Given the importance of sub-daily extreme precipitation events for the occurrence of pluvial floods, it is a key component in climate change adaptation to quantify the likelihood of such extreme events under current and future climate conditions. Such assessments are usually limited by a lack of sufficiently dense and sub-daily precipitation observations, (ii) high-resolution convection-permitting regional climate model (CPM) simulations that realistically represent sub-daily precipitation extremes, and (iii) statistical methods that allow us to extrapolate extreme precipitation return levels under limited data availability and non-stationary conditions (i.e., climate change) based on the main governing physical processes. We overcome these constraints through the utilization of kilometer-scale hourly radar precipitation estimates (RADKLIM) and spatially disaggregated observed daily temperature data (HYRAS-DE-TAS), and the implementation of a novel CPM ensemble covering the entirety of Germany, obtained from the NUKLEUS project within the BMBF-funded RegIKlim (Regionale Information zum Klimahandeln) initiative. Additionally, we introduce the Temperature-dependent Non-Asymptotic statistical model for eXtreme return levels (TENAX) model, a new approach that integrates daily temperature as a covariate, aligning with observed Clausius-Clapeyron scaling rates. This innovation results in a groundbreaking dataset of hourly extreme precipitation for Germany, marking the first instance of accounting for non-stationary climate conditions, i.e., in a +2K and +3K warmer world. The new dataset contains kilometer-scale hourly precipitation extremes for the return level of a 100-year event. Due to the inherent biases of radar-based estimates compared to ground observations, the precipitation extremes have been bias-adjusted on return level basis using KOSTRA.

Annual maxima of sub-daily precipitation were extracted from each of 35 members of a EURO-CORDEX ensemble with a spatial resolution of 0.11° (EURO-CORDEX: https://www.euro-cordex.net/). Precipitation durations range from 1 to 72 hours. Regional Climate Models (RCMs) involved are: ALADIN63,COSMO, HadREM3, RCA4, RegCM4-6, and REMO2015. For each member, we considered both historical (1950-2005) and future (2006-2100) RCP8.5 scenarios. In EURO-CORDEX, different RCMs can have (slightly) different grids and some RCMs (e.g. ALADIN63 and RegCM4-6) have a much different domain. For each RCM the correct bounds are given in the corresponding dataset. In contrast, the bounds given in the Experiment are smaller and can be found on the EURO-CORDEX website: https://euro-cordex.net/060374/index.php.en A new version exists now. In Version 2, we supplemented the original dataset from Version 1 with the regridded data in a common grid. We also added evaluation runs (where available) and useful variables such as “surface elevation” (orog) and “land surface fraction” (sftlf) to all NetCDF files.

Annual maxima of sub-daily precipitation were extracted from each of 35 members of a EURO-CORDEX ensemble with a spatial resolution of 0.11° (EURO-CORDEX: https://www.euro-cordex.net/). Precipitation durations range from 1 to 72 hours. Regional Climate Models (RCMs) involved are: ALADIN63,COSMO, HadREM3, RCA4, RegCM4-6, and REMO2015. For each member, we considered both historical (1950-2005) and future (2006-2100) RCP8.5 scenarios. Simulations of four RCMs (out of a total of six) are also available for the past, with imposed “perfect” lateral boundary conditions following ERA-Interim reanalyses (1979-2019). In EURO-CORDEX, different RCMs can have (slightly) different grids and some RCMs (e.g. ALADIN63 and RegCM4-6) have a much different domain. For each RCM the correct bounds are given in the corresponding dataset. In contrast, the bounds given in the Experiment are smaller and can be found on the EURO-CORDEX website: https://euro-cordex.net/060374/index.php.en For practical applications, we also provide the regridded values on a common grid of 0.11° × 0.11° with spatial coverage of 28N−70N and 13W−35E. In Version 2, we supplemented the original dataset from Version 1 with the regridded data in a common grid. We also added evaluation runs (where available) and useful variables such as “surface elevation” (orog) and “land surface fraction” (sftlf) to all NetCDF files.