Abstract
AbstractThe 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.
Highlights
Regional climate change projections are widely used for research and applications in order to describe the future of climatic conditions and subsequent impacts at a scale that is presumably better suited than coarser resolution global climate projections (Giorgi, 2019; Rummukainen, 2016)
Several systematic biases are found as well, with shared responsibilities among regional climate model (RCM) and global climate models (GCMs): Simulations are overall too cold, too wet, and too windy compared to available observations or reanalyses
We focus on a subset of variables and indices linked to some economic sectors, intending to provide a broad view of the ensemble's capacity to represent useful information for further use in science and decision making
Summary
Regional climate change projections are widely used for research and applications in order to describe the future of climatic conditions and subsequent impacts at a scale that is presumably better suited than coarser resolution global climate projections (Giorgi, 2019; Rummukainen, 2016). Regional climate projections generally use limited area models, or regional climate models (RCMs), with resolutions currently ranging from a few kilometers to about 50 km, downscaling GCMs. Regional climate projections generally use limited area models, or regional climate models (RCMs), with resolutions currently ranging from a few kilometers to about 50 km, downscaling GCMs Formal analysis: Robert Vautard, Nikolay Kadygrov, Carley Iles, Fredrik Boberg, Erasmo Buonomo, Katharina Bülow, Erika Coppola, Lola Corre, Erik van Meijgaard, Rita Nogherotto, Marit Sandstad, Clemens Schwingshackl, Samuel Somot, Emma Aalbers, Ole B. Marie‐ Estelle Demory, Klaus Keuler, Erik Kjellström, Silje Lund Sørland, Christian Steger, Kirsten Warrach‐Sagi, Volker Wulfmeyer
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