We compiled a climate dataset with high spatial and temporal resolution consisting of model and observational data suitable for assessing the impact of climate change on German forests. The dataset includes nine climate parameters with daily resolution: (1) minimum, (2) mean, and (3) maximum temperature, (4) total precipitation sum, (5) mean wind speed, (6) total shortwave radiation, (7) mean relative humidity, (8) mean water vapour pressure and (9) mean potential evapotranspiration. The data were calculated as a time series with daily resolution from 1961 to 2100 at the sample grid points (approximately 4 x 4 km) of the German National Forest Inventory (NFI) (Hennig 2022). Due to the pointwise spatial arrangement, this dataset cannot be considered raster data, but rather as sample grid points (Thünen-Atlas 2026). Models for climate projections were provided by 'Regionale Klimaprojektionen Ensemble für Deutschland' (ReKliEs-De) (Hübener et al. 2017). A variety of combinations of global circulation and regional climate models, as well as statistical and dynamic climate models, were employed to calculate climate projections. Two Representative Concentration Pathway (RCP) scenarios (4.5 and 8.5) were taken into account. A total of nine model runs were executed, seven based on RCP8.5 and two based on RCP4.5: (1) EC-Earth/RACMO (ECECMO); (2) HadGEM2-ES/WR13 (HAD013); (3) HadGEM2-ES/WRF (HADWRF); (4) MIROC5/CCLM (MIRCLM); (5) MPI-ESM-LR/CCLM (MPICLM); (6) MPI-ESM-LR/WR13 (MPI013); (7) MPI-ESM-LR/WRF (MPIWRF). The German Meteorological Service (DWD) provided observation data from 1961 to 2020. Both climate model and observation data were downscaled to a spatial resolution of 250 x 250 metres (Ahrends et al. 2018, Feigenwinter et al. 2018, Sutmöller et al. 2021). The dataset consists of 22,444 NFI potential (forested and unforested) sample grid points covering Germany. To process the data using the Climate Data Operators (CDO) tool, the sample grid points were transformed into a virtual, continuous spatial grid based on Network Common Data Form (NetCDF) files, with no georeferencing involved. The grid-based NetCDF files can be transformed into georeferenced point data (CSV) at NFI sample grid points with the aid of the included NetCDF help files (easting.nc, northing.nc, trakt_number.nc) and the R-script (NetCDF_to_csv.R). The coordinate reference system EPSG:25832 is used for transforming virtual raster data to point data.