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N. Ban et al. ; Here we present the first multi-model ensemble of regional climate simulations at kilometer-scale horizontal grid spacing over a decade long period. A total of 23 simulations run with a horizontal grid spacing of ∼3 km, driven by ERA-Interim reanalysis, and performed by 22 European research groups are analysed. Six different regional climate models (RCMs) are represented in the ensemble. The simulations are compared against available high-resolution precipitation observations and coarse resolution (∼ 12 km) RCMs with parameterized convection. The model simulations and observations are compared with respect to mean precipitation, precipitation intensity and frequency, and heavy precipitation on daily and hourly timescales in different seasons. The results show that kilometer-scale models produce a more realistic representation of precipitation than the coarse resolution RCMs. The most significant improvements are found for heavy precipitation and precipitation frequency on both daily and hourly time scales in the summer season. In general, kilometer-scale models tend to produce more intense precipitation and reduced wet-hour frequency compared to coarse resolution models. On average, the multi-model mean shows a reduction of bias from ∼ −40% at 12 km to ∼ −3% at 3 km for heavy hourly precipitation in summer. Furthermore, the uncertainty ranges i.e. the variability between the models for wet hour frequency is reduced by half with the use of kilometer-scale models. Although differences between the model simulations at the kilometer-scale and observations still exist, it is evident that these simulations are superior to the coarse-resolution RCM simulations in the representing precipitation in the present-day climate, and thus offer a promising way forward for investigations of climate and climate change at local to regional scales. ; Open access funding provided by University of Innsbruck and Medical University of Innsbruck. ; The ETH team, MZ, CNRM IPSL, ICTP, SMHI, Met-Office, DMI, CMCC, HZG, KNMI acknowledge funding from the HORIZON 2020 EUCP (European Climate Prediction System) project (https://www.eucp-project.eu, grant agreement No. 776613). AL-G acknowledges support by the Spanish government through grant BES-2016-078158 and MINECO/FEDER co-funded project MULTI-SDM (CGL2015-66583-R). ; Peer reviewed

Here we present the first multi-model ensemble of regional climate simulations at kilometer-scale horizontal grid spacing over a decade long period. A total of 23 simulations run with a horizontal grid spacing of ?3 km, driven by ERA-Interim reanalysis, and performed by 22 European research groups are analysed. Six different regional climate models (RCMs) are represented in the ensemble. The simulations are compared against available high-resolution precipitation observations and coarse resolution (? 12 km) RCMs with parameterized convection. The model simulations and observations are compared with respect to mean precipitation, precipitation intensity and frequency, and heavy precipitation on daily and hourly timescales in different seasons. The results show that kilometer-scale models produce a more realistic representation of precipitation than the coarse resolution RCMs. The most significant improvements are found for heavy precipitation and precipitation frequency on both daily and hourly time scales in the summer season. In general, kilometer-scale models tend to produce more intense precipitation and reduced wet-hour frequency compared to coarse resolution models. On average, the multi-model mean shows a reduction of bias from ? ?40% at 12 km to ? ?3% at 3 km for heavy hourly precipitation in summer. Furthermore, the uncertainty ranges i.e. the variability between the models for wet hour frequency is reduced by half with the use of kilometer-scale models. Although differences between the model simulations at the kilometer-scale and observations still exist, it is evident that these simulations are superior to the coarse-resolution RCM simulations in the representing precipitation in the present-day climate, and thus offer a promising way forward for investigations of climate and climate change at local to regional scales. ; The ETH and UIBK team acknowledges PRACE for awarding access to Piz Daint at Swiss National Supercomputing Center (CSCS, Switzerland), and the Federal Office for Meteorology and Climatology MeteoSwiss, the Swiss National Supercomputing Centre (CSCS), and ETH Zürich for their contributions to the development of the GPU-accelerated version of COSMO. The funding for their research was provided by the Swiss National Sciences Foundation through the Sinergia Grant CRSII2_154486 'crCLIM'. The ETH team, MZ, CNRM IPSL, ICTP, SMHI, Met-Office, DMI, CMCC, HZG, KNMI acknowledge funding from the HORIZON 2020 EUCP (European Climate Prediction System) project (https://www.eucp-project.eu, grant agreement No. 776613). The RegCM simulations by the ICTP have been completed thanks to the support of the Consorzio Interuniversitario per il Calcolo Automatico dell'Italia Nord Orientale (CINECA) super-computing center (Bologna, Italy). ICTP team acknowledge the CETEMPS, University of L'Aquila, for allowing access to the Italian database of precipitation which GRIPHO is based on. EK and SK acknowledge the GRNET HPC-ARIS infrastructure (project pr003005) and the AUTH-IT scientific center for their support. MT acknowledge that computational resources were made available by the German Climate Computing Center (DKRZ) through support from the Federal Ministry of Education and Research in Germany (BMBF), and further acknowledge the funding of the German Research Foundation (DFG) through grant nr. 401857120. HT and DM acknowledge the projects HighEnd:Extremes, EASICLIM, and reclip:convex, funded by the Austrian Climate Research Programme (ACRP) of the Klima- und Energiefonds (nos. B368608, KR16AC0K13160, and B769999, respectively) and the Vienna Scientific Cluster (VSC) (projects 70992 and 71193). HT, DM and KG gratefully acknowledge the computing time granted through JARA (project JJSC39) and the John von Neumann Institute for Computing (NIC) (project HKA19) at the Jülich Supercomputing Centre. AL-G acknowledges support by the Spanish government through grant BES-2016-078158 and MINECO/FEDER co-funded project MULTI-SDM (CGL2015-66583-R). UCAN simulations have been carried out on the Altamira Supercomputer at the Instituto de Física de Cantabria (IFCA, CSIC-UC), member of the Spanish Supercomputing Network. SS and TL gratefully acknowledge the support of the Norwegian Environment Agency and their basic funding support of NORCE's Climate Services strategic project. Their simulations were performed on resources provided by UNINETT Sigma2—the National Infrastructure for High Performance Computing and Data Storage in Norway. JM and JF gratefully acknowledge the support by the Spanish government R+D programme through grant INSIGNIA (CGL2016-79210-R), co-funded by the ERDF/FEDER. The UHOH team and JM are also thankful for the support of the German Science Foundation (DFG) through project FOR 1695. The UHOH simulations were carried out using the computational resources received from the supercomputing center HLRS in Stuttgart, Germany. IPSL's work was granted access to the HPC resources of TGCC under the allocations 2018-A0030106877 and 2019-A0030106877 made by GENCI. EB and BA thank the Hessian Competence Center for High Performance Computing. The CICERO team was funded through the Norwegian Research Council project HYPRE (grant no. 243942) and acknowledges computing resources from Notur (NN9188K). EJK gratefully acknowledges funding from the Joint UK BEIS/Defra Met Office Hadley Centre Climate Programme (GA01101). All authors gratefully acknowledge the WCRP-CORDEX-FPS on Convective phenomena at high resolution over Europe and the Mediterranean (FPSCONV-ALP-3) and the research data exchange infrastructure and services provided by the Jülich Supercomputing Centre, Germany, as part of the Helmholtz Data Federation initiative.

To make sound decisions in the face of climate change, government agencies, policymakers and private stakeholders require suitable climate information on local to regional scales. In Switzerland, the development of climate change scenarios is strongly linked to the climate adaptation strategy of the Confederation. The current climate scenarios for Switzerland CH2018 - released in form of six user-oriented products - were the result of an intensive collaboration between academia and administration under the umbrella of the National Centre for Climate Services (NCCS), accounting for user needs and stakeholder dialogues from the beginning. A rigorous scientific concept ensured consistency throughout the various analysis steps of the EURO-CORDEX projections and a common procedure on how to extract robust results and deal with associated uncertainties. The main results show that Switzerland's climate will face dry summers, heavy precipitation, more hot days and snow-scarce winters. Approximately half of these changes could be alleviated by mid-century through strong global mitigation efforts. A comprehensive communication concept ensured that the results were rolled out and distilled in specific user-oriented communication measures to increase their uptake and to make them actionable. A narrative approach with four fictitious persons was used to communicate the key messages to the general public. Three years after the release, the climate scenarios have proven to be an indispensable information basis for users in climate adaptation and for downstream applications. Potential for extensions and updates has been identified since then and will shape the concept and planning of the next scenario generation in Switzerland. ; Climate Scenarios for Switzerland CH2018 – Approach and Implications ; publishedVersion