodplain is defined as: 'A flat or nearly flat land adjacent to a stream or river that stretches from the banks of its channel to the base of the enclosing valley walls and experiences flooding during periods of high discharge' (Goudie, A. S., 2004, Encyclopedia of Geomorphology, vol. 1. Routledge, New York. ISBN 0-415-32737-7). This value is instantaneous.","unit_id":207,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":240017,"name":"Days since last observation","shortname":"dslr","description":"The number of days since the last observation.\nThe value is initialised as 1 on the first day, and then incremented (instant)","unit_id":166,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":240018,"name":"Frost index","shortname":"frost","description":"When the soil surface is frozen, this affects the hydrological processes occurring near the soil surface. To estimate whether the soil surface is frozen or not, a frost index F is calculated. The equation is based on Molnau & Bissell (1983, cited in Maidment 1993), and adjusted for variable time steps. The rate at which the frost index changes is given by:\r\n
\r\ndF/dt = (1-Af)F-Tav•e(-0.04•K•ds/wes)\r\n
\r\ndF/dt is expressed in [°C day-1 day-1 ]. Af is a decay coefficient [day-1], K is a a snow\r\ndepth reduction coefficient [cm-1], ds is the (pixel-average) depth of the snow cover\r\n(expressed as mm equivalent water depth), and wes is a parameter called snow\r\nwater equivalent, which is the equivalent water depth water of a snow cover\r\n(Maidment, 1993). The soil is considered frozen when the frost index rises above a\r\ncritical threshold of 56. For each time step the value of F [°C day-1] is updated as:\n
\r\nF(t) = F(t −1) + dF/dt•Δt\r\n
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Instantaneous.
Please note that the encodings listed here for uerra (which includes carra/cerra) are for Time-mean total column vertically-integrated graupel (snow pellets). The specific encoding for Time-mean total column vertically-integrated graupel (snow pellets) can be found in 235120.
","unit_id":22,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":260002,"name":"Surface latent heat net flux","shortname":"slhtf","description":null,"unit_id":76,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":260004,"name":"Heat index","shortname":"heatx","description":"The heat index describes the perception of the human body when its evaporative cooling mechanism is limited due to increased relative humidity. It is derived from air temperature and relative humidity.","unit_id":2,"encoding_ids":["grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":260005,"name":"Wind chill factor","shortname":"wcf","description":"The wind chill factor describes the cooling sensation felt by the human body and is based on the rate of heat loss from exposed skin caused by the effects of wind and cold. It is derived from air temperature and wind speed.","unit_id":2,"encoding_ids":["grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":260007,"name":"Snow phase change heat flux","shortname":"snohf","description":null,"unit_id":76,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":260008,"name":"Vapor pressure","shortname":"vapp","description":null,"unit_id":16,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":260009,"name":"Large scale precipitation (non-convective)","shortname":"ncpcp","description":null,"unit_id":22,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":260010,"name":"Snowfall rate water equivalent","shortname":"srweq","description":null,"unit_id":33,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":260011,"name":"Convective snow","shortname":"snoc","description":null,"unit_id":22,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":260012,"name":"Large scale snow","shortname":"snol","description":null,"unit_id":22,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":260013,"name":"Snow age","shortname":"snoag","description":null,"unit_id":98,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":260014,"name":"Absolute humidity","shortname":"absh","description":null,"unit_id":9,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":260015,"name":"Precipitation type","shortname":"ptype","description":"
This parameter describes the type of precipitation at the surface, at the specified time.
A precipitation type is assigned wherever there is a non-zero value of precipitation in the model output field. The precipitation type should be used together with the precipitation rate to provide, for example, an indication of potential freezing rain events.
In the ECMWF Integrated Forecasting System (IFS) there are only two predicted precipitation variables: rain and snow. Precipitation type is derived from these two predicted variables in combination with atmospheric conditions, such as temperature.
Values of precipitation type defined in the IFS:
0 = No precipitation 1 = Rain 3 = Freezing rain (i.e. supercooled raindrops which freeze on contact with the ground and other surfaces) 5 = Snow 6 = Wet snow (i.e. snow particles which are starting to melt) 7 = Mixture of rain and snow 8 = Ice pellets 12 = Freezing drizzle (i.e. supercooled drizzle which freezes on contact with the ground and other surfaces)
These precipitation types are consistent with WMO Code Table 4.201. 2 (thunderstorm), 4 (mixed ice) and 9 (graupel), 10 (hail) and 11 (drizzle) are not diagnosed in the IFS.
","unit_id":100,"encoding_ids":["grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":260016,"name":"Integrated liquid water","shortname":"iliqw","description":null,"unit_id":22,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":260017,"name":"Condensate","shortname":"tcond","description":null,"unit_id":21,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":260018,"name":"Cloud mixing ratio","shortname":"clwmr","description":null,"unit_id":21,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":260019,"name":"Ice water mixing ratio","shortname":"icmr","description":null,"unit_id":21,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":260020,"name":"Rain mixing ratio","shortname":"rwmr","description":null,"unit_id":21,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":260021,"name":"Snow mixing ratio","shortname":"snmr","description":null,"unit_id":21,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":260022,"name":"Horizontal moisture convergence","shortname":"mconv","description":null,"unit_id":39,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":260025,"name":"Total snowfall","shortname":"asnow","description":"Please be aware that this parameter represents the metres of snowfall in a gridbox accumulated over a period of time without the conversion to liquid water equivalent. Please refer to parameter 144 (m of water equivalent) and 228144 (kg m-2) for this parameter.","unit_id":4,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":260026,"name":"Precipitable water category","shortname":"pwcat","description":null,"unit_id":103,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":260027,"name":"Hail","shortname":"hail","description":null,"unit_id":4,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":260028,"name":"Graupel (snow pellets)","shortname":"grle","description":null,"unit_id":21,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":260029,"name":"Categorical rain","shortname":"crain","description":null,"unit_id":104,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":260030,"name":"Categorical freezing rain","shortname":"cfrzr","description":null,"unit_id":104,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":260031,"name":"Categorical ice pellets","shortname":"cicep","description":null,"unit_id":104,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":260032,"name":"Categorical snow","shortname":"csnow","description":null,"unit_id":104,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":260033,"name":"Convective precipitation rate","shortname":"cpr","description":null,"unit_id":33,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":260034,"name":"Horizontal moisture divergence","shortname":"mdiv","description":null,"unit_id":39,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":260035,"name":"Percent frozen precipitation","shortname":"cpofp","description":null,"unit_id":29,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":260036,"name":"Potential evaporation","shortname":"pevap","description":"[DEPRECATED - Please use paramId 231005 instead]","unit_id":22,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":260038,"name":"Snow cover","shortname":"snowc","description":null,"unit_id":29,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":260039,"name":"Rain fraction of total cloud water","shortname":"frain","description":null,"unit_id":105,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":260040,"name":"Rime factor","shortname":"rime","description":null,"unit_id":106,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":260041,"name":"Total column integrated rain","shortname":"tcolr","description":null,"unit_id":22,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":260042,"name":"Total column integrated snow","shortname":"tcols","description":null,"unit_id":22,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":260043,"name":"Large scale water precipitation (non-convective)","shortname":"lswp","description":null,"unit_id":22,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":260044,"name":"Convective water precipitation","shortname":"cwp","description":null,"unit_id":22,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":260045,"name":"Total water precipitation","shortname":"twatp","description":null,"unit_id":22,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":260046,"name":"Total snow precipitation","shortname":"tsnowp","description":null,"unit_id":22,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":260047,"name":"Total column water (Vertically integrated total water (vapour + cloud water/ice))","shortname":"tcwat","description":null,"unit_id":22,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":260048,"name":"Total precipitation rate","shortname":"tprate","description":"This parameter is the rate of total precipitation, at the specified time.
In the ECMWF Integrated Forecasting System (IFS), total precipitation is rain and snow that falls to the Earth's surface. It is the sum of large-scale precipitation and convective precipitation. Large-scale precipitation is generated by the cloud scheme in the IFS. The cloud scheme represents the formation and dissipation of clouds and large-scale precipitation due to changes in atmospheric quantities (such as pressure, temperature and moisture) predicted directly by the IFS at spatial scales of a grid box or larger. Convective precipitation is generated by the convection scheme in the IFS. The convection scheme represents convection at spatial scales smaller than the grid box.See further information. Precipitation parameters do not include fog, dew or the precipitation that evaporates in the atmosphere before it lands at the surface of the Earth.
1 kg of water spread over 1 square metre of surface is 1 mm deep (neglecting the effects of temperature on the density of water), therefore the units are equivalent to mm per second.
Care should be taken when comparing model parameters with observations, because observations are often local to a particular point in space and time, rather than representing averages over a model grid box and model time step .","unit_id":33,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":260049,"name":"Total snowfall rate water equivalent","shortname":"tsrwe","description":null,"unit_id":33,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":260050,"name":"Large scale precipitation rate","shortname":"lsprate","description":null,"unit_id":33,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":260053,"name":"Total snowfall rate","shortname":"tsrate","description":null,"unit_id":5,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":260054,"name":"Convective snowfall 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Cloud ceiling is a measurement used in the aviation industry to indicate airport landing conditions.
This parameter is calculated by searching from the second lowest model level upwards, to the height of the level where cloud fraction becomes greater than 50% and condensate content greater than 1.E-6 kg kg-1. Fog (i.e., cloud in the lowest model layer) is not considered when defining ceiling.","unit_id":4,"encoding_ids":["grib1","grib2"],"access_ids":["dissemination"],"published":true,"pending":false,"retired":false},{"id":260110,"name":"Non-convective cloud cover","shortname":"cdlyr","description":null,"unit_id":29,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":260111,"name":"Cloud work function","shortname":"cwork","description":null,"unit_id":17,"encoding_ids":["grib1","grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":260112,"name":"Convective cloud efficiency","shortname":"cuefi","description":null,"unit_id":105,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":260113,"name":"Total condensate","shortname":"tcond","description":null,"unit_id":21,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":260114,"name":"Total column-integrated cloud water","shortname":"tcolw","description":null,"unit_id":22,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":260115,"name":"Total column-integrated cloud ice","shortname":"tcoli","description":null,"unit_id":22,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":260116,"name":"Total column-integrated condensate","shortname":"tcolc","description":null,"unit_id":22,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":260117,"name":"Ice fraction of total condensate","shortname":"fice","description":null,"unit_id":105,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":260118,"name":"Cloud ice mixing ratio","shortname":"cdcimr","description":null,"unit_id":21,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":260119,"name":"Sunshine","shortname":"suns","description":null,"unit_id":106,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":260120,"name":"Horizontal extent of cumulonimbus (CB)","shortname":"~","description":null,"unit_id":29,"encoding_ids":["grib2"],"access_ids":[],"published":true,"pending":false,"retired":false},{"id":260121,"name":"K index","shortname":"kx","description":"This parameter is a measure of potential for a thunderstorm to develop calculated from the temperature and dew point temperature in the lower part of the atmosphere. The calculation uses the temperature at 850, 700 and 500 hPa and dewpoint temperature at 850 and 700 hPa. Higher values of K indicate a higher potential for the development of thunderstorms.
This parameter is related to the probability of occurrence of a thunderstorm:
Parameter value
Thunderstorm Probability
<20 K
No thunderstorm.
20-25 K
Isolated thunderstorms.
26-30 K
Widely scattered thunderstorms.
31-35 K
Scattered thunderstorms.
>35 K
Numerous thunderstorms
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TT index
Thunderstorm Probability
<44
Thunderstorms not likely.
44-50
Thunderstorms likely.
51-52
Isolated severe thunderstorms.
53-56
Widely scattered severe thunderstorms.
56-60
Scattered severe thunderstorms more likely.
The total totals index is the temperature difference between 850 hPa (near surface) and 500 hPa (mid-troposphere) (lapse rate) plus a measure of the moisture content between 850 hPa and 500 hPa. The probability of deep convection tends to increase with increasing lapse rate and atmospheric moisture content.
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