Evaluation of the Large EURO‐CORDEX Regional Climate Model Ensemble. Issue 17 (1st September 2021)

• Record Type: Journal Article
• Authors: Vautard, Robert; Kadygrov, Nikolay; Iles, Carley; Boberg, Fredrik; Buonomo, Erasmo; Bülow, Katharina; Coppola, Erika; Corre, Lola; van Meijgaard, Erik; Nogherotto, Rita; Sandstad, Marit; Schwingshackl, Clemens; Somot, Samuel; Aalbers, Emma; Christensen, Ole B.; Ciarlo, James M.; Demory, Marie‐Estelle; Giorgi, Filippo; Jacob, Daniela; Jones, Richard G.; Keuler, Klaus; Kjellström, Erik; Lenderink, Geert; Levavasseur, Guillaume; Nikulin, Grigory; Sillmann, Jana; Solidoro, Cosimo; Sørland, Silje Lund; Steger, Christian; Teichmann, Claas; Warrach‐Sagi, Kirsten; Wulfmeyer, Volker;
• Is Part Of: Journal of geophysical research. Volume 126:Issue 17(2021)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2021-09-01
• Subjects: climate change -- regional climate modeling -- EURO‐CORDEX -- climate model evaluation -- model biases -- European climate; Atmospheric physics -- Periodicals; Geophysics -- Periodicals; 551.5
• DOI: 10.1029/2019JD032344
• Languages: English
• ISSNs: 2169-897X

Abstract

Abstract: 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. Plain Language Summary: This study analyses the ability of the unprecedently large ensemble of 55 regional climate simulations to properly simulate the climatology of several variables, extremes, and impact‐oriented indices over the European continent. This analysis should guide the use of regional climate projections in climate services development. Key Points: Biases of an unprecedentedly large ensemble of 55 European climate simulations using 8 global climate models and 11 regional climate models are assessed Climate variables, extremes, and impact‐oriented indices are assessed, indicating whether such ensemble can—or cannot—be used in climate service applications Simulations are generally too wet, too cold and too windy, and the share of contributions to the bias from GCMs and RCMs is found to differ for each variable or index