ECMWF ERA5-Land

Summary Description

ERA5-Land is a high-resolution global land surface reanalysis dataset produced by the European Centre for Medium-Range Weather Forecasts (ECMWF). It provides historical climate and weather data, focusing on land surface variables with enhanced spatial and temporal resolution. ERA5-Land is generated using the same land surface model as ERA5 driven by the meteorological forcing from the ERA5 climate reanalysis, but without atmospheric data assimilation. The objective for it’s generation is improved consistency in the representation of land-related processes, at high resolution and over an extended period to support applications in water resource, land and environmental management.

ERA5-Land Example

ERA5-Land data over North America (Source: PAVICS)

Dataset Characteristics

Strengths and Limitations

Key Strengths of ERA5-Land

Strength Description
High Spatial Resolution 0.1° x 0.1°; Native resolution is ~9 km.9 km grid.
Long-Term Consistency Extends back to 1950, enabling long-term climate studies and trend analysis.
Hourly Data Availability Supports high-frequency climate and hydrological applications.
Improved Land Surface Processes Enhanced representation of soil moisture, snow, and vegetation dynamics.
Global Coverage Provides consistent land surface data across all continents.

Limitations of ERA5-Land

Limitation Description
No Atmospheric Data Assimilation Unlike ERA5, ERA5-Land does not assimilate atmospheric observations, which may introduce biases.
Precipitation Uncertainties Forced by ERA5 atmospheric fields, which can lead to regional biases in precipitation estimates.
Limited Ocean Representation. Focuses on land; coastal interactions may be less accurate.
Computationally Intensive. High-resolution data requires significant storage and processing resources.
Lack of Direct Observations. The data are entirely model-based, potentially differing from ground-based observations.
Wind data only at 10 m height. Wind data are only provided at 10m. However, 100 m data aree available from ERA5.

Expert Guidance

The ERA5-Land dataset provides a consistent long term view of the evolution of land surface variables. Compared to it’s driver ERA5, beyond higher resolution, ERA5-Land shows added value in the description of the hydrological cycle and river discharge, with enhanced soil moisture and lake description. It shows mixed performance regarding snow depth and results comparable to ERA5 in the description of the energy cycle. Validation has shown that a good part of the better performance is related to better spatial represention of energy fluxes near coasts or lakes. It is noteworthy to point out that both ERA5 and ERA5-Land outperform their predecessor ERA-Interim, and the multi-decadal consistency enables reliable trend analysis (Muñoz-Sabater et al. (2021)).

Temperature values of ERA5-Land are generally well reproduced, however, because cities are non-existent and ERA5-Land does not assimilate observations, the urban heat island signals in cities aren’t explicitly represented. For peak-demand and heat-risk work in cities, urban stations would be a better alternative.

Precipitation is generated by the ERA5 atmospheric model and input to the ERA5-Land land surface model which does no adjustion or correction, and no direct rain-gauge assimilation is performed. Precipitaion values comprise accumulated liquid and frozen water, including rain and snow, originatining from both, large-scale precipitation and convective precipitation. The variable is accumulated from the beginning of the forecast time to the end of the forecast step. ERA5-Land precipitation values generarlly show large deviations from observations (Muñoz-Sabater et al. (2021)), partially because observations are point observations integrated over a period of time, rather than representing averages over a model grid box and model time step.

Regarding snow accumulation, ERA5-Land shows improved snow mass and snow depth estimeates on mid latitude mountains which is related to the higher resolution. However, ERA5 and ERA5-Land both overestimate total Northern Hemispher SWE by up to 150 % to 200 % compared to the SWE reference data (for details see Kouki et al. (2023) and Sarpong and Nazemi (2025)). These errors are related to biases in solid precipitation but may also be related to processes like snow transport and sublimation not being considered in the model.

Wind values of ERA5-Land are provided as eastward and westward components of the 10m wind, describing the horizontal speed of air moving at a height of ten metres above the surface of the Earth, in metres per second. These values may be biased when compared to wind observations, which may vary on small space and time scales and are affected by the local terrain, vegetation and buildings, which may not be represented in the ECMWF Integrated Forecasting System. Also, at ~9 km resolution, complex terrain and shoreline circulations are under-resolved, so local speed-ups/channelling and lake/sea-breeze structures are often underestimated. This can be important for BC fjords & mountain valleys and along the Great Lakes (ON/QC). The northward and eastward components of 10m wind can be combined to give the speed and direction of the horizontal 10m wind. Note that ERA5-Land only provides 10-m winds. Frequently required hub-height 100 m wind data at are available from ERA5.

Regarding other variables provided by ERA5-Land, it should be noted that the ERA5-Land model does not include the water balance equation for lakes and lake volume will be held constant (i.e. lake depth and surface area do not change in time). Thus evaporation and mixing depth will be based on a fixed, “average” water depth. Generally, lake water surface temperature are underestimated (1.3˚C cooler than observed, on average). Hence, ERA5-Land’s lake temperatures and energy fluxes are fine for broad-scale climatology but cannot be used directly for studies needing realistic water level or storage changes.

Finally, Cao et al. (2020) concluded that ERA5-Land soil data are not well suited for informing permafrost research and decision making directly.

Evaluation studies of ERA5 and ERA5-Land for applications in agriculture and hydrology have been conducted by Fatolahzadeh Gheysari et al. (2024) and Tarek et al. (2020), respectively.

Example Applications

links to Electricity Sector Applications

Variables available in ERA5-Land

For details click on variable group to uncollapse

  • 2m temperature [K]
  • 2m dewpoint temperature [K]

Temperature of air at 2m above the surface of land, sea or in-land waters. Temperature values are provided in kelvin and can be converted to degrees Celsius (°C) by subtracting 273.15.
Dewpoint temperature can be used to calculate relative humidity when combined with temperature and pressure.

For more details see the respective table at the bottom of the ERA5-Land dataset web site.

  • Total precipitation [m]

For more details see the respective table at the bottom of the ERA5-Land dataset web site.

  • 10m u-component of wind (eastward) [m s-1]
  • 10m v-component of wind (northward) [m s-1]

The eastward and westward component of the 10m wind can be to give the speed and direction of the horizontal 10m wind.

For more details see the respective table at the bottom of the ERA5-Land dataset web site.

Note that frequently required hub-height 100 m wind data at are available from ERA5-Land’s driving dataset ERA5.

ERA5-Land does not provide any variable for humidity. However, relative humidity may be calculated from temperature, dew point temperature and surface pressur. For more details see the respective table at the bottom of the ERA5-Land dataset web site.

  • Surface net solar radiation [J m-2]
  • Surface net thermal radiation [J m-2]
  • Forecast albedo [fraction]
  • Snow albedo [fraction]

Solar radiation (shortwave) includes both direct and indirect incoming radiation. Solar and thermal radiation are accumulated energy from the beginning to the end of the time step. By model convention downward fluxes are positive. To obtain values to [W m-2] the accumulated values need to be divided by the accumulation period expressed in seconds.

  • Snow cover [%]
  • Snow density [kg m-3]
  • Snow depth [m]
  • Snow depth water equivalent [m of water equivalent]
  • Snow evaporation [m of water equivalent]
  • Snowfall [m of water equivalent]
  • Snowmelt [m of water equivalent]

Most values for snow are gid box averages, exept the snow depth water equivalent which refers to the snow covered fraction of the grid box.

For more details see the respective table at the bottom of the ERA5-Land dataset web site.

ERA5-Land provides a host of other surface and meteorologial variables such as potential evapotranspiration, surface pressure, surface sensible heat flux, snow layer temperature, soil water content and temperatures, lake water parameters, leaf area index, and runoff variables.

For more details see the respective table at the bottom of the ERA5-Land dataset web site.

Data Access

ERA5-Land hourly data from 1950 to present are available on the Copernicus Data Store. ECMWF has a web site with Instructions to download ERA5-Land. Hourly and daily temperature and precipitation data from ERA5-Land over North America are available on PAVICS.

To avoid downloading very large datasets in their entirety PAVICS allows partial/regional extraction and provides a tutorial to do so, using the CaSR reanalysis as an example . With a free PAVICS user account, the Jupyter notebook with the Python code in the tutorial can be directly used on PAVICS.

References

Cao, B., Gruber, S., Zheng, D., Li, X., 2020. The ERA5-land soil temperature bias in permafrost regions. The Cryosphere 14, 2581–2595. https://doi.org/10.5194/tc-14-2581-2020
Fatolahzadeh Gheysari, A., Maghoul, P., Ojo, E.R., Shalaby, A., 2024. Reliability of ERA5 and ERA5-land reanalysis data in the canadian prairies. Theoretical and Applied Climatology 155, 3087–3098. https://doi.org/10.1007/s00704-023-04771-z
Kouki, K., Luojus, K., Riihelä, A., 2023. Evaluation of snow cover properties in ERA5 and ERA5-land with several satellite-based datasets in the northern hemisphere in spring 1982–2018. The Cryosphere 17, 5007–5026. https://doi.org/10.5194/tc-17-5007-2023
Muñoz-Sabater, J., 2019. ERA5-land hourly data from 1950 to present [WWW Document]. Copernicus Climate Change Service (C3S) Climate Data Store (CDS). URL https://cds.climate.copernicus.eu/datasets/reanalysis-era5-land?tab=overview (accessed 4.25.2025).
Muñoz-Sabater, J., Dutra, E., Agustı́-Panareda, A., Albergel, C., Arduini, G., Balsamo, G., Boussetta, S., Choulga, M., Harrigan, S., Hersbach, H., Martens, B., Miralles, D.G., Piles, M., Rodrı́guez-Fernández, N.J., Zsoter, E., Buontempo, C., Thépaut, J.-N., 2021. ERA5-land: A state-of-the-art global reanalysis dataset for land applications. Earth System Science Data 13, 4349–4383. https://doi.org/10.5194/essd-13-4349-2021
Sarpong, R., Nazemi, A., 2025. Benchmarking snow fields of ERA5-land in the northern regions of north america. EGUsphere 2025, 1–31. https://doi.org/10.5194/egusphere-2024-4150
Tarek, M., Brissette, F.P., Arsenault, R., 2020. Evaluation of the ERA5 reanalysis as a potential reference dataset for hydrological modelling over north america. Hydrology and Earth System Sciences 24, 2527–2544. https://doi.org/10.5194/hess-24-2527-2020