
Introduction
Here we document the ERA-Interim dataset, which, covers the period from 1st January 1979 to 31st August 2019.
ERA-interim was produced using cycle 31r2 of the Integrated Forecast System (IFS - CY31R2) 2006, with 60 vertical levels, with the top level at 0.01 hPa. Atmospheric data are available on these levels and they are also interpolated to 37 pressure, 16 potential temperature and 1 potential vorticity
level(s). "Surface or single level" data are also available, containing 2D parameters such as precipitation, 2m temperature, top of atmosphere radiation and vertical integrals over the entire atmosphere.
Generally, the data are available at a sub-daily and monthly frequency and consist of analyses and 10-day forecasts, initialised twice daily at 00 and 12 UTC. Most analysed parameters are also available from the forecasts. There are a number of forecast parameters, e.g. mean rates and accumulations, that are not available from the analyses.
How to download ERA-Interim
The data are archived in the ECMWF data archive MARS and datasets are available through both the Web interface and the ECMWF WebAPI, which is the programmatic way of retrieving data from the archive.
Documentation is available on How to download ERA-Interim data from the ECMWF data archive (Member State users can access the data directly from MARS, in the usual manner).
The IFS and data assimilation
The model documentation for CY31r2 (choose Cy31r1) is at https://www.ecmwf.int/en/publications/ifs-documentation.
The 4D-Var data assimilation uses 12 hour windows from 15 UTC to 03 UTC and 03 UTC to 15 UTC (the following day).
The model time step is 30 minutes.
Data organisation
The data can be accessed from MARS using the keywords class=ea and expver=0001. Subdivisions of the data are labelled using stream, type and levtype.
Stream:
- oper: sub-daily products
- wave: sub-daily ocean-waves products
- mnth: synoptic monthly means
- moda: monthly means of daily means
- mdfa: monthly means of daily forecast accumulations
Type:
- an: analyses
- fc: forecasts
Levtype:
- sfc: surface or single level
- pl: pressure levels
- pt: potential temperature levels
- pv: potential vorticity levels
- ml: model levels
In MARS: the date and time of the data is specified with three MARS keywords:
For analyses date and time, specify the analysis time and step equal to 0 hours. For forecasts date and time, choose the forecast start time and then step specifies the number of hours since that start time. The combination of date, time and forecast step defines the validity time. For analyses, the validity time is equal to the analysis time.
Spatial grid
The horizontal grid spacing of ERA-Interim atmospheric model and reanalysis system is around 80 km (reduced Gaussian grid N128) which became around 83km (
) when interpolated to a regular lat/lon grid.
Depending on the parameter, the data are archived either as the full T255 spectral resolution and on the corresponding N128 reduced Gaussian grid, depending on their basic representation in the model. The coupled ocean-wave model data are produced and archived on a reduced
1.0^{\circ}\times 1.0^{\circ} |
latitude/longitude grid. For more information see ERA-Interim archive report Version 2.0, Section 2.
It is possible to specify the grid when downloading data. Available options are:
- GRIB1 format (native format): native grid, different Gaussian grids, and regular lat/lon grids. Data will be interpolated to your chosen grid if different to the native one.
- NetCDF format: NetCDF only supports regular lat/lon grids. Data is transformed to a regular lat/lon grid, interpolated to your selected resolution, and converted from the native GRIB1 format to NetCDF.
Longitudes range from 0 to 360, which is equivalent to -180 to +180 in Geographic coordinate systems.
Spatial reference systems
The ECMWF model assumes the Earth is a perfect sphere, but the geodetic latitude/longitude of the surface elevation datasets are used as if they were the spherical latitude/longitude of the ECMWF model.
ECMWF data is referenced in the horizontal with respect to the WGS84 ellipse (which defines the major/minor axes) but in the vertical it is referenced to the Geoid (EGM96).
Earth model
For data in GRIB1 format (as is the case with ERA-Interim data) the earth model is a sphere with radius = 6367.47 km, as defined in the WMO GRIB Edition 1 specifications, Table 7, GDS Octet 17
For data in NetCDF format (i.e. converted from the native GRIB format to NetCDF), the earth model is inherited from the GRIB data.
Temporal frequency
Analyses of atmospheric fields on model levels, pressure levels, potential temperature and potential vorticity, are available every 6 hours at 00, 06, 12, and 18 UTC. Forecasts run twice at 00 and 12 UTC and provide 3 hours output for surface and pressure level parameters up to 24 hours, with decreasing frequency to 10 days.

Wave spectra
The ERA-Interim atmospheric model is coupled ocean-wave model resolving 30 wave frequencies and 24 wave directions at the nodes of its reduced
1.0^{\circ}\times 1.0^{\circ} |
latitude/longitude grid.
Download from ERA-Interim Wave data can be downloaded using the same mechanisms as atmospheric data. Please see How to download data via the ECMWF WebAPI For wave spectra you need to specify the additional parameters 'direction' and 'frequency'.
#!/usr/bin/env python
from ecmwfapi import ECMWFDataServer
server = ECMWFDataServer()
server.retrieve({
"class": "ei",
"dataset": "interim",
"expver": "1",
"stream": "wave",
"type": "an",
"date": "2016-01-01/to/2016-01-31",
"time": "00:00:00/06:00:00/12:00:00/18:00:00",
"param": "251.140",
"direction": "1/2/3/4/5/6/7/8/9/10/11/12/13/14/15/16/17/18/19/20/21/22/23/24",
"frequency": "1/2/3/4/5/6/7/8/9/10/11/12/13/14/15/16/17/18/19/20/21/22/23/24/25/26/27/28/29/30",
"target": "2d_spectra_201601",
}) |
If you want to download the data in NetCDF format, please add the 'format' and 'grid' parameters: #!/usr/bin/env python
from ecmwfapi import ECMWFDataServer
server = ECMWFDataServer()
server.retrieve({
......
"grid": "0.75/0.75", # Spatial resolution in degrees latitude/longitude
"format": "netcdf"
"target": "2d_spectra_201601.nc"
}) |
|
Decoding 2D wave spectra in GRIB To decode wave spectra in GRIB format we recommend ecCodes. Wave spectra are encoded in a specific way that other tools might not decode correctly. In GRIB, the parameter is called 2d wave spectra (single) because in GRIB, the data are stored as a single global field per each spectral bin (a given frequency and direction), but in NetCDF, the fields are nicely recombined to produce a 2d matrix representing the discretized spectra at each grid point. The wave spectra are encoded in GRIB using a local table specific to ECMWF. Because of this, the conversion of the meta data containing the information about the frequencies and the directions are not properly converted from GRIB to NetCDF format. So rather than having the actual values of the frequencies and directions, values show index numbers (1,1) : first frequency, first direction, (1,2) first frequency, second direction, etc ....
For ERA, because there are a total of 24 directions, the direction increment is 15 degrees with the first direction given by half the increment, namely 7.5 degree, where direction 0. means going towards the north and 90 towards the east (Oceanographic convention), or more precisely, this should be expressed in gradient since the spectra are in m^2 /(Hz radian) The first frequency is 0.03453 Hz and the following ones are : f(n) = f(n-1)*1.1, n=2,30 Also note that it is NOT the spectral density that is encoded but rather log10 of it, so to recover the spectral density, expressed in m^2 /(radian Hz), one has to take the power 10 (10^) of the NON missing decoded values. Missing data are for all land points, but also, as part of the GRIB compression, all small values below a certain threshold have been discarded and so those missing spectral values are essentially 0. m^2 /(gradient Hz). Decoding 2D wave spectra in NetCDF The NetCDF wave spectra file will have the dimensions longitude, latitude, direction, frequency and time. However, the direction and frequency bins are simply given as 1 to 24 and 1 to 30, respectively. The direction bins start at 7.5 degree and increase by 15 degrees until 352.5, with 90 degree being towards the east (Oceanographic convention). The frequency bins are non-linearly spaced. The first bin is 0.03453 Hz and the following bins are: f(n) = f(n-1)*1.1; n=2,30. The data provided is the log10 of spectra density. To obtain the spectral density one has to take to the power 10 (10 ** data). This will give the units 2D wave spectra as m**2 s radian**-1 . Very small values are discarded and set as missing values. These are essentially 0 m**2 s radian**-1. This recoding can be done with the Python xarray package, for example: import xarray as xr
import numpy as np
da = xr.open_dataarray('2d_spectra_201601.nc')
da = da.assign_coords(direction=np.arange(7.5, 352.5 + 15, 15))
da = da.assign_coords(frequency=np.full(30, 0.03453) * (1.1 ** np.arange(0, 30)))
da = 10 ** da
da = da.fillna(0)
da.to_netcdf(path='2d_spectra_201601_recoded.nc') |
Units of 2D wave spectra Once decoded, the units of 2D wave spectra are m2 s radian-1 |
Instantaneous and Accumulated parameters
Instantaneous parameters represent an average over the model time step (30min). Accumulated parameters are accumulated from the start of the forecast, ie. from 00 UTC or 12 UTC to the time step selected. All the analysed fields are instantaneous instead forecast data could be either instantaneous or accumulated, depending on the parameter. More detailed information on parameters are shown in Parameter listing.
Minimum/maximum since the previous post processing
In ERA-Interim there are some parameters named '...since previous post-processing', for example 'Maximum temperature at 2 metres since previous post-processing'. This represents the maximum temperature between the previous archived forecast 'Step' and the forecast 'Step'. For example, 'Maximum temperature at 2 metres since previous post-processing' with start time 00 UTC and Step=9, is the maximum 2m temperature in the 3-hour period between 06 UTC and 09 UTC.
Monthly means
ERA-interim sub-daily data are monthly averaged on data with valid times or accumulation periods that fall within the calendar month in question. The different monthly means are:
- Synoptic Monthly Means (stream=mnth) are the monthly averages:
- for each analysis time (at the four main synoptic hours - 00, 06, 12, and 18 UTC)
- for each forecast start time (00 and 12 UTC) and step (3, 6, 9, 12 etc).
- Monthly Means of Daily Means (stream=moda) are only available for analysis and instantaneous forecast data.
- Monthly Means of Daily Forecast Accumulations (stream=mdfa) are similar to Monthly Means of Daily Means but are for accumulated fields (eg precipitation, radiation) and three step ranges are available.
See also Section 3 of the ERA-Interim archive documentation.
Data format
Model level fields are in GRIB2 format. All other fields are in GRIB1, unless otherwise indicated.?
Level listings
Pressure levels: 1000/975/950/925/900/875/850/825/800/775/750/700/650/600/550/500/450/400/350/300/250/225/200/175/150/125/100/70/50/30/20/10/7/5/3/2/1
Potential temperature levels: 265/275/285/300/315/320/330/350/370/395/430/475/530/600/700/850
Model levels: 1/to/60, which are described at https://www.ecmwf.int/en/forecasts/documentation-and-support/60-model-levels
Potential vorticity level:
Parameter listings
Tables 1-6 below describe the surface and single level parameters (levtype=sfc), Table 7 describes wave parameters, Table 8 describes the monthly mean exceptions for surface and single level and wave parameters and Tables 9-13 describe upper air parameters on various levtypes. Information on all ECMWF parameters is available from the ECMWF parameter database.
Parameters described as "instantaneous" below, are valid at the specified time.
Instantaneous, invariant, surface and single level parameters table
count | name | an | fc | paramId | units | 1 | Low vegetation cover | x |
| 27 | (0-1) | 2 | High vegetation cover | x |
| 28 | (0-1) | 3 | Low vegetation type (table index - see Table 10.1 in IFS CY31R1 Documentation) | x |
| 29 | index | 4 | High vegetation type (table index - see Table 10.1 in IFS CY31R1 Documentation) | x |
| 30 | index | 5 | Standard deviation of filtered subgrid orography | x |
| 74 | m | 6 | Surface geopotential | x | x | 129 | m2s-2 | 7 | Standard deviation of orography | x |
| 160 | m | 8 | Anisotropy of orography X | x |
| 161 | ~ | 9 | Angle of sub-grid scale orography | x |
| 162 | ~ | 10 | Slope of sub-grid scale orography | x |
| 163 | ~ | 11 | Land-sea mask | x | x | 172 | (0 - 1) |
|
Instantaneous, varying, surface and single level parameters table
count | name | an | fc | paramId | units | 1 | Sea ice fraction | x | x | 31 | (0 - 1) | 2 | Snow albedo | x | x | 32 | (0 - 1) | 3 | Snow density | x | x | 33 | kg m-3 | 4 | Sea surface temperature | x | x | 34 | K | 5 | Sea ice temperature layer 11 | x | x | 35 | K | 6 | Sea ice temperature layer 21 | x | x | 36 | K | 7 | Sea ice temperature layer 31 | x | x | 37 | K | 8 | Sea ice temperature layer 41 | x | x | 38 | K | 9 | Volumetric soil water level 12 | x | x | 39 | m3 m-3 | 10 | Volumetric soil water level 22 | x | x | 40 | m3 m-3 | 11 | Volumetric soil water level 32 | x | x | 41 | m3 m-3 | 12 | Volumetric soil water level 42 | x | x | 42 | m3 m-3 | 13 | Convective available potential energy (CAPE) |
| x | 59 | J kg-1 | 14 | Total column liquid water |
| x | 78 | kg m-2 | 15 | Total column ice water |
| x | 79 | kg m-2 | 16 | Surface pressure3 | x | x | 134 | Pa | 17 | total column water | x | x | 136 | kg m-2 | 18 | total column water vapour | x | x | 137 | kg m-2 | 19 | Soil temperature level 1 | x | x | 139 | K | 20 | Snow depth | x | x | 141 | m of water equivalent | 21 | Charnock parameter | x | x | 148 | ~ | 22 | Mean sea level pressure | x | x | 151 | Pa | 23 | Boundary layer height |
| x | 159 | m | 24 | Total cloud cover | x | x | 164 | (0 - 1) | 25 | 10 metre U wind component | x | x | 165 | m s-1 | 26 | 10 metre V wind component | x | x | 166 | m s-1 | 27 | 2 metre temperature | x | x | 167 | K | 28 | 2 metre dewpoint temperature | x | x | 168 | K | 29 | Soil temperature level 2 | x | x | 170 | K | 30 | Surface roughness | x |
| 173 | m | 31 | Albedo (climate) | x |
| 174 | ~ | 32 | Soil temperature level 3 | x | x | 183 | K | 33 | Low cloud cover | x | x | 186 | (0 - 1) | 34 | Medium cloud cover | x | x | 187 | (0 - 1) | 35 | High cloud cover | x | x | 188 | (0 - 1) | 36 | Skin reservoir content | x | x | 198 | m of water equivalent | 37 | Total column ozone | x | x | 206 | kg m-2 | 38 | Instantaneous eastward turbulent surface stress |
| x | 229 | N m-2 | 39 | Instantaneous northward turbulent surface stress |
| x | 230 | N m-2 | 40 | Instantaneous surface heat flux |
| x | 231 | W m-2 | 41 | Instantaneous moisture flux (evaporation) |
| x | 232 | kg m-2 s | 42 | Log. surface roughness length (m) for heat | x |
| 234 | ~ | 43 | Skin temperature | x | x | 235 | K | 44 | Soil temperature level 4 | x | x | 236 | K | 45 | Temperature of snow layer | x | x | 238 | K | 46 | Forecast albedo |
| x | 243 | ~ | 47 | Forecast surface roughness |
| x | 244 | m | 48 | Forecast logarithm of surface roughness for heat |
| x | 245 | ~ |
1
Layer | Range |
---|
Layer 1 | 0 - 7 cm | Layer 2 | 7 - 28 cm | Layer 3 | 28 - 100 cm | Layer 4 | 100 - 150 cm |
|
2
Layer | Range |
---|
Layer 1 | 0 - 7 cm | Layer 2 | 7 - 28 cm | Layer 3 | 28 - 100 cm | Layer 4 | 100 - 289 cm |
|
3Forecasts are only available up to a range of 12-hours
|
Forecast accumulated surface and single level parameters
count | name | paramId | units | 1 | Clear sky surface photosynthetically active radiation | 20 | W m-2s | 2 | Snow evaporation | 44 | m | 3 | Snow melt | 45 | m | 4 | Large-scale precipitation fraction | 50 | s | 5 | Downward UV radiation at the surface | 57 | W m-2 s | 6 | Surface photosynthetically active radiation | 58 | W m-2 s | 7 | Large-scale precipitation | 142 | m of water | 8 | Convective precipitation | 143 | m of water | 9 | Snowfall | 144 | m of water equivalent | 10 | Boundary layer dissipation | 145 | W m-2 s | 11 | Surface sensible heat flux | 146 | W m-2 s | 12 | Surface latent heat flux | 147 | W m-2 s | 13 | Downward surface solar radiation | 169 | W m-2 s | 14 | Downward surface thermal radiation | 175 | W m-2 s | 15 | Surface solar radiation | 176 | W m-2 s | 16 | Surface thermal radiation | 177 | W m-2 s | 17 | Top solar radiation | 178 | W m-2 s | 18 | Top thermal radiation | 179 | W m-2 s | 19 | East-West turbulent surface stress | 180 | N m-2 s | 20 | North-South turbulent surface stress | 181 | N m-2 s | 21 | East-West gravity wave surface stress | 195 | N m-2 s | 22 | North-South gravity wave surface stress | 196 | N m-2 s | 23 | Gravity wave dissipation | 197 | W m-2 s | 24 | Runoff | 205 | m of water | 25 | Top net solar radiation, clear sky | 208 | W m-2 s | 26 | Top net thermal radiation, clear sky | 209 | W m-2 s | 27 | Surface solar radiation, clear sky | 210 | W m-2 s | 28 | Surface thermal radiation, clear sky | 211 | W m-2 s | 29 | TOA incident solar radiation | 212 | W m-2 s | 30 | Total precipitation | 228 | m of water | 31 | Convective snowfall | 239 | m of water equivalent | 32 | Large-scale snowfall | 240 | m of water equivalent |
|
Forecast minimum/maximum surface and single level parameters
count | name | paramId | units | 1 | Wind gusts at 10 m | 49 | m s-1 | 2 | Max. temp. at 2 m since previous post-processing | 201 | K | 3 | Min. temp. at 2 m since previous post-processing | 202 | K |
|
Vertical single level integrals for budgets
count | name | units | paramId | an | fc | 1 | Vertical integral of mass of atmosphere | kg m-2 | 53 | x | x | 2 | Vertical integral of temperature | K kg m-2 | 54 | x | x | 3 | Vertical integral of water vapour | kg m-2 | 55 | x | x | 4 | Vertical integral of cloud liquid water | kg m-2 | 56 | x | x | 5 | Vertical integral of cloud frozen water | kg m-2 | 57 | x | x | 6 | Vertical integral of ozone | kg m-2 | 58 | x | x | 7 | Vertical integral of kinetic energy | J m-2 | 59 | x | x | 8 | Vertical integral of thermal energy | J m-2 | 60 | x | x | 9 | Vertical integral of potential+internal energy | J m-2 | 61 | x | x | 10 | Vertical integral of potential+internal+latent energy | J m-2 | 62 | x | x | 11 | Vertical integral of total energy | J m-2 | 63 | x | x | 12 | Vertical integral of energy conversion | W m-2 | 64 | x | x | 13 | Vertical integral of eastward mass flux | kg m-1 s-1 | 65 | x | x | 14 | Vertical integral of northward mass flux | kg m-1s-1 | 66 | x | x | 15 | Vertical integral of eastward kinetic energy flux | W m-1 | 67 | x | x | 16 | Vertical integral of northward kinetic energy flux | W m-1 | 68 | x | x | 17 | Vertical integral of eastward heat flux | W m-1 | 69 | x | x | 18 | Vertical integral of northward heat flux | W m-1 | 70 | x | x | 19 | Vertical integral of eastward water vapour flux | kg m-1 s-1 | 71 | x | x | 20 | Vertical integral of northward water vapour flux | kg m-1 s-1 | 72 | x | x | 21 | Vertical integral of eastward geopotential flux | W m-1 | 73 | x | x | 22 | Vertical integral of northward geopotential flux | W m-1 | 74 | x | x | 23 | Vertical integral of eastward total energy flux | W m-1 | 75 | x | x | 24 | Vertical integral of northward total energy flux | W m-1 | 76 | x | x | 25 | Vertical integral of eastward ozone flux | kg m-1 s-1 | 77 | x | x | 26 | Vertical integral of northward ozone flux | kg m-1 s-1 | 78 | x | x | 27 | Vertical integral of divergence of cloud liquid water flux | kg m-2 s-1 | 79 | x | x | 28 | Vertical integral of divergence of cloud frozen water flux | kg m-2 s-1 | 80 | x | x | 29 | Vertical integral of divergence of mass flux | kg m-2 s-1 | 81 | x | x | 30 | Vertical integral of divergence of kinetic energy flux | W m-2 | 82 | x | x | 31 | Vertical integral of divergence of thermal energy flux | W m-2 | 83 | x | x | 32 | Vertical integral of divergence of moisture flux | kg m-2 s-1 | 84 | x | x | 33 | Vertical integral of divergence of geopotential flux | W m-2 | 85 | x | x | 34 | Vertical integral of divergence of total energy flux | W m-2 | 86 | x | x | 35 | Vertical integral of divergence of ozone flux | kg m-2 s-1 | 87 | x | x | 36 | Vertical integral of eastward cloud liquid water flux | kg m-1 s-1 | 88 | x | x | 37 | Vertical integral of northward cloud liquid water flux | kg m-1 s-1 | 89 | x | x | 38 | Vertical integral of eastward cloud frozen water flux | kg m-1 s-1 | 90 | x | x | 39 | Vertical integral of northward cloud frozen water flux | kg m-1 s-1 | 91 | x | x | 40 | Vertical integral of mass tendency | kg m-2 s-1 | 92 | x |
|
|
Wave and gridded ERS altimeter parameters
count | name | units | paramId | an | fc | 20 | Model bathymetry | m | 219 | x |
| 21 | Mean wave period based on first moment | s | 220 | x | x | 22 | Mean wave period based on second moment | s | 221 | x | x | 23 | Wave spectral directional width | ~ | 222 | x | x | 24 | Mean wave period based on first moment for wind waves | s | 223 | x | x | 25 | Mean wave period based on second moment for wind waves | s | 224 | x | x | 26 | Wave spectral directional width for wind waves | ~ | 225 | x | x | 27 | Mean wave period based on first moment for swell | s | 226 | x | x | 28 | Mean wave period based on second moment for swell | s | 227 | x | x | 29 | Wave spectral directional width for swell | ~ | 228 | x | x | 30 | Significant height of combined wind waves and swell | m | 229 | x | x | 31 | Mean wave direction | degrees | 230 | x | x | 32 | Peak wave period | s | 231 | x | x | 33 | Mean wave period | s | 232 | x | x | 34 | Coefficient of drag with waves | ~ | 233 | x | x | 35 | Significant height of wind waves | m | 234 | x | x | 36 | Mean direction of wind waves | degrees | 235 | x | x | 37 | Mean period of wind waves | s | 236 | x | x | 38 | Significant height of total swell | m | 237 | x | x | 39 | Mean direction of total swell | degrees | 238 | x | x | 40 | Mean period of total swell | s | 239 | x | x | 41 | Mean square slope of waves | dimensionless | 244 | x | x | 42 | 10 metre wind speed1 | m s-1 | 245 | x | x | 43 | Gridded ERS altimeter wave height2 | m | 246 | x |
| 44 | Gridded corrected ERS altimeter corrected wave height2 | m | 247 | x |
| 45 | Gridded ERS altimeter range relative correction2 | ~ | 248 | x |
| 46 | 2D wave spectra (single)3 | m2 s radians-1 | 251 | x | x | 47 | Wave spectral kurtosis | ~ | 252 | x | x | 48 | Benjamin-Feir index | ~ | 253 | x | x | 49 | Wave spectral peakedness | s-1 | 254 | x | x |
1Forecasts are also available at a range of 3-hours 2Available from late 1991 3Available for 30 frequencies and 24 directions
|
Monthly mean surface and single level parameters: Exceptions from Tables 1-4
count | name | an | fc | paramId | units | 1 | Magnitude of surface stress (accumulated) |
| x | 48 | N m-2 s | 2 | Wind gusts at 10 m |
| no mean | 49 | m s-1 | 3 | Geopotential | x | no mean | 129 | m-2 s-2 | 4 | Land/sea mask | x | no mean | 172 | (0,1) | 5 | Max. temp. at 2 m since previous post-processing |
| no mean | 201 | K | 6 | Min. temp. at 2 m since previous post-processing |
| no mean | 202 | K | 7 | 10 metre wind speed | x | x | 207 | m s-1 |
|
Accumulated model full levels parameters to validate clear sky radiation
count | name | an | fc | paramId | units | 1 | Short wave radiative tendency | x | x | 100 | K | 2 | Long wave radiative tendency | x | x | 101 | K | 3 | Clear sky short wave radiative tendency | x | x | 102 | K | 4 | Clear sky long wave radiative tendency | x | x | 103 | K |
|
Accumulated model half or model full levels parameters to support chemical transport modelling
count | name | an | fc | paramId | units | Surfaces | 1 | Updraught mass flux | x | x | 104 | kg m-2 | half levels | 2 | Downdraught mass flux | x | x | 105 | kg m-2 | half levels | 3 | Updraught detrainment rate | x | x | 106 | kg m-2 | full levels | 4 | Downdraught detrainment rate | x | x | 107 | kg m-2 | full levels | 5 | Total precipitation profile | x | x | 108 | kg m-2 | half levels | 6 | Turbulent diffusion coefficient for heat | x | x | 109 | m2 | half levels |
|
Accumulated model full levels net tendencies
count | name | an | fc | paramId | units | 1 | T tendency | x | x | 110 | K | 2 | q tendency | x | x | 111 | kg kg-1 | 3 | u tendency | x | x | 112 | m s-1 | 4 | v tendency | x | x | 113 | m s-1 |
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Parameters on isentropic surfaces
count | name | gg1 | sh2 | paramId | units | 1 | Montgomery potential |
| x | 53 | m2 s-2 | 2 | Pressure |
| x | 54 | Pa | 3 | Potential vorticity3 | x |
| 60 | m2 s-1 K kg-1 | 4 | Eastward wind component |
|
| 131 | m s-2 | 5 | Northward wind component |
|
| 132 | m s-2 | 6 | Specific humidity | x |
| 133 | kg/kg | 7 | Vorticity |
| x | 138 | s-1 | 8 | Divergence |
| x | 155 | s-1 | 9 | ozone mass mixing ratio | x |
| 203 | kg/kg |
1Gaussian grid 2Spherical harmonics 3Only PV is archived at 320 K |
Parameters on the PV = ± 2 PVU surface
count | name | paramId | units | 1 | Potential temperature | 3 | K | 2 | Pressure | 54 | Pa | 3 | Geopotential | 129 | m2 s-2 | 4 | Eastward wind component | 131 | m s-2 | 5 | Northward wind component | 132 | m s-2 | 6 | Specific humidity | 133 | kg/kg | 79 | ozone mass mixing ratio | 203 | kg/kg |
|
Observations
The observations (satellite and in-situ) used as input into ERA-Interim are listed in tables below.
Satellite Data
Sensor | Satellite | Satellite agency | Data provider+ | Measurement (sensitivities exploited in ERA5 / variables analysed) |
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Satellite radiances (infrared and microwave) |
|
|
|
|
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AIRS | AQUA | NASA | NOAA | BT (T, humidity and ozone) | AMSRE | AQUA | JAXA |
| BT (column water vapour, cloud liquid water, precipitation and ocean surface wind speed) | AMSUA | NOAA-15/16/17/18/19, AQUA, METOP-A | NOAA,ESA,EUMETSAT |
| BT (T) | AMSUB | NOAA-16/17 | NOAA |
| BT (humidity) | HIRS | METOP-A, NOAA-10/11/12/14/15/16/17/18/19 | NOAA |
| BT (T, humidity and ozone) | MHS | NOAA-18/19, METOP-A | NOAA, EUMETSAT/ESA |
| BT (humidity and precipitation) | MSU | NOAA-10/11/12/14 |
|
| BT (T) | SSM/I | DMSP-8/10/11/13/14/15/16 | US Navy | NOAA,CMSAF | BT (column water vapour, cloud liquid water, precipitation and ocean surface wind speed) | SSMIS | DMSP-16 | US Navy | NOAA | BT (T, humidity, column water vapour, cloud liquid water, precipitation and ocean surface wind speed) | SSU | NOAA-11/14 | NOAA |
| BT (T) | MVIRI | METEOSAT 5/7 | EUMETSAT/ESA | EUMETSAT | BT (water vapour, surface/cloud top T) | SEVIRI | METEOSAT-8/9 | EUMETSAT/ESA | EUMETSAT | BT (water vapour, surface/cloud top T) | GOES IMAGER | GOES-8/9/10/11/12/13/15 | NOAA | CIMMS,NESDIS | BT (water vapour, surface/cloud top T) | MTSAT IMAGER | MTSAT-1R | JMA |
| BT (water vapour, surface/cloud top T) | Satellite retrievals from radiance data |
|
|
|
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MVIRI | METEOSAT-4/5/7 | EUMETSAT/ESA | EUMETSAT | wind vector | SEVIRI | METEOSAT-8/9/10 | EUMETSAT/ESA | EUMETSAT | wind vector | GOES IMAGER | GOES-8/9/10/12 | NOAA | CIMMS,NESDIS | wind vector | GMS IMAGER | GMS-3/4/5 | JMA |
| wind vector | MTSAT IMAGER | MTSAT-1R | JMA |
| wind vector | AHI | Himawari-8 | JMA | JMA | wind vector | AVHRR | NOAA-7 /9/10/11/12/14 to 18, METOP-A | NOAA | CIMMS,EUMETSAT | wind vector | MODIS | AQUA/TERRA | NASA | NESDIS,CIMMS | wind vector | GOME | ERS-2* | ESA |
| Ozone | MIPAS | ENVISAT* | ESA |
| Ozone | MLS | EOS-AURA* | NASA |
| Ozone | OMI | EOS-AURA* | NASA |
| Ozone | SBUV | NIMBUS-7*,NOAA*9/11/14/16/17/18 | NOAA | NASA | Ozone | SCIAMACHY | ENVISAT* | ESA |
| Ozone | TOMS | NIMBUS-7*,METEOR-3,ADEOS-1*,EARTH PROBE | NASA |
| Ozone | Satellite GPS-Radio Occultation data |
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BlackJack | CHAMP | DLR,NASA/DLR,NASA/COMAE | GFZ,UCAR | Bending angle | GRAS | METOP-A | EUMETSAT/ESA | EUMETSAT | Bending angle | IGOR | COSMIC-1 to 6 | NSPO/NOAA | GFZ,UCAR | Bending angle | Satellite Altimeter data |
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RA | ERS-1*/2* | ESA |
| Wave Height | RA-2 | ENVISAT* | ESA |
| Wave Height | Poseidon-2 | JASON-1* | CNES/NASA | CNES | Wave Height |
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In-situ data, provided by WMO WIS
Dataset name | Observation type | Measurement |
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SYNOP | Land station | Surface Pressure, Temperature, wind, humidity | METAR | Land station | Surface Pressure, Temperature, wind,humidity | DRIBU/DRIBU-BATHY/DRIBU-TESAC/BUFR Drifting Buoy | Drifting buoys | 10m-wind, Surface Pressure | BUFR Moored Buoy | Moored buoys | 10m-wind, Surface Pressure | SYNOP SHIP | ship station | Surface Pressure, Temperature, wind, humidity | Land/ship PILOT | Radiosondes | wind profiles | American Wind Profiler | Radar | wind profiles | European Wind Profiler | Radar | wind profiles | Japanese Wind Profiler | Radar | wind profiles | TEMP SHIP | Radiosondes | Temperature, wind, humidity profiles | DROP Sonde | Aircraft-sondes | Temperature, wind profiles | Land/Mobile TEMP | Radiosondes | Temperature, wind, humidity profiles | AIREP | Aircraft data | Temperature, wind profiles | AMDAR | Aircraft data | Temperature, wind profiles | ACARS | Aircraft data | Temperature, wind profiles, humidity | WIGOS AMDAR | Aircraft data | Temperature, wind profiles | Ground based radar | Radar precipitation composites | Rain rates |
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Computation of near-surface humidity and snow cover
Near-surface humidity
Near-surface humidity is not archived directly in ERA datasets, but the archive contains near-surface (2m from the surface) temperature (T), dew point temperature (Td), and surface pressure[1] (sp) from which you can calculate specific and relative humidity at 2m:
- Specific humidity can be calculated over water and ice using equations 6.4 and 6.5 from Part IV, Physical processes section (Chapter 6, section 6.6.1b) in the documentation of the IFS for CY31R1. Use the 2m dew point temperature and surface pressure (which is approximately equal to the pressure at 2m) in these equations.
- Relative humidity should be calculated: RH = 100 * es(Td)/es(T)
The relative humidity can be calculated with respect to saturation over water, ice or mixed phase by defining es(T) with respect to saturation over water, ice or mixed phase (water and ice). The usual practice is to define near-surface relative humidity with respect to saturation over water.
[1] Access to surface pressure varies by dataset. For example, for ERA-Interim surface pressure is available from the Web Interface and from the WebAPI, while for ERA-40 surface pressure is not available from the Web Interface, but only via the WebAPI.
Snow Cover
In the ECMWF model (IFS), snow is represented by an additional layer on top of the uppermost soil level. The whole grid box may not be covered in snow. The snow cover gives the fraction of the grid box that is covered in snow. The method for calculating snow cover depends on the particular version of the IFS and for ERA-Interim is computed directly using snow water equivalent (ie parameter SD (141.128)) as:
The Physical depth of snow where there is snow cover is equal to RW*SD/(RSN*SC) where RSN = density of snow (parameter 33.128). For more in depth information see:
Surface elevation and orography
In ERA-Interim, and often in meteorology, altitudes (the altitude of the land and sea surface, or specific altitudes in the atmosphere) are not represented as geometric altitude (in metres above the spheroid), but as geopotential height (in metres above the geoid). However, ECMWF archive the geopotential (in m2/s2), not the geopotential height.
In order to calculate the geopotential height of the land and sea surface (the so called surface geopotential height, or orography):
In order to define the surface geopotential in ERA-Interim, the ECMWF model uses surface elevation data interpolated from GTOPO30, with some fixes for Antarctica and Greenland. See Chapter 10 Climatological data, of Part IV. Physical processes, of the ERA-Interim model documentation at https://www.ecmwf.int/search/elibrary/part?solrsort=sort_label%20asc&title=part&secondary_title=31r1.
Notes
- The surface geopotential is also available on model levels (at level=1), where it is archived in spectral form.
- Over oceans the surface geopotential field shows 'spectral ripples' (Know issue KI6, see ERA-Interim known issues page for details), which are a reflection of the fact that the ERA-Interim model is a spectral model and the grid point surface geopotential has been spectrally fitted.
- The model levels are hybrid pressure/sigma, eg for ERA-Interim. See Chapter 2 Basic equations and discretization of Part III. Dynamics and numerical procedures, of the ERA-Interim model documentation at https://www.ecmwf.int/search/elibrary/part?solrsort=sort_label%20asc&title=part&secondary_title=31r1.
- The definition of the 60 model levels, for ERA-Interim, and the corresponding half-level, ph, and full-level, pf, values of pressure (for a standard atmosphere with a surface pressure of 1013.250 hPa), geopotential and geopotential heights can be found at http://www.ecmwf.int/en/forecasts/documentation-and-support/60-model-levels
Known issues
Please see the ERA-Interim known issues page for guidance and workarounds.
How to cite ERA-Interim
Please use this as the main scientific reference to ERA-Interim:
Dee, D. P., Uppala, S. M., Simmons, A. J., Berrisford, P., Poli, P., Kobayashi, S., Andrae, U., Balmaseda, M. A., Balsamo, G., Bauer, P., Bechtold, P., Beljaars, A. C. M., van de Berg, L., Bidlot, J., Bormann, N., Delsol, C., Dragani, R., Fuentes, M., Geer, A. J., Haimberger, L., Healy, S. B., Hersbach, H., Hólm, E. V., Isaksen, L., Kållberg, P., Köhler, M., Matricardi, M., McNally, A. P., Monge-Sanz, B. M., Morcrette, J.-J., Park, B.-K., Peubey, C., de Rosnay, P., Tavolato, C., Thépaut, J.-N. and Vitart, F. (2011), The ERA-Interim reanalysis: configuration and performance of the data assimilation system. Q.J.R. Meteorol. Soc., 137: 553–597. doi: 10.1002/qj.828
For a more technical documentation of the contents of the ERA-Interim dataset please use:
Berrisford, P, Dee, DP, Poli, P, Brugge, R, Fielding, K, Fuentes, M, Kållberg, PW, Kobayashi, S, Uppala, S, Simmons, A (2011): The ERA-Interim archive Version 2.0. ERA Report Series 1, http://www.ecmwf.int/en/elibrary/8174-era-interim-archive-version-20
To cite the source of the data, you may use the following data citation:
If no specific advice is given by the journals, it is usually recommended that the above data citation is put in the acknowledgements section.
Reports
2004-2007
2008
2009
2010
2011
2014
References
- Berrisford, P., P. Kållberg, S. Kobayashi, D. Dee, S. Uppala, A. J. Simmons, P. Poli, and H. Sato, 2011: Atmospheric conservation properties in ERA-Interim. Q.J.R. Meteorol. Soc., 137: 1381–1399. doi: 10.1002/qj.864
- Dee, D. P., and Coauthos, 2011: The ERA-Interim reanalysis: configuration and performance of the data assimilation system. Q.J.R. Meteorol. Soc., 137: 553–597. doi:10.1002/qj.828
- Further references available from the ECMWF e-library
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