Climate change affects the productivity (e.g., Boisvenue and Running 2006) and carbon sequestration of forests (cf. Hui et al. 2017). To model potential future site-specific forest productivity, high quality data for both forest stands and climate are required. So far, the available climate data meet the requirements for forestry scientific questions only to a certain degree. Existing datasets, such as the E-OBS gridded dataset (Haylock et al. 2008), the WorldClim data (Hijmans et al. 2005), the grids of monthly aggregated climate data (e.g., DWD Climate Data Center—CDC 2016a), and the recently published CHELSA data (Karger et al. 2017), achieve a spatial resolution of 0.2° and 0.3° (lat./long.) or 1-km2 regular grid. Due to the availability of high-resolution digital terrain models for Germany via the German Federal Agency for Cartography and Geodesy (Bundesamt für Kartographie und Geodäsie BKG 2010), there is a suitable basis for a more precise elaboration of terrain induced climatic effects, such as cold air flows, respectively, accumulation. Not only long-term changes in climatic conditions may cause physiological stress to trees. Especially, weather extremes may generate effects even within short timescales. Therefore, the climate variables influencing forest productivity are required in daily resolution, which is neither realized by WorldClim, CHELSA nor in the DWD climate datasets. In the frame of the project “Forest Productivity–Carbon Sequestration–Climate Change” (WP-KS-KW) (Mette 2017), climate regionalization provides the spatial and temporal requirements by resolving climate information for Germany in a daily raster of 250 × 250 m for the period 1961 to 2100. The “NFI 2012 environmental data base climate” contains aggregated time series with spatial climate information for monthly and annual values, extreme value statistics, and specific characteristics for phenological phases or specific periods in the above-mentioned timeframe for the German National Forest Inventory (NFI) and the National Forest Soil Inventory (NFSI).