Introduction
Here we document the ERA5-Land dataset that, in its consolidated version, covers the period from January 1950 to 2-3 months before the present. In addition, the ERA5-Land-T version delivers non-checked close to Near-Real-Time (NRT) daily updates. ERA5-Land-T is synchronized with the close to NRT daily updates provided by the ERA5 climate reanalysis (ERA5T).
ERA5-Land is a replay of the land component of the ERA5 climate reanalysis, forced by meteorological fields from ERA5. Note that ERA5-Land always uses forcing fields based on the final release of ERA5 (i.e., expver=0001). ERA5-Land comes with a series of improvements making it more accurate for all types of land applications. In particular, ERA5-Land runs at enhanced resolution (9 km vs 31 km in ERA5). The temporal frequency of the output is hourly and the fields are masked for all oceans, making them lighter to handle. Click this link here for comparison of the ERA5-Land features against other ECMWF reanalyses.
ERA5-Land is produced under a single simulation, without coupling to the atmospheric module of the ECMWF's Integrated Forecasting System (IFS) or to the ocean wave model of the IFS. It runs without data assimilation, making it computationally affordable for relatively quick updates. For example, if significant improvements of the land surface model are implemented, the whole or part of the dataset can be reprocessed in a relatively short period. Also, updates are possible in case improved auxiliary datasets are used as input for the production.
Observations indirectly influence the simulation through the atmospheric forcing of ERA5. This forcing drives the ERA5-Land single simulation and it has been obtained by assimilating observations through a 4D-VAR data assimilation system and a Simplified Extended Kalman Filter.
The core of ERA5-Land is the Tiled ECMWF Scheme for Surface Exchanges over Land incorporating land surface hydrology (H-TESSEL). It uses version CY45R1 of the IFS.
Currently, ERA5-Land dataset contains only one (9 km) high resolution realisation (HRES). Uncertainty information can currently be used from the reduced resolution ten member ensemble (EDA) of ERA5. The data are available at a sub-daily and monthly frequencies. For convention and consistency with the previous ERA-Interim/Land dataset, the data parameters are labelled as analyses and short (24 hour) forecasts initialised once daily from analyses at 00 UTC. Accumulation parameters are only available from the forecasts and the convention used in ERA5-Land differs from that for ERA5.
Currently, the data can only be downloaded on a regular latitude/longitude grid of 0.1°x0.1° via the CDS catalogue. ECMWF member states with access to the ECMWF Meteorological Archival and Retrieval System (MARS) can also retrieve the data in the native grid.
NOTE: Please, note that since 1st Jan 2020 the new ECMWF Meteorological Interpolation and Regridding interpolation package (MIR) has been used to interpolate the atmospheric forcing of ERA5 into the ERA5-Land grid. While this change will be unnoticeable for the overwhelming majority of users, locally and under very limited conditions (some areas with high orography, some coastal points) some fields may suffer of a very small discontinuity this day.
Land Surface Model
H-TESSEL is the land surface model that is the basis of ERA5-Land. The H-TESSEL version used in the production of ERA5-Land corresponds to that of the IFS model documentation CY45R1.
Data organisation and access
The full ERA5-Land and ERA5-Land-T data are archived in the ECMWF data archive (MARS) and the data have been copied to the Climate Data Store (CDS). ERA5-Land (or recent ERA5-Land-T) data should be downloaded using the CDS catalogue or the CDS API, which can obtain data from the CDS copy or from MARS (Member State users can access the data using MARS directly, in the usual manner). Documentation on how to use the CDS API to download ERA5-Land data can be found here. The installation and downloading steps are similar to those of ERA5.
A couple of downloading examples to extract the data using the CDS API are given below:
Convention used in MARS: the date and time of the data is specified with three MARS keywords, 'date', 'time' and 'step'. For parameters labelled as analyses (see list of parameters), step=0 hours so that date and time specify the analysis time. All forecasts start at 00UTC (time=00 hours), and for parameters labelled as forecasts (see list of parameters), date specifies the forecast start day and step specifies the number of hours since the start of the forecast, with a maximum of step=24 hours. 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.
Convention used in the CDS: 'analyses' are provided if available for a particular parameter, otherwise forecasts are provided. The date and time of the data is specified using the validity date/time, so step does not need to be specified. For parameters labelled as forecasts in MARS, steps between 1 and 24 hours have been used to provide data for all the validity times within 24 hours, see Table 0 below.
Table 0: the mapping, for forecasts, between MARS date, time and step and the CDS date and time
CDS date time | MARS date time step | CDS date time | MARS date time step | |
---|---|---|---|---|
date 00 | date-1 0 24 | date 12 | date 0 12 | |
date 01 | date 0 1 | date 13 | date 0 13 | |
date 02 | date 0 2 | date 14 | date 0 14 | |
date 03 | date 0 3 | date 15 | date 0 15 | |
date 04 | date 0 4 | date 16 | date 0 16 | |
date 05 | date 0 5 | date 17 | date 0 17 | |
date 06 | date 0 6 | date 18 | date 0 18 | |
date 07 | date 0 7 | date 19 | date 0 19 | |
date 08 | date 0 8 | date 20 | date 0 20 | |
date 09 | date 0 9 | date 21 | date 0 21 | |
date 10 | date 0 10 | date 22 | date 0 22 | |
date 11 | date 0 11 | date 23 | date 0 23 |
Spatial grid
The ERA5-Land HRES dataset has been produced at a resolution of 9 km, (~0.08°) and in a (octahedral) reduced Gaussian grid (represented as TCo1279). Currently, the uncertainty of the fields is to be obtained from the ERA5 EDA dataset, which has a resolution of 62km (~0.56°).
The article "Model grid box and time step" might be useful.
The data is referenced in the horizontal with respect to the WGS84 ellipse (which defines the major/minor axes) and in the vertical it is referenced to the EGM96 geoid over land but over ocean it is referenced to mean sea level, with the approximation that this is assumed to be coincident with the geoid. For more information on the relationship between mean sea level and the geoid, see for example Gregory et al. (2019).
Temporal frequency
For sub-daily data for the HRES (stream=oper) the parameters labelled as analyses (type=an) are available hourly. The once daily short forecasts, run from 00 UTC, also provide data hourly, with steps from 01 to 24. The uncertainty is currently provided by ERA5 EDA fields, which are available every 3 hours for the surface fields.
Data update frequency
Initial release data, i.e. data with just a few days behind real time, is called ERA5-Land-T. Both for the CDS and MARS, daily updates for ERA5-Land-T are available about 5 days behind real time and monthly mean updates are available about 5 days after the end of the month.
The daily updates for ERA5-Land-T data on the CDS occur at no fixed time during the day.
For the CDS, ERA5-Land-T data for a month is overwritten by the final ERA5-Land data about two months after the month in question.
For MARS, the final ERA5-Land data are available about two months after the month in question. In addition, the last few months of data are kept online and can be accessed much quicker than older data on tape.
In the event that serious flaws are detected in ERA5-Land-T, the latter could be different to the final consolidated ERA5-Land data. Based on experience with the production of ERA5-Land so far, our expectation is that such an event would occur only when a flaw in the atmospheric forcing (from ERA5) is detected, and the expectation is that the latter occur only on rare occasions.
Accumulations
Please, note that the convention for accumulations used in ERA5-Land differs with that for ERA5. The accumulations in the short forecasts of ERA5-Land (with hourly steps from 01 to 24) are treated the same as those in ERA-Interim or ERA-Interim/Land, i.e., they are accumulated from the beginning of the forecast to the end of the forecast step. For example, runoff at day=D, step=12 will provide runoff accumulated from day=D, time=0 to day=D, time=12. The maximum accumulation is over 24 hours, i.e., from day=D, time=0 to day=D+1,time=0 (step=24).
- HRES: accumulations are from 00 UTC to the hour ending at the forecast step
- For the CDS time, or validity time, of 00 UTC, the accumulations are over the 24 hours ending at 00 UTC i.e. the accumulation is during the previous day
- Synoptic monthly means (stream=mnth): accumulations have units of "variable_units per forecast_step hours"
- Monthly means of daily means (stream=moda): accumulations have units that include "per day", see section Monthly means
Monthly means
In addition to the sub-daily data, all ERA5-Land parameters are also available as monthly means. Monthly means are available in two forms:
- Synoptic monthly means, for each particular time and forecast step (stream=mnth) - in the CDS, referred to as "monthly averaged by hour of day".
- Monthly means of daily means, for the month as a whole (stream=moda) - in the CDS, referred to as "monthly averaged". These monthly means are created from the hourly data for the HRES.
Monthly means for:
- parameters labelled as analyses or instantaneous forecasts are created from data with a valid time in the month, between 00 and 23 UTC on each day of the month.
- accumulations are created from data with a forecast period falling within the month. Monthly means of daily means for accumulations are created from the last forecast step (24) of the forecasts for each day of the month.
The accumulations in monthly means of daily means (stream=moda) have units that include "per day". So for accumulations in this stream:
- The hydrological parameters are in units of "m of water equivalent 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.
The accumulations in synoptic monthly means (stream=mnth) have units that include "variable_units per forecast_step hours". So for accumulations in this stream:
- The hydrological parameters are in units of "m of water equivalent per forecast_step hours" and so they should be multiplied by 1000 to convert to kgm-2 per forecast_step hours or mm per forecast_step hours.
- The energy (turbulent and radiative) and momentum fluxes should be divided by 60 x 60 x fc_step to convert to the units of Wm-2 and Nm-2, respectively.
Data format
Surface fields in ERA5-Land are encoded either in GRIB1 or GRIB2 format. Tables 1 and 2 indicate the format for all parameters in ERA5-Land. Note that the retrieval of the data in NetCDF format is still an option available via the CDS.
The article "What are GRIB files and how can I read them" might be helpful.
For GRIB format, ERA5-Land-T data can be identified by the key expver=0005 in the GRIB header. Consolidated ERA5-Land data is identified by the key expver=0001.
For netCDF data requests which return just ERA5-Land or just ERA5-Land-T data, there is no means of differentiating between ERA5-Land and ERA5-Land-T data in the resulting netCDF files.
For netCDF data requests which return a mixture of ERA5-Land and ERA5-Land-T data, the origin of the variables (1 or 5) will be identifiable in the resulting netCDF files. See this link for more details applied to ERA5 data.
Parameter listings
Tables 1 and 2 below describe the surface parameters available in ERA5-Land (levtype=sfc). Information on all ECMWF parameters is available from the ECMWF parameter database.
For the sake of completeness, most of the forcing fields used to run ERA5-Land are included in the catalogue. Note, however, that these fields have purely been interpolated to the ERA5-Land grid and they are not obtained by running the land surface model (i.e., a purely linear interpolation based on a triangular mesh). They are included in Table 1 and Table 2 below under the column "Used as forcing field".
Auxiliary land invariant parameters are attached here below, already interpolated to a regular lat/lon grid of 0.1°x0.1°. Relevant information about how to use/interpret these fields are in chapter 8 of https://www.ecmwf.int/en/elibrary/18714-ifs-documentation-cy45r1-part-iv-physical-processes, and plots of these fields are in chapter 11.
Parameters described as "instantaneous" in Table 2 are valid at the specified time.
Note that in the tables below, "an" and "fc" is just a label used for convention to archive the data in MARS.
Table 1: surface parameters: invariants (in time)
name | download link | units | shortName | paramId | GRIB1 | GRIB2 | netCDF4 |
---|---|---|---|---|---|---|---|
Geopotential (GRIB version 1) Geopotential(GRIB version 2) Geopotential (netCDF4) | m**2 s**-2 | z | 129 | x | x | x | |
Lake cover (GRIB version 2) Lake cover (netCDF4) | (0-1) | cl | 26 | x | x | ||
m | dl | 228007 | x | x | |||
Land-sea-mask (GRIB version 2) Land-sea mask (netCDF4) | (0-1) | lsm | 172 | x | x | ||
Low vegetation cover (GRIB version 2) Low vegetation cover (netCDF4) | (0 - 1) | cvl | 27 | x | x | ||
High vegetation cover (GRIB version 2) High vegetation cover (netCDF4) | (0 - 1) | cvh | 28 | x | x | ||
Glacier mask (GRIB version 2) Glacier mask (netCDF4) | Proportion | glm | 260294 | x | x | ||
Soil type (GRIB version 2) Soil type (netCDF4) | ~ | slt | 43 | x | x | ||
Type of low vegetation (GRIB version 1) Type of low vegetation (netCDF4) | ~ | tvl | 29 | x | x | ||
Type of high vegetation (GRIB version 1) Type of high vegetation (netCDF4) | ~ | tvh | 30 | x | x |
Table 2: stream=oper/mnth/moda, levtype=sfc: surface parameters: instantaneous
name | units | Variable name in CDS | shortName | paramId | an | fc | GRIB1 | GRIB2 | Used as forcing field | |
---|---|---|---|---|---|---|---|---|---|---|
1 | K | lake_mix_layer_temperature | lmlt | 228008 | x | x | ||||
2 | m | lake_mix_layer_depth | lmld | 228009 | x | x | ||||
3 | K | lake_bottom_temperature | lblt | 228010 | x | x | ||||
4 | K | lake_total_layer_temperature | ltlt | 228011 | x | x | ||||
5 | dimensionless | lake_shape_factor | lshf | 228012 | x | x | ||||
6 | K | lake_ice_temperature | lict | 228013 | x | x | ||||
7 | m | lake_ice_depth | licd | 228014 | x | x | ||||
8 | Snow cover | % | snow_cover | snowc | 260038 | x | x | |||
9 | Snow depth | m | snow_depth | sde | 3066 | x | x | |||
10 | (0 - 1) | snow_albedo | asn | 32 | x | x | ||||
11 | kg m**-3 | snow_density | rsn | 33 | x | x | ||||
12 | m**3 m**-3 | volumetric_soil_water_layer_1 | swvl1 | 39 | x | x | ||||
13 | m**3 m**-3 | volumetric_soil_water_layer_2 | swvl2 | 40 | x | x | ||||
14 | m**3 m**-3 | volumetric_soil_water_layer_3 | swvl3 | 41 | x | x | ||||
15 | m**3 m**-3 | volumetric_soil_water_layer_4 | swvl4 | 42 | x | x | ||||
16 | m**2 m**-2 | leaf_area_index_low_vegetation | lai_lv | 66 | x | x | ||||
17 | m**2 m**-2 | leaf_area_index_high_vegetation | lai_hv | 67 | x | x | ||||
18 | Pa | surface_pressure | sp | 134 | x | x | x | |||
19 | K | soil_temperature_level_1 | stl1 | 139 | x | x | ||||
20 | m of water equivalent | snow_depth_water_equivalent | sd | 141 | x | x | ||||
21 | m s**-1 | 10m_u_component_of_wind | u10 | 165 | x | x | x | |||
22 | m s**-1 | 10m_v_component_of_wind | v10 | 166 | x | x | x | |||
23 | K | 2m_temperature | 2t | 167 | x | x | ||||
24 | K | 2m_dewpoint_temperature | 2d | 168 | x | x | ||||
25 | K | soil_temperature_level_2 | stl2 | 170 | x | x | ||||
26 | K | soil_temperature_level_3 | stl3 | 183 | x | x | ||||
27 | m of water equivalent | skin_reservoir_content | src | 198 | x | |||||
28 | K | skin_temperature | skt | 235 | x | x | ||||
29 | K | soil_temperature_level_4 | stl4 | 236 | x | x | ||||
30 | K | temperature_of_snow_layer | tsn | 238 | x | x | ||||
31 | (0 - 1) | forecast_albedo | fal | 243 | x | x |
1
2 Leaf Area Index (LAI) parameters are based on a monthly climatology as explained IFS model documentation CY45R1. So the users will only see monthly variability, but not inter-annual variability.
Table 3: stream=oper/mnth/moda, levtype=sfc: surface parameters: accumulations
name | units | Variable name in CDS | shortName | paramId | an | fc | GRIB1 | GRIB2 | Used as forcing field | |
---|---|---|---|---|---|---|---|---|---|---|
1 | m | surface_runoff | sro | 8 | x | x | ||||
2 | m | sub_surface_runoff | ssro | 9 | x | x | ||||
3 | m of water equivalent | snow_evaporation | es | 44 | x | x | ||||
4 | m of water equivalent | snowmelt | smlt | 45 | x | x | ||||
5 | m of water equivalent | snowfall | sf | 144 | x | x | x | |||
6 | Surface sensible heat flux | J m**-2 | surface_sensible_heat_flux | sshf | 146 | x | x | |||
7 | Surface latent heat flux | J m**-2 | surface_latent_heat_flux | slhf | 147 | x | x | |||
8 | Surface solar radiation downwards | J m**-2 | surface_solar_radiation_downwards | ssrd | 169 | x | x | x | ||
9 | Surface thermal radiation downwards | J m**-2 | surface_thermal_radiation_downwards | strd | 175 | x | x | x | ||
10 | Surface net solar radiation | J m**-2 | surface_net_solar_radiation | ssr | 176 | x | x | x | ||
11 | Surface net thermal radiation | J m**-2 | surface_net_thermal_radiation | str | 177 | x | x | x | ||
12 | m of water equivalent | total_evaporation | e | 182 | x | x | ||||
13 | m | runoff | ro | 205 | x | x | ||||
14 | m | total_precipitation | tp | 228 | x | x | x | |||
15 | Evaporation from the top of canopy | m of water equivalent | evaporation_from_the_top_of_canopy | evatc | 228100 | x | x | |||
16 | Evaporation from bare soil | m of water equivalent | evaporation_from_bare_soil | evabs | 228101 | x | x | |||
17 | Evaporation from open water surfaces excluding oceans | m of water equivalent | evaporation_from_open_water_surfaces_excluding_oceans | evaow | 228102 | x | x | |||
18 | Evaporation from vegetation transpiration | m of water equivalent | evaporation_from_vegetation_transpiration | evavt | 228103 | x | x | |||
19 | m | potential_evaporation | pev | 228251 | x | x |
Accumulations are described in section ERA5-Land: data documentation#accumulations. The accumulations in monthly means (stream=moda/mnth) are described in section monthly means
Guidelines
Known issues
ERA5-Land forecast parameters are missing for the validity time of 1st January 1950 00 UTC.
How to cite the ERA5-Land dataset
In addition to the terms and conditions of the license(s), users must:
- cite the CDS catalogue entry;
- provide clear and visible attribution to the Copernicus programme and attribute each data product used;
Step 1: Check the licence to use Copernicus Products for attribution/reference clause.
Step 2: Cite the CDS catalogue entry (as traceable source of data).
Step 3: Provide clear and visible attribution to the Copernicus programme and attribute each data product used (to accredit the creators of the data). Throughout the content of your publication, the dataset used is referred to as Author (YYYY).
The 3-steps procedure above is illustrated with this example:
Use Case 1: ERA5-Land hourly data from 1950 to present
For complete details, please refer to How to acknowledge and cite a Climate Data Store (CDS) catalogue entry and the data published as part of it.
Reference articles
J. Muñoz-Sabater, Dutra, E., Agustí-Panareda, A., Albergel, C., Arduini, G., Balsamo, G., Boussetta, S., Choulga, M., Harrigan, S., Hersbach, H., Martens, B., Miralles, D. G., Piles, M., Rodríguez-Fernández, N. J., Zsoter, E., Buontempo, C., and Thépaut, J.-N.: ERA5-Land: A state-of-the-art global reanalysis dataset for land applications, Earth Syst. Sci. Data,13, 4349–4383, 2021. https://doi.org/10.5194/essd-13-4349-2021.
Further ERA5-Land references and related information are available from the ECMWF website.