Introduction

Here we document the ERA5 dataset, which, eventually, will cover the period from January 1950 onwards. Complete ERA5 data released so far covers the period from 1979 and continues to be extended forward in near real time. For up to date information on ERA5, please consult theC3S Announcementson the Copernicus user forum.

ERA5 is produced using 4D-Var data assimilation in CY41R2 of ECMWF’s Integrated Forecast System (IFS), with 137 hybrid sigma/pressure (model) levels in the vertical, 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. The IFS is coupled to a soil model, the parameters of which are also designated as surface parameters, and an ocean wave model.

The ERA5 dataset contains one (hourly, 31 km) high resolution realisation (referred to as "reanalysis" or "HRES") and a reduced resolution ten member ensemble (referred to as "ensemble" or "EDA"). Generally, the data are available at a sub-daily and monthly frequency and consist of analyses and short (18 hour) forecasts, initialised twice daily from analyses at 06 and 18 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.

The data are archived in the ECMWF data archive (MARS) and a pertinent sub-set of the data, interpolated to a regular latitude/longitude grid, has been copied to the C3S Climate Data Store (CDS) disks. On the CDS disks, analyses are provided rather than forecasts, unless the parameter is only available from the forecasts.

ERA5.1 is a re-run of ERA5, for the years 2000 to 2006 only, and was produced to improve upon the cold bias in the lower stratosphere seen in ERA5 during this period.

 An ERA5 back extension 1950-1978 (Preliminary version) has been produced. Although in many other respects the quality is relatively good, this preliminary data does suffer from excessively intense tropical cyclones. This dataset will be available as a separate entry in the CDS catalogue (it will be available in MARS at a later date) for a short period of time, after which it will be deprecated and replaced by a new updated version which will be accessible through the main ERA5 entry. The main entry currently contains data from 1979 onwards.

Data format

Model level fields (see below) are in GRIB2 format. All other fields are in GRIB1, unless otherwise indicated.

In the CDS, there is the option of retrieving the data in netCDF format.

Data update frequency

Initial release data, i.e. data no more than three months behind real time, is called ERA5T.  In the event that serious flaws are detected in ERA5T, this data could be different to the final ERA5 data. In practice, though, this will be very unlikely to occur. Based on experience with the production of ERA5 so far (and ERA-Interim in the past), our expectation is that such an event would not occur more than once every few years, if at all. In the unlikely event that such a correction is required, users will be notified as soon as possible.

For the CDS, daily updates are available about 5 days behind real time and monthly mean updates are available about 5 days after the end of the month.

Note: At the moment the timing of the availability of ERA5T data on the CDS on a daily basis can vary. We do not work to a specific target schedule. However, the D-5 data are typically available by 12UTC, but not guaranteed. We are working on reducing the variability of the time of availability, but this may take several months to achieve.

For MARS ERA5 data, monthly updates are available about two months after the month in question.

For GRIB data, ERA5T can be identified by the key expver=0005 in the GRIB header. ERA5 is identified by the key expver=0001.

For netCDF data requests which return just ERA5 or just ERA5T data, there is no means of differentiating between ERA5 and ERA5T data in the resulting netCDF files.

For netCDF data requests which return a mixture of ERA5 and ERA5T data, the origin of the variables (1 or 5) will be identifiable in the resulting netCDF files. See the link for more details.

The IFS and data assimilation

For ERA5, the IFS documentation for CY41R2 should be used.

The 4D-Var data assimilation uses 12 hour windows from 09 UTC to 21 UTC and 21 UTC to 09 UTC (the following day).

The model time step is 12 minutes for the HRES and 20 minutes for the EDA, though occasionally these numbers are adjusted to cope with instabilities.

Data organisation and how to download ERA5

The full ERA5 and ERA5T datasets are held in the ECMWF data archive (MARS) and a pertinent sub-set of these data, interpolated to a regular latitude/longitude grid, has been copied to the C3S Climate Data Store (CDS) disks. ERA5.1 is not available from the CDS disks. On the CDS disks, where single level and pressure level data are available, analyses are provided rather than forecasts, unless the parameter is only available from the forecasts.

Data on the CDS disks provides the fastest access to ERA5 data.

Documentation is available on How to download ERA5.

Date and time specification

In MARS: the date and time of the data is specified with three MARS keywords, date, time and step. For analyses, step=0 hours so that date and time specify the analysis date/time. For forecasts, date and time specify the forecast start time and step specifies the number of hours since that start time. The combination of date, time and forecast step defines the validity date/time. For analyses, the validity date/time is equal to the analysis date/time.

In the CDS: analyses are provided rather than forecasts, unless the parameter is only available from the forecasts. The date and time of the data is specified using the validity date/time, so step does not need to be specified. For forecasts, steps between 1 and 12 hours have been used to provide data for all the validity times in 24 hours, see Table 0 below.

Spatial grid

The ERA5 HRES atmospheric data has a resolution of 31km, 0.28125 degrees, and the EDA has a resolution of 63km, 0.5625 degrees. (Depending on the parameter, the data are archived either as spectral coefficients with a triangular truncation of T639 (HRES) and T319 (EDA) or on a reduced Gaussian grid with a resolution of N320 (HRES) and N160 (EDA). These grids are so called "linear grids", sometimes referred to as TL639 (HRES) and TL319 (EDA).)

The wave data are produced and archived on a different grid to that of the atmospheric model, namely a reduced latitude/longitude grid with a resolution of 0.36 degrees (HRES) and 1.0 degrees (EDA).

ERA5 data available from the CDS disks has been pre-interpolated to a regular latitude/longitude grid appropriate for that data.

The article Model grid box and time step might be useful.

Temporal frequency

For sub-daily data for the HRES (stream=oper/wave) the analyses (type=an) are available hourly. The short forecasts, run twice daily from 06 and 18 UTC, provide hourly output forecast steps from 0 to 18 hours. For the EDA, the sub-daily non-wave data (stream=enda) are available every 3 hours but the sub-daily wave data (stream=ewda) are available hourly.

Wave spectra

The ERA5 wave model uses wave spectra with 24 directions and 30 frequencies (see "2D wave spectra (single)", Table 7),

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')

Instantaneous parameters

All the analysed parameters and many of the forecast parameters are described as "instantaneous". For more information on what this means, see Parameters valid at the specified time.

Mean rates and accumulations

The accumulations (over the processing period) in the short forecasts (from 06 and 18 UTC) of ERA5 are treated differently compared with those in ERA-Interim and operational data (where the accumulations are from the beginning of the forecast to the validity date/time). In the short forecasts of ERA5, the accumulations are since the previous post processing (archiving), so for:

• reanalysis: accumulations are over the hour (the processing period) ending at the validity date/time
• ensemble: accumulations are over the 3 hours (the processing period) ending at the validity date/time
• Monthly means (of daily means, stream=moda/edmo): accumulations have been scaled to have an "effective" processing period of one day, see section Monthly means

Mean rate parameters in ERA5 (e.g. Table 4) provide similar information to accumulations (Table 3), over the same processing periods, but they have different units which include "per second".

• Mean rate parameters are easier to deal with than accumulations because the units do not vary with the processing period.
• The mean rate hydrological parameters (e.g. the "Mean total precipitation rate") have units of "kg m-² s^-1", which are equivalent to "mm s^-1". If you multiply by 86400 seconds (24 hours) you will produce the commonly used units of "mm day^-1".

Note that:

• For the CDS time, or validity time, of 00 UTC, the mean rates and accumulations are over the hour (3 hours for the EDA) ending at 00 UTC i.e. the mean or accumulation is during the previous day.
• Mean rates and accumulations are not available from the analyses.
• Mean rates and accumulations at step=0 have values of zero because the length of the processing period is zero.

Minimum/maximum since the previous post processing

The short forecasts of ERA5 contain some surface and single level parameters that are the minimum or maximum value since the previous post processing (archiving), see Table 5 below. So, for:

• reanalysis: the minimum or maximum values are in the hour (the processing period) ending at the validity date/time
• ensemble: the minimum or maximum values are in the 3 hours (the processing period) ending at the validity date/time

Monthly means

In addition to the sub-daily data, most parameters are also available as monthly means. For the surface and single level parameters, there are some exceptions which are listed in Table 8.

Monthly means are available in two forms:

• Synoptic monthly means, for each particular time and forecast step (stream=mnth/wamo/edmm/ewmm) - in the CDS, referred to as "monthly averaged by hour of day".
• Monthly means (of daily means, stream=moda/wamd/edmo/ewmo) for the month as a whole - in the CDS, referred to as "monthly averaged". These monthly means are created from all the hourly (3 hourly for the ensemble) data in the month.

Monthly means for:

• forecast parameters are created using the first 12 hours of the twice daily short forecasts (beginning at 06 and 18 UTC).
• analysis and instantaneous forecast parameters are created from data with a validity time in the month, between 00 and 23 UTC, which excludes the time 00 UTC on the first day of the following month.
• accumulation and mean rate forecast parameters are created from data with a processing period falling within the month. Therefore, monthly means of daily means for accumulations and mean rates are created from contiguous data with processing periods spanning from 00 UTC on the first day of the month to 00 UTC on the first day of the following month.

The accumulations in monthly means (of daily means, stream=moda/edmo) have been scaled to have an "effective" processing period of one day, so for accumulations in these streams:

• The hydrological parameters have effective units of "m of water per day" and so they should be multiplied by 1000 to convert to kgm^-2day^-1 or mmday^-1.
• The energy (turbulent and radiative) and momentum fluxes should be divided by 86400 seconds (24 hours) to convert to the commonly used units of Wm^-2 and Nm^-2, respectively.

Ensemble means and standard deviations

For the EDA sub-daily data (stream=enda/ewda), compared with HRES sub-daily data (stream=oper/wave), there are also ensemble means and standard deviations (type=em/es).

Ensemble standard deviation is often referred to as ensemble spread and is calculated as the standard deviation of the 10-members in the ensemble (i.e., including the control). It is not the sample stdv, so we divide by 10 rather than 9 (N-1). 

Ensemble means and standard deviations contain analysed parameters when step=0, otherwise they contain forecast parameters. However, only surface and pressure level data (levtype=sfc/pl) contain forecast steps beyond 3 hours. There are no monthly means for ensemble means and standard deviations.

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

Potential vorticity level: 2000

Model levels: 1/to/137, which are described at https://www.ecmwf.int/en/forecasts/documentation-and-support/137-model-levels.

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 (e.g. columns shortName and paramId) is available from the ECMWF parameter database.

Note: If a parameter name listed in the tables below does not have a Variable name in CDS, this means that this particular parameter is only available from the ECMWF MARS tape archive using CDS-API (see Data Organisation section above).

Parameters described as "invariants" below, are invariant in time.

Parameters described as "instantaneous"  below, are valid at the specified time.

Table 1: surface and single level parameters: invariants

(stream=oper/enda/mnth/moda/edmm/edmo, levtype=sfc)

*Soil type (texture) determines the saturation, field capacity and permanent wilting point at all the soil levels, see Table 8.9 in Chapter 8 Surface parametrization, Part IV Physical Processes of the IFS documentation (CY41R2 for ERA5).

Table 2: surface and single level parameters: instantaneous

(stream=oper/enda/mnth/moda/edmm/edmo, levtype=sfc)

¹

*GRIB2 format

Table 3: surface and single level parameters: accumulations

(stream=oper/enda/mnth/moda/edmm/edmo, levtype=sfc)

Accumulations are described in section Mean rates and accumulations. The accumulations in monthly means of daily means (stream=moda/edmo) have been scaled to have units that include "per day", so for accumulations in these streams:

• Most hydrological parameters are in units of "m of water per day", so these should be multiplied by 1000 to convert to kg m^-2 day^-1 or mm day^-1.
• Energy (turbulent and radiative) and momentum fluxes should be divided by 86400 seconds (24 hours) to convert to the commonly used units of W m^-2 and N m^-2, respectively.

Table 4: surface and single level parameters: mean rates

(stream=oper/enda/mnth/moda/edmm/edmo, levtype=sfc)

The mean rates in Table 4 provide similar information to the accumulations in Table 3, except that they are expressed as temporal averages instead of accumulations, and so have units of "per second". The hydrological parameters are in units of "kg m^-2 s^-1" and so they can be multiplied by 86400 seconds (24 hours) to convert to kg m^-2 day^-1 or mm day^-1.

Table 5: surface and single level parameters: minimum/maximum

(stream=oper/enda, levtype=sfc)

Table 6: surface and single level parameters: vertical integrals and total column: instantaneous

(stream=oper/enda/mnth/moda/edmm/edmo - vertical integrals not available for type=em/es, levtype=sfc

Table 7: wave parameters: instantaneous

(stream=wave/ewda/wamo/wamd/ewmm/ewmo)

*for 30 frequencies and 24 directions

Table 8: monthly mean surface and single level and wave parameters: exceptions from Tables 1-7

(stream=mnth/moda/edmm/edmo, levtype=sfc or wamo/wamd/ewmm/ewmo)

Table 9: pressure level parameters: instantaneous

(stream=oper/enda/mnth/moda/edmm/edmo, levtype=pl)

Table 10: potential temperature level parameters: instantaneous

(stream=oper/enda/mnth/moda/edmm/edmo, levtype=pt)

Table 11: potential vorticity level parameters: instantaneous

(stream=oper/enda/mnth/moda/edmm/edmo, levtype=pv)

Table 12: model level parameters: instantaneous

(stream=oper/enda/mnth/moda/edmm/edmo, levtype=ml)

*Only archived on level=1.

Table 13: model level parameters: mean rates

(stream=oper/enda/mnth/moda/edmm/edmo, levtype=ml)

*These parameters provide data for the model half levels, at the interfaces of the model layers.

Observations

The observations(satellite and in-situ) used as input into ERA5 are listed below.

Table 14: Satellite Data

* reprocessed dataset
+ when different than the satellite agency

Table 15: In-situ data, provided by WMO WIS

Table 16: Snow data

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 7.4 and 7.5 from Part IV, Physical processes section (Chapter 7, section 7.2.1b) in the documentation of the IFS for CY41R2. Use the 2m dew point temperature and surface pressure (which is approximately equal to the pressure at 2m) in these equations. The constants in 7.4 are to be found in Chapter 12 (of Part IV: Physical processes) and the parameters in 7.5 should be set for saturation over water because the dew point temperature is being used.
• Relative humidity should be calculated: RH = 100 * es(Td)/es(T)

 Relative humidity can be calculate 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.

For ERA5, the snow cover (SC) is computed using snow water equivalent (ie parameter SD (141.128)) as follows:

ERA5 physical depth of snow where there is snow cover is equal to RW*SD/(RSN*SC).

Guidelines

The following advice is intended to help users understand particular features of the ERA5 data:

• Sea surface temperature and sea-ice cover (see Table 2 above) are available at the usual times, eg hourly for the HRES, but their content is only updated once daily.
• Mean rates and accumulations at step=0 have values of zero because the length of the processing period is zero.

Known issues

Currently, we are aware of these issues with ERA5:

• ERA5 uncertainty: although small values of ensemble spread correctly mark more confident estimates than large values, numerical values are over confident. The spread does give an indication of the relative, random uncertainty in space and time.

• ERA5 suffers from an overly strong equatorial mesospheric jet, particularly in the transition seasons.

• From 2000 to 2006, ERA5 has a poor fit to radiosonde temperatures in the stratosphere, with a cold bias in the lower stratosphere. In addition, a warm bias higher up persists for much of the period from 1979. The lower stratospheric cold bias was rectified in a re-run for the years 2000 to 2006, called ERA5.1, see "Resolved issues" below.

• Discontinuities in ERA5Discontinuities in ERA5: ERA5 is produced by several parallel experiments, each for a different period, which are then appended together to create the final product. This can create discontinuities at the transition points.
  
• The analysed "2 metre temperature" can be larger than the forecast "Maximum temperature at 2 metres since previous post-processing".The analysed "2 metre temperature" can be larger than the forecast "Maximum temperature at 2 metres since previous post-processing".
• The analysed 10 metre wind speed (derived from the 10 metre wind components) can be larger than the forecast "10 metre wind gust since previous post-processing".
• ERA5 diurnal cycle for winds: the hourly data reveals a mismatch in the analysed near surface wind speed between the end of one assimilation cycle and the beginning of the next (which occurs at 9:00 and 21:00 UTC). This problem mostly occurs in low latitude oceanic regions, though it can also be seen over Europe and the USA. We cannot rectify this problem in the analyses. The forecast near surface winds show much better agreement between the assimilation cycles, at least on average, so if this mismatch is problematic for a particular application, our advice would be to use the forecast winds. The forecast near surface winds are available from MARS, see the above section, Data organisation and how to download ERA5.
  
• ERA5: large 10m windsERA5: large 10m winds: up to a few times per year, the analysed low level winds, eg 10m winds, become very large in a particular location, which varies amongst a few apparently preferred locations. The largest values seen so far are about 300 ms^-1.
  
• ERA5 rain bombs: from time to time, the rainfall (precipitation) can become extremely large in small areas.
• Large values of CAPE: occasionally, the Convective available potential energy in ERA5 is unrealistically large.
• Ship tracks in the SST: prior to September 2007, in the period when HadISST2 was used, ship tracks can be visible in the SST.
• Prior to 2014, the SST was not used over the Great Lakes to nudge the lake model. Consequently, the 2 metre temperature has an annual cycle that is too strong, with temperatures being too cold in winter and too warm in summer.
• Wind values are far too low on pressure levels at the poles in the Climate Data Store (CDS)Wind values are far too low on pressure levels at the poles in the Climate Data Store (CDS)
  
• The Potential Evaporation field (pev, parameter Id 228251) is largely underestimated over deserts and high-forested areas. This is due to a bug in the code that does not allow transpiration in case no low vegetation type is present.
• Wave parameters (Table 7 above) for the three swell partitions: these parameters have been calculated incorrectly. The problem is most evident in the swell partition parameters involving the mean wave period: Mean wave period of first swell partition, Mean wave period of second swell partition and Mean wave period of third swell partition, where the periods are far too long.
• ERA5 surface photosynthetically available radiation (PAR) is too low, so surface PAR and clear sky surface PAR have not been published. ERA5 is produced by the ECMWF Integrated Forecasting System (IFS), which we suspect has a bug in the calculation of surface PAR in that it looks like it is taken from the wrong parts of the spectrum. We have shortwave bands that include 0.442-0.625 micron, 0.625-0.778 micron and 0.778-1.24 micron. PAR is coded as if it was intending to sum all of the radiation in the first of these and 0.42 of the second (to account for the fact that PAR is normally defined to stop at 0.7 microns. However, PAR is in fact calculated from the sum of the second band plus 0.42 of the third. We will try to fix this in a future cycle, but it is not possible to correct previously released data.

• 
  

  ERA5 has output analysis values for the instantaneous surface stress components and friction velocity. There is however an issue with those analysis values over the oceans. The analysis for those type of surface parameters is obtained by running the surface module to connect the surface with the model level analysed variables. However, at that stage, the surface aero-dynamical roughness length scale (z0) over the oceans is not initialised from its actual value but a constant value of 0.0001 is used instead. This initial value for z0 is generally too low ( by one order of magnitude or more): Over the oceans, for winds above few m/s, z0 is modelled using the Charnock relation: z0 ~ (alpha/g) u*^2 where alpha is the Charnock parameter, g is gravity, and u* is the friction velocity with typical values of alpha ~ 0.018 g=9.81 u*^2 = Cd U10^2 where Cd is the drag coefficient Cd ~ 0.008 + 0.0008 U10 for U10=10m/s =>  z0 ~ 0.003 As a consequence, the instantaneous surface stress components and friction velocity will tend to be too low For forecast data, the same problem affects step 0, however, it will not affect the accumulated surface stress parameters (recall the accumulated parameters are produced by running short range forecasts), because, the accumulation starts from the first time step (i.e. at time step 0 all accumulated variables are initialised to 0.). Note that this problem can easily be fixed, by using the initial value of Charnock that is available at initial time.

  
  

• ERA5 back extension 1950-1978 (Preliminary version): tropical cyclones are too intense
• ERA5 back extension 1950-1978 (Preliminary version): large bias in surface analysis over Australia prior to 1970
• ERA5 back extension 1950-1978 (Preliminary version): the deep soil moisture tends to be too dry

Resolved issues

• Wrong values of U/V on pressure levels in the Climate Data Store (CDS)
  

• ERA5.1 is a re-run of ERA5, for the years 2000 to 2006 only, and was produced to improve upon the cold bias in the lower stratosphere seen in ERA5.

  ERA5.1 is a re-run of ERA5 for the years 2000 to 2006 only. ERA5.1 was produced to improve upon the cold bias in the lower stratosphere exhibited by ERA5 during this period. Moreover, ERA5.1 analyses have a better representation of the following features: upper stratospheric temperature stratospheric humidity The lower and middle troposphere in ERA5.1 are similar to those in ERA5, as is the synoptic evolution in the extratropical stratosphere. For access to ERA5.1 data read Data organisation and how to download ERA5. The dataset is 'reanalysis-era5.1-complete' in the CDS API.

  
  

• If you retrieved ERA5.1 from the CDS anytime before 20/05/2020 08:00 UTC for any stream other than oper (i.e. streams: wave, enda, edmo, ewmo, edmm, ewmm, ewda, moda, wamd, mnth, wamo) you will need to request the data again. Prior to this date, stream oper would be delivered regardless of which stream was requested.

User support

There is a range of user support available for ERA5, including a Knowledge Base (where this article resides), a Forum and a ticketed system for questions - for more information see the C3S Help and Support Page.

How to acknowledge and cite ERA5

• If you have downloaded ERA5 data interactively from the Climate Data Store website or programmatically using the CDS API service (except 'reanalysis-era5-complete' or 'reanalysis-era5.1-complete), then please proceed as follows:

• If you have downloaded ERA5 data from the complete archive, physically stored on the MARS Tape archive system using the CDS-API ('reanalysis-era5-complete' or 'reanalysis-era5.1-complete) or via authorised access to MARS, then please contact the C3S Helpdesk at ECMWF.

Please refer to How to acknowledge, cite and reference data published on the Climate Data Store for complete details.

References

The ERA5 global reanalysis

Global stratospheric temperature bias and other stratospheric aspects of ERA5 and ERA5.1

Further ERA5 references are available from the ECMWF e-Library.

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