E‐OBS(European Observations) is a gridded climate data set which contains maximum temperature, minimum temperature, and precipitation on a daily time step. The data can be as fine as 0.25° in resolution and extends over the entire European continent and parts of Africa and Asia. However, for studying regional or local climatic effects, a finer resolution would be more appropriate. A continental data set with resolution would allow research that is large in scale and still locally relevant. Until now, a climate data set with high spatial and temporal resolution has not existed for Europe. To fulfil this need, we produced a downscaled version of E‐OBS, applying the delta method, which uses WorldClim climate surfaces to obtain a 0.008° (about 1 × 1 km) resolution climate data set on a daily time step covering the European Union. The new downscaled data set includes minimum and maximum temperature and precipitation for the years 1951–2012. It is analysed against weather station data from six countries: Norway, Germany, France, Italy, Austria, and Spain. Our analysis of the downscaled data set shows a reduction in the mean bias error of 3 °C for mean daily minimum temperature and of 4 °C for mean daily maximum temperature. Daily precipitation improved by 0.15 mm on average for all weather stations in the validation. The entire data set is freely and publically available at ftp://palantir.boku.ac.at/Public/ClimateData.

Net primary production (NPP) is an important ecological metric for studying forest ecosystems and their carbon sequestration, for assessing the potential supply of food or timber and quantifying the impacts of climate change on ecosystems. The global MODIS NPP dataset using the MOD17 algorithm provides valuable information for monitoring NPP at 1-km resolution. Since coarse-resolution global climate data are used, the global dataset may contain uncertainties for Europe. We used a 1-km daily gridded European climate data set with the MOD17 algorithm to create the regional NPP dataset MODIS EURO. For evaluation of this new dataset, we compare MODIS EURO with terrestrial driven NPP from analyzing and harmonizing forest inventory data (NFI) from 196,434 plots in 12 European countries as well as the global MODIS NPP dataset for the years 2000 to 2012. Comparing these three NPP datasets, we found that the global MODIS NPP dataset differs from NFI NPP by 26%, while MODIS EURO only differs by 7%. MODIS EURO also agrees with NFI NPP across scales (from continental, regional to country) and gradients (elevation, location, tree age, dominant species, etc.). The agreement is particularly good for elevation, dominant species or tree height. This suggests that using improved climate data allows the MOD17 algorithm to provide realistic NPP estimates for Europe. Local discrepancies between MODIS EURO and NFI NPP can be related to differences in stand density due to forest management and the national carbon estimation methods. With this study, we provide a consistent, temporally continuous and spatially explicit productivity dataset for the years 2000 to 2012 on a 1-km resolution, which can be used to assess climate change impacts on ecosystems or the potential biomass supply of the European forests for an increasing bio-based economy. MODIS EURO data are made freely available at ftp://palantir.boku.ac.at/Public/MODIS_EURO.

Pan‐European gridded datasets derived from a single methodology to inform researchers, policy makers and conservationists on the state of forest structures would improve our ability to study forests independent of political boundaries and along various gradients. Although National Forest Inventory (NFI) data provide information on the characteristics of forests, including carbon content, volume, height, and age, such spatial data is not available across Europe. Before this study, remotely sensed data covering all of Europe had not been utilized to produce multiple European‐focused forest structure datasets over the entire continent that are methodologically consistent and comparable. We used existing European data to develop a pan‐European dataset covering tons of live tree carbon and volume per hectare, mean tree height and mean tree age by integrating remotely sensed and harmonized NFI data from 13 different European countries. We produced a pan‐European map for each of the four key variables on a 0.133° grid representing the time period 2000–2010.