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Thiswhite paper and the accompanying tables published in GitHubare meant to help modellers in EURO-CORDEX, and elsewhere, make informed decisions when it comes to selecting GCMs for downscaling from the CMIP6 archive. While the approach to GCM selection during the CMIP5 downscaling phase cannot be wholly considered an “ensemble of opportunity” it is also true that the selection of GCMs was not as rigorous as it could have been. We aim to improve upon this situation and help us construct smarter, more reliable and more useful downscaled ensembles (dynamical, statistical and hybrid) and make the selection process more transparent. The community should consider this a living document that will evolve along with our scientific understanding.We rely mostly on peer-reviewed literature for the assessment of CMIP6 models provided in the linked tables and have devised innovative ways to include relevant metadata and update the tool with new results [https://wcrp-cordex.github.io/cmip6-for-cordex]. We encourage the wider CORDEX community to become active in this activity, suggest ways to improve and alert us when new results become available or mistakes are noted in the evaluation tables. We also hope that this EURO-CORDEX GCM selection work can inspire good practices and contribute to fruitful discussions in other CORDEX domains and CORDEX-FPS activities.

This document consists of a summary of the components of the models contributing future regional climate change simulations to the Coordinated Regional climate Downscaling Experiment (CORDEX, http://cordex.org) initiative (Table 1), the institutions and contacts for the simulations (Table 2), and references for all components. Version 1.0 (2021-01-31) of this resource contributed to the IPCC AR6 WGI report (IPCC 2021: AnnexII), see version history. This information has been gathered from the modelling groups initially by the Copernicus Climate Change Service (C3S), aligned with the deadlines and activities of IPCC AR6. The full list of institutions and model names officially registered for CORDEX, including the Terms of Use for the corresponding data, is available at https://is-enes-data.github.io. This resource (as of version 2.1) is described and discussed in the journal publication: Diez-Sierra et al. (2022) The worldwide C3S CORDEX grand ensemble: A major contribution to assess regional climate change in the IPCC AR6 Atlas. Bull. Am. Meteorol. Soc. https://doi.org/10.1175/BAMS-D-22-0111.1

In this study, we evaluate a set of high-resolution (25–50 km horizontal grid spacing) global climate models (GCMs) from the High-Resolution Model Intercomparison Project (HighResMIP), developed as part of the EU-funded PRIMAVERA (Process-based climate simulation: Advances in high resolution modelling and European climate risk assessment) project, and from the EURO-CORDEX (Coordinated Regional Climate Downscaling Experiment) regional climate models (RCMs) (12–50 km horizontal grid spacing) over a European domain. It is the first time that an assessment of regional climate information using ensembles of both GCMs and RCMs at similar horizontal resolutions has been possible. The focus of the evaluation is on the distribution of daily precipitation at a 50 km scale under current climate conditions. Both the GCM and RCM ensembles are evaluated against high-quality gridded observations in terms of spatial resolution and station density. We show that both ensembles outperform GCMs from the 5th Coupled Model Intercomparison Project (CMIP5), which cannot capture the regional-scale precipitation distribution properly because of their coarse resolutions. PRIMAVERA GCMs generally simulate precipitation distributions within the range of EURO-CORDEX RCMs. Both ensembles perform better in summer and autumn in most European regions but tend to overestimate precipitation in winter and spring. PRIMAVERA shows improvements in the latter by reducing moderate-precipitation rate biases over central and western Europe. The spatial distribution of mean precipitation is also improved in PRIMAVERA. Finally, heavy precipitation simulated by PRIMAVERA agrees better with observations in most regions and seasons, while CORDEX overestimates precipitation extremes. However, uncertainty exists in the observations due to a potential undercatch error, especially during heavy-precipitation events. The analyses also confirm previous findings that, although the spatial representation of precipitation is improved, the effect of increasing resolution from 50 to 12 km horizontal grid spacing in EURO-CORDEX daily precipitation distributions is, in comparison, small in most regions and seasons outside mountainous regions and coastal regions. Our results show that both high-resolution GCMs and CORDEX RCMs provide adequate information to end users at a 50 km scale The PRIMAVERA project is funded by the European Union's Horizon 2020 programme, grant agreement no. 641727. We acknowledge the World Climate Research Programme's Working Group on Regional Climate and the Working Group on Coupled Modelling, the former coordinating body of CORDEX and responsible panel for CMIP5. We also thank all the climate modelling groups (listed in Tables 1 and 2 of this paper) for producing and making available their model output. We also acknowledge the Earth System Grid Federation infrastructure, an international effort led by the U.S. Department of Energy's Program for Climate Model Diagnosis and Intercomparison, the European Network for Earth System Modelling, and other partners in the Global Organisation for Earth System Science Portals (GO-ESSP). Marie-Estelle Demory, Silje L. Sørland, Roman Brogli, and Christoph Schär acknowledge the Partnership for advanced computing in Europe (PRACE) for awarding us access to Piz Daint at ETH Zürich/Swiss National Supercomputing Centre (Switzerland) for conducting COSMO simulations. This work used JASMIN, the UK's collaborative data analysis environment (http://jasmin.ac.uk, last access: July 2020). Ségolène Berthou gratefully acknowledges funding from the European Union under Horizon 2020 project European Climate Prediction System (EUCP; grant agreement: 776613). Jesús Fernández acknowledges support from the Spanish R&D Program through project INSIGNIA (CGL2016-79210-R), co-funded by the European Regional Development Fund (ERDF/FEDER). We acknowledge the E-OBS dataset from the EU-FP6 project UERRA (http://www.uerra.eu, last access: September 2019) and the data providers in the ECA&D project (https://www.ecad.eu, last access: September 2019). We acknowledge the CARPATCLIM Database © European Commission – JRC, 2013. The authors thank IPMA for the PT02 precipitation dataset, as well as AEMET and UC for the Spain02 dataset, available at http://www.meteo.unican.es/datasets/spain02 (last access: September 2019). The SAFRAN dataset was provided by METEO FRANCE. The European Climate Prediction system, which provided UKCPobs, is funded by the European Union's Horizon 2020 programme, grant agreement no. 776613. We thank the Federal Office of Meteorology and Climatology MeteoSwiss for providing the Alpine precipitation grid dataset (EURO4M-APGD) developed as part of the EU project EURO4M (http://www.euro4m.eu, last access: September 2019). The authors would like to thank Andreas F. Prein and an anonymous referee for their thorough review and constructive comments that contributed to the improvement of this paper.

In this study, we evaluate a set of high-resolution (25–50 km horizontal grid spacing) global climate models (GCMs) from the High-Resolution Model Intercomparison Project (HighResMIP), developed as part of the EU-funded PRIMAVERA (Process-based climate simulation: Advances in high resolution modelling and European climate risk assessment) project, and from the EURO-CORDEX (Coordinated Regional Climate Downscaling Experiment) regional climate models (RCMs) (12–50 km horizontal grid spacing) over a European domain. It is the first time that an assessment of regional climate information using ensembles of both GCMs and RCMs at similar horizontal resolutions has been possible. The focus of the evaluation is on the distribution of daily precipitation at a 50 km scale under current climate conditions. Both the GCM and RCM ensembles are evaluated against high-quality gridded observations in terms of spatial resolution and station density. We show that both ensembles outperform GCMs from the 5th Coupled Model Intercomparison Project (CMIP5), which cannot capture the regional-scale precipitation distribution properly because of their coarse resolutions. PRIMAVERA GCMs generally simulate precipitation distributions within the range of EURO-CORDEX RCMs. Both ensembles perform better in summer and autumn in most European regions but Published by Copernicus Publications on behalf of the European Geosciences Union. 5486 M.-E. Demory et al.: European daily precipitation in EURO-CORDEX RCMs and HighResMIP GCMs tend to overestimate precipitation in winter and spring. PRIMAVERA shows improvements in the latter by reducing moderate-precipitation rate biases over central and western Europe. The spatial distribution of mean precipitation is also improved in PRIMAVERA. Finally, heavy precipitation simulated by PRIMAVERA agrees better with observations in most regions and seasons, while CORDEX overestimates precipitation extremes. However, uncertainty exists in the observations due to a potential under catch error, especially during heavy-precipitation events. The analyses also confirm previous findings that, although the spatial representation of precipitation is improved, the effect of increasing resolution from 50 to 12 km horizontal grid spacing in EURO-CORDEX daily precipitation distributions is, in comparison, small in most regions and seasons outside mountainous regions and coastal regions. Our results show that both high-resolution GCMs and CORDEX RCMs provide adequate information to end users at a 50 km scale

Interactions between the land surface and the atmosphere play a fundamental role in the weather and climate system. Here we present a comparison of summertime land?atmosphere coupling strength found in a subset of the ERA?Interim?driven European domain Coordinated Regional Climate Downscaling Experiment (EURO?CORDEX) model ensemble (1989?2008). Most of the regional climate models (RCMs) reproduce the overall soil moisture interannual variability, spatial patterns, and annual cycles of surface exchange fluxes for the different European climate zones suggested by the observational Global Land Evaporation Amsterdam Model (GLEAM) and FLUXNET data sets. However, some RCMs differ substantially from FLUXNET observations for some regions. The coupling strength is quantified by the correlation between the surface sensible and the latent heat flux, and by the correlation between the latent heat flux and 2?m temperature. The first correlation is compared to its estimate from the few available long?term European high?quality FLUXNET observations, and the latter to results from gridded GLEAM data. The RCM simulations agree with both observational datasets in the large?scale pattern characterized by strong coupling in southern Europe and weak coupling in northern Europe. However, in the transition zone from strong to weak coupling covering large parts of central Europe many of the RCMs tend to overestimate the coupling strength in comparison to both FLUXNET and GLEAM. The RCM ensemble spread is caused primarily by the different land surface models applied, and by the model?specific weather conditions resulting from different atmospheric parameterizations. The authors like to thank the coordination and the participating institutes of the EURO‐CORDEX initiative for making this study possible. The contribution from Centre de Recherche Public‐Gabriel Lippmann (labeled here as “MIUB”) (now Luxembourg Institute of Science and Technology, LIST) was funded by the Luxembourg National Research Fund (FNR) through grant FNR C09/SR/16 (CLIMPACT). The John von Neumann Institute for Computing and the Forschungszentrum Jülich provided the required compute time for the project JJSC15. Work is furthermore sponsored through a research and development cooperation on hydrometeorology between the Federal Institute of Hydrology, Koblenz, Germany, and the Meteorological Institute, University of Bonn, Bonn, Germany. The KNMI‐RACMO simulation was supported by the Dutch Ministry of Infrastructure and the Environment. The simulations of the Universidad de Cantabria were supported by the CORWES project (CGL2010‐22158‐C02), funded by the Spanish R&D Programme and by the FP7 grant 308291 (EUPORIAS). We acknowledge Santander Supercomputacion support group at the University of Cantabria, who provided access to the Altamira Supercomputer at the Institute of Physics of Cantabria (IFCA‐CSIC), member of the Spanish Supercomputing Network. Rowan Fealy acknowledges the financial support provided by the Irish Environmental Protection Agency and the use of Maynooth University's high‐performance computer and the Irish Centre for High End Computing (ICHEC) Stokes facility. The work done by Rita M. Cardoso and Pedro M.M. Soares was financed the Portuguese Science Foundation (FCT) under Project SOLAR‐PTDC/GEOMET/7078/2014. The work of University of Hohenheim as part of the Project RU 1695 was funded by German Science Foundation (DFG). WRF‐UHOH simulations were carried out at the supercomputing center HLRS in Stuttgart (Germany). The CLMcom‐CCLM simulation was supported by the German Federal Ministry of Education and Research (BMBF) and the German Climate Computing Centre (DKRZ). AUTH‐DMC acknowledges the technical support of AUTH‐Scientific Computing Center, the HellasGrid/EGI infrastructure, and the financial support of AUTH‐Research Committee (Pr.Nr. 91376 and 87783). This work used eddy covariance data acquired by the FLUXNET community. We acknowledge the financial support to the eddy covariance data harmonization (www.fluxdata.org). The ERA‐Interim data were accessed from http://apps.ecmwf.int/datasets/. The GLEAM data were accessed from www.gleam.eu/#downloads. The analysis results and the underlying RCM data base are available upon request (sknist@uni‐bonn.de). The data are archived at the Jülich Supercomputing Centre, Research Centre Jülich, Jülich, Germany. We thank the anonymous reviewers for their detailed and constructive comments.

Medicanes are cyclones over the Mediterranean Sea having a tropical structure and a rather small size, for which the sea-atmosphere interaction plays a fundamental role. High resolution and ocean-atmosphere coupled RCM simulations performed in MedCORDEX and EURO-CORDEX projects are used to analyze the ability of RCMs to represent the observed characteristics of medicanes, and the impact of increasing resolution and using air-sea coupling on its simulation. An observational database based on satellite images combined with very high resolution simulations (Miglietta et al. 2013) is used as the reference for evaluating the simulations. The simulated medicanes do not coincide in general with the observed cases, so that the evaluation should be done in a statistical sense. The spatial distribution of medicanes is generally well simulated, while the monthly distribution reveals the difficulty of simulating the first medicanes appearing in September after the summer minimum. Large differences are found among models, supporting the use of multi-model ensembles. Interesting trade-offs are found for some models, as better values for intensity are associated to worse frequency values in one model, or relatively good values of frequency and intensity are obtained at the expense of a damped air-sea interaction in a model with spectral nudging. High resolution has a strong and positive impact on the frequency of simulated medicanes, while the effect on its intensity is less clear. Air-sea coupling reduces the medicane frequency, as could be expected due to a negative intensity feedback that is known for tropical cyclones. A preliminary analysis indicates that this feedback could depend on the oceanic mixed layer depth, increasing the interest of applying ocean-atmosphere coupled RCMs.

International audience; Interactions between the land surface and the atmosphere play a fundamental role in the weather and climate system. Here we present a comparison of summertime land-atmosphere coupling strength found in a subset of the ERA-Interim-driven European domain Coordinated Regional Climate Downscaling Experiment (EURO-CORDEX) model ensemble (1989-2008). Most of the regional climate models (RCMs) reproduce the overall soil moisture interannual variability, spatial patterns, and annual cycles of surface exchange fluxes for the different European climate zones suggested by the observational Global Land Evaporation Amsterdam Model (GLEAM) and FLUXNET data sets. However, some RCMs differ substantially from FLUXNET observations for some regions. The coupling strength is quantified by the correlation between the surface sensible and the latent heat flux, and by the correlation between the latent heat flux and 2 m temperature. The first correlation is compared to its estimate from the few available long-term European high-quality FLUXNET observations, and the latter to results from gridded GLEAM data. The RCM simulations agree with both observational datasets in the large-scale pattern characterized by strong coupling in southern Europe and weak coupling in northern Europe. However, in the transition zone from strong to weak coupling covering large parts of central Europe many of the RCMs tend to overestimate the coupling strength in comparison to both FLUXNET and GLEAM. The RCM ensemble spread is caused primarily by the different land surface models applied, and by the model-specific weather conditions resulting from different atmospheric parameterizations.

Medicanes are cyclones over the Mediterranean Sea having a tropical-like structure but a rather small size, that can produce significant damage due to the combination of intense winds and heavy precipitation. Future climate projections, performed generally with individual atmospheric climate models, indicate that the intensity of the medicanes could increase under climate change conditions. The availability of large ensembles of high resolution and ocean– atmosphere coupled regional climate model (RCM) simulations, performed in MedCORDEX and EURO-CORDEX projects, represents an opportunity to improve the assessment of the impact of climate change on medicanes. As a first step towards such an improved assessment, we analyze the ability of the RCMs used in these projects to reproduce the observed characteristics of medicanes, and the impact of increased resolution and air-sea coupling on their simulation. In these storms, air-sea interaction plays a fundamental role in their formation and intensification, a different mechanism from that of extra-tropical cyclones, where the baroclinic instability mechanism prevails. An observational database, based on satellite images combined with high resolution simulations (Miglietta et al. in Geophys Res Lett 40:2400– 2405, 2013), is used as a reference for evaluating the simulations. In general, the simulated medicanes do not coincide on a case-by-case basis with the observed medicanes. However, observed medicanes with a high intensity and relatively long duration of tropical characteristics are better replicated in simulations. The observed spatial distribution of medicanes is generally well simulated, while the monthly distribution reveals the difficulty of simulating the medicanes that first appear in September after the summer minimum in occurrence. Increasing the horizontal resolution has a systematic and generally positive impact on the frequency of simulated medicanes, while the general underestimation of their intensity is not corrected in most cases. The capacity of a few models to better simulate the medicane intensity suggests that the model formulation is more important than reducing the grid spacing alone. A negative intensity feedback is frequently the result of air-sea interaction for tropical cyclones in other basins. The introduction of air-sea coupling in the present simulations has an overall limited impact on medicane frequency and intensity, but it produces an interesting seasonal shift of the simulated medicanes from autumn to winter. This fact, together with the analysis of two contrasting particular cases, indicates that the negative feedback could be limited or even absent in certain situations. We suggest that the effects of air-sea interaction on medicanes may depend on the oceanic mixed layer depth, thus increasing the applicability of ocean–atmosphere coupled RCMs for climate change analysis of this kind of cyclones.

In this study, we evaluate a set of high-resolution (25–50 km horizontal grid spacing) global climate models (GCMs) from the High-Resolution Model Intercomparison Project (HighResMIP), developed as part of the EU-funded PRIMAVERA (Process-based climate simulation: Advances in high resolution modelling and European climate risk assessment) project, and from the EURO-CORDEX (Coordinated Regional Climate Downscaling Experiment) regional climate models (RCMs) (12–50 km horizontal grid spacing) over a European domain. It is the first time that an assessment of regional climate information using ensembles of both GCMs and RCMs at similar horizontal resolutions has been possible. The focus of the evaluation is on the distribution of daily precipitation at a 50 km scale under current climate conditions. Both the GCM and RCM ensembles are evaluated against high-quality gridded observations in terms of spatial resolution and station density. We show that both ensembles outperform GCMs from the 5th Coupled Model Intercomparison Project (CMIP5), which cannot capture the regional-scale precipitation distribution properly because of their coarse resolutions. PRIMAVERA GCMs generally simulate precipitation distributions within the range of EURO-CORDEX RCMs. Both ensembles perform better in summer and autumn in most European regions but tend to overestimate precipitation in winter and spring. PRIMAVERA shows improvements in the latter by reducing moderate-precipitation rate biases over central and western Europe. The spatial distribution of mean precipitation is also improved in PRIMAVERA. Finally, heavy precipitation simulated by PRIMAVERA agrees better with observations in most regions and seasons, while CORDEX overestimates precipitation extremes. However, uncertainty exists in the observations due to a potential undercatch error, especially during heavy-precipitation events. The analyses also confirm previous findings that, although the spatial representation of precipitation is improved, the effect of increasing resolution from 50 to 12 km horizontal grid spacing in EURO-CORDEX daily precipitation distributions is, in comparison, small in most regions and seasons outside mountainous regions and coastal regions. Our results show that both high-resolution GCMs and CORDEX RCMs provide adequate information to end users at a 50 km scale., Geoscientific Model Development, 13 (11), ISSN:1991-9603, ISSN:1991-959X