This paper analyzes the ensemble of regional climate model (RCM) projections for Europe completed within the EURO-CORDEX project. Projections are available for the two greenhouse gas concentration scenarios RCP2.6 (22 members) and RCP8.5 (55 members) at 0.11°resolution from 11 RCMs driven by eight global climate models (GCMs). The RCM ensemble results are compared with the driving CMIP5 global models but also with a subset of available last generation CMIP6 projections. Maximum warming is projected by all ensembles in Northern Europe in winter, along with a maximum precipitation increase there; in summer, maximum warming occurs in the Mediterranean and Southern European regions associated with a maximum precipitation decrease. The CMIP6 ensemble shows the largest signals, both for temperature and precipitation, along with the largest inter-model spread. There is a high model consensus across the ensembles on an increase of extreme precipitation and drought frequency in the Mediterranean region. Extreme temperature indices show an increase of heat extremes and a decrease of cold extremes, with CMIP6 showing the highest values and EURO-CORDEX the finest spatial details. This data set of unprecedented size and quality will provide the basis for impact assessment and climate service activities for the European region.

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The use of regional climate model (RCM)‐based projections for providing regional climate information in a research and climate service contexts is currently expanding very fast. This has been possible thanks to a considerable effort in developing comprehensive ensembles of RCM projections, especially for Europe, in the EURO‐CORDEX community (Jacob et al., 2014, 2020). As of end of 2019, EURO‐CORDEX has developed a set of 55 historical and scenario projections (RCP8.5) using 8 driving global climate models (GCMs) and 11 RCMs. This article presents the ensemble including its design. We target the analysis to better characterize the quality of the RCMs by providing an evaluation of these RCM simulations over a number of classical climate variables and extreme and impact‐oriented indices for the period 1981–2010. For the main variables, the model simulations generally agree with observations and reanalyses. However, several systematic biases are found as well, with shared responsibilities among RCMs and GCMs: Simulations are overall too cold, too wet, and too windy compared to available observations or reanalyses. Some simulations show strong systematic biases on temperature, others on precipitation or dynamical variables, but none of the models/simulations can be defined as the best or the worst on all criteria. The article aims at supporting a proper use of these simulations within a climate services context.

The new Coordinated Output for Regional Evaluations (CORDEX-CORE) ensemble provides high-resolution, consistent regional climate change projections for the major inhabited areas of the world. It serves as a solid scientific basis for further research related to vulnerability, impact, adaptation and climate services in addition to existing CORDEX simulations. The aim of this study is to investigate and document the climate change information provided by the CORDEX-CORE simulation ensemble, as a part of the World Climate Research Programme (WCRP) CORDEX community. An overview of the annual and monthly mean climate change information in selected regions in different CORDEX domains is presented for temperature and precipitation, providing the foundation for detailed follow-up studies and applications. Initially, two regional climate models (RCMs), REMO and RegCM were used to downscale global climate model output. The driving simulations by AR5 global climate models (AR5-GCMs) were selected to cover the spread of high, medium, and low equilibrium climate sensitivity at a global scale. The CORDEX-CORE ensemble has doubled the spatial resolution compared to the previously existing CORDEX simulations in most of the regions (25$$\,\mathrm {km}$$ km (0.22$$^{\circ }$$ ∘ ) versus 50$$\,\mathrm {km}$$ km (0.44$$^{\circ }$$ ∘ )) leading to a potentially improved representation of, e.g., physical processes in the RCMs. The analysis focuses on changes in the IPCC physical climate reference regions. The results show a general reasonable representation of the spread of the temperature and precipitation climate change signals of the AR5-GCMs by the CORDEX-CORE simulations in the investigated regions in all CORDEX domains by mostly covering the AR5 interquartile range of climate change signals. The simulated CORDEX-CORE monthly climate change signals mostly follow the AR5-GCMs, although for specific regions they show a different change in the course of the year compared to the AR5-GCMs, especially for RCP8.5, which needs to be investigated further in region specific process studies.

Climate signal maps can be used to identify regions where robust climate changes can be derived from an ensemble of climate change simulations. Here, robustness is defined as a combination of model agreement and the significance of the individual model projections. Climate signal maps do not show all information available from the model ensemble, but give a condensed view in order to be useful for non-climate scientists who have to assess climate change impact during the course of their work. Three different ensembles of regional climate projections have been analyzed regarding changes of seasonal mean and extreme precipitation (defined as the number of days exceeding the 95th percentile threshold of daily precipitation) for Germany, using climate signal maps. Although the models used and the scenario assumptions differ for the three ensembles (representative concentration pathway (RCP) 4.5 vs. RCP8.5 vs. A1B), some similarities in the projections of future seasonal and extreme precipitation can be seen. For the winter season, both mean and Atmosphere 2015, 6 678 extreme precipitation are projected to increase. The strength, robustness and regional pattern of this increase, however, depends on the ensemble. For summer, a robust decrease of mean precipitation can be detected only for small regions in southwestern Germany and only from two of the three ensembles, whereas none of them projects a robust increase of summer extreme precipitation.