ERA5-Land is a state-of-the-art global reanalysis dataset for land applications, developed as part of the Copernicus Climate Change Service (C3S) by the European Centre for Medium-range Weather Forecasts (ECMWF). It provides a high-resolution (9 km) and hourly dataset of the water and energy cycles over land, covering the period from 1950 to the present, with continuous updates. ERA5-Land is produced using the ECMWF land surface model (CHTESSEL), driven by downscaled meteorological forcing from the ERA5 climate reanalysis, including elevation correction for the thermodynamic near-surface state. It shares most of the parameterizations with ERA5 and offers improved horizontal resolution compared to ERA5 and ERA-Interim. Evaluation against in situ observations and global reference datasets shows that ERA5-Land provides better estimates of the hydrological cycle, particularly in soil moisture and lake descriptions, and improved agreement with river discharge observations. However, its snow depth estimates show mixed performance depending on location and altitude. The dataset is available through the C3S Climate Data Store and is used for hydrological studies, initializing NWP and climate models, and supporting water resource and environmental management applications. ERA5-Land is produced in three streams, with data available from January 1981 to near present, and aims for full dataset release in summer/autumn 2021. The high spatial and temporal resolution, extended period, and consistency of the fields make it a valuable dataset for land surface studies. The dataset includes 50 variables describing the water and energy cycles over land, with monthly and hourly averages available. The methodology involves initializing the land surface model with ERA5 meteorological fields, using a four-dimensional variational assimilation system and simplified extended Kalman filter for atmospheric forcing. The land surface model includes improvements in soil hydrology, snow scheme, vegetation seasonality, and lake modeling. The dataset is evaluated against in situ observations and reference datasets for soil moisture, snow depth, lake surface water temperature, river discharge, and energy fluxes. Results show that ERA5-Land performs better than ERA5 and ERA-Interim in many aspects, particularly in soil moisture and lake temperature, but has mixed performance in snow depth. The dataset is used for various applications, including hydrological modeling, climate studies, and environmental monitoring.ERA5-Land is a state-of-the-art global reanalysis dataset for land applications, developed as part of the Copernicus Climate Change Service (C3S) by the European Centre for Medium-range Weather Forecasts (ECMWF). It provides a high-resolution (9 km) and hourly dataset of the water and energy cycles over land, covering the period from 1950 to the present, with continuous updates. ERA5-Land is produced using the ECMWF land surface model (CHTESSEL), driven by downscaled meteorological forcing from the ERA5 climate reanalysis, including elevation correction for the thermodynamic near-surface state. It shares most of the parameterizations with ERA5 and offers improved horizontal resolution compared to ERA5 and ERA-Interim. Evaluation against in situ observations and global reference datasets shows that ERA5-Land provides better estimates of the hydrological cycle, particularly in soil moisture and lake descriptions, and improved agreement with river discharge observations. However, its snow depth estimates show mixed performance depending on location and altitude. The dataset is available through the C3S Climate Data Store and is used for hydrological studies, initializing NWP and climate models, and supporting water resource and environmental management applications. ERA5-Land is produced in three streams, with data available from January 1981 to near present, and aims for full dataset release in summer/autumn 2021. The high spatial and temporal resolution, extended period, and consistency of the fields make it a valuable dataset for land surface studies. The dataset includes 50 variables describing the water and energy cycles over land, with monthly and hourly averages available. The methodology involves initializing the land surface model with ERA5 meteorological fields, using a four-dimensional variational assimilation system and simplified extended Kalman filter for atmospheric forcing. The land surface model includes improvements in soil hydrology, snow scheme, vegetation seasonality, and lake modeling. The dataset is evaluated against in situ observations and reference datasets for soil moisture, snow depth, lake surface water temperature, river discharge, and energy fluxes. Results show that ERA5-Land performs better than ERA5 and ERA-Interim in many aspects, particularly in soil moisture and lake temperature, but has mixed performance in snow depth. The dataset is used for various applications, including hydrological modeling, climate studies, and environmental monitoring.