Climate Dynamics

, Volume 41, Issue 9–10, pp 2555–2575 | Cite as

The simulation of European heat waves from an ensemble of regional climate models within the EURO-CORDEX project

  • Robert VautardEmail author
  • Andreas Gobiet
  • Daniela Jacob
  • Michal Belda
  • Augustin Colette
  • Michel Déqué
  • Jesús Fernández
  • Markel García-Díez
  • Klaus Goergen
  • Ivan Güttler
  • Tomáš Halenka
  • Theodore Karacostas
  • Eleni Katragkou
  • Klaus Keuler
  • Sven Kotlarski
  • Stephanie Mayer
  • Erik van Meijgaard
  • Grigory Nikulin
  • Mirta Patarčić
  • John Scinocca
  • Stefan Sobolowski
  • Martin Suklitsch
  • Claas Teichmann
  • Kirsten Warrach-Sagi
  • Volker Wulfmeyer
  • Pascal Yiou


The ability of a large ensemble of regional climate models to accurately simulate heat waves at the regional scale of Europe was evaluated. Within the EURO-CORDEX project, several state-of-the art models, including non-hydrostatic meso-scale models, were run for an extended time period (20 years) at high resolution (12 km), over a large domain allowing for the first time the simultaneous representation of atmospheric phenomena over a large range of spatial scales. Eight models were run in this configuration, and thirteen models were run at a classical resolution of 50 km. The models were driven with the same boundary conditions, the ERA-Interim re-analysis, and except for one simulation, no observations were assimilated in the inner domain. Results, which are compared with daily temperature and precipitation observations (ECA&D and E-OBS data sets) show that, even forced by the same re-analysis, the ensemble exhibits a large spread. A preliminary analysis of the sources of spread, using in particular simulations of the same model with different parameterizations, shows that the simulation of hot temperature is primarily sensitive to the convection and the microphysics schemes, which affect incoming energy and the Bowen ratio. Further, most models exhibit an overestimation of summertime temperature extremes in Mediterranean regions and an underestimation over Scandinavia. Even after bias removal, the simulated heat wave events were found to be too persistent, but a higher resolution reduced this deficiency. The amplitude of events as well as the variability beyond the 90th percentile threshold were found to be too strong in almost all simulations and increasing resolution did not generally improve this deficiency. Resolution increase was also shown to induce large-scale 90th percentile warming or cooling for some models, with beneficial or detrimental effects on the overall biases. Even though full causality cannot be established on the basis of this evaluation work, the drivers of such regional differences were shown to be linked to changes in precipitation due to resolution changes, affecting the energy partitioning. Finally, the inter-annual sequence of hot summers over central/southern Europe was found to be fairly well simulated in most experiments despite an overestimation of the number of hot days and of the variability. The accurate simulation of inter-annual variability for a few models is independent of the model bias. This indicates that internal variability of high summer temperatures should not play a major role in controlling inter-annual variability. Despite some improvements, especially along coastlines, the analyses conducted here did not allow us to generally conclude that a higher resolution is clearly beneficial for a correct representation of heat waves by regional climate models. Even though local-scale feedbacks should be better represented at high resolution, combinations of parameterizations have to be improved or adapted accordingly.


Regional climate modeling Heat waves Model evaluation Climate projection EURO-CORDEX 



The EURO-CORDEX simulations and analysis were carried out in several groups within the framework of the IMPACT2C FP7 project (Grant FP7-ENV.2011.1.1.6-1). The BTU Cottbus offered an exchange ftp site for sharing all model simulation files. The contribution from CRP-GL was funded by the Luxembourg National Research Fund (FNR) through Grant FNR C09/SR/16 (CLIMPACT). We acknowledge financial support from the Spanish R&D program through Grants CGL2010-21869 (EXTREMBLES) and CGL2010-22158-C02-01 (CORWES). Charles University runs were supported partially in framework of the Research Plan of MSMT (No. MSM 0021620860) and GACR project No. P209/11/2405. The contribution from UHOH was funded by the German Science Foundation (DFG) through project FOR 1695. The REMO simulations were supported by CSC, MPI, as well as BMBF and performed under the “Konsortial” share at the German Climate Computing Centre (DKRZ), as well as the CCLM simulations carried out by BTU, which we are further thankful for their various support. We are thankful to the French CCRT/TGCC supercomputing center support and the CEA and GENCI computing resource allocation agency for the WRF-IPSL-INERIS runs. The development of the modeling chain at INERIS and IPSL was carried out in part within the French national project SALUT’AIR (PRIMEQUAL research program). Part of SMHI contribution was done in the ECLISE projects that receive funding from the European Union Seventh Framework Programme (FP7/2007–2013) under Grant agreement 265240 and in the Swedish Mistra-SWECIA programme founded by Mistra (the Foundation for Strategic Environmental Research). DHMZ contribution was partially supported by the Croatian Ministry of Science, Education and Sports (Grant No. 004-1193086-3035). We also acknowledge the Research Committee of AUTH for the financial support, the Scientific Computing Center of AUTH for the technical support and the EGI and HellasGrid infrastructures for the provision of computational resources. The BCCR contribution was supported in part by the Center for Climate Dynamics (SKD). We acknowledge the E-OBS dataset from the EU-FP6 project ENSEMBLES ( and the data providers in the ECA&D project ( The Climate Data Operators software was extensively used throughout this analysis (


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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Robert Vautard
    • 1
    Email author
  • Andreas Gobiet
    • 2
  • Daniela Jacob
    • 3
  • Michal Belda
    • 4
  • Augustin Colette
    • 5
  • Michel Déqué
    • 6
  • Jesús Fernández
    • 7
  • Markel García-Díez
    • 8
  • Klaus Goergen
    • 9
  • Ivan Güttler
    • 10
  • Tomáš Halenka
    • 4
  • Theodore Karacostas
    • 11
  • Eleni Katragkou
    • 11
  • Klaus Keuler
    • 12
  • Sven Kotlarski
    • 13
  • Stephanie Mayer
    • 14
  • Erik van Meijgaard
    • 18
  • Grigory Nikulin
    • 15
  • Mirta Patarčić
    • 10
  • John Scinocca
    • 16
  • Stefan Sobolowski
    • 14
  • Martin Suklitsch
    • 2
  • Claas Teichmann
    • 17
  • Kirsten Warrach-Sagi
    • 19
  • Volker Wulfmeyer
    • 19
  • Pascal Yiou
    • 1
  1. 1.Laboratoire des Sciences du Climat et de l’EnvironnementIPSL, CEA/CNRS/UVSQGif sur YvetteFrance
  2. 2.Wegener Center for Climate and Global Change and Institute for Geophysics, Astrophysics, and MeteorologyUniversity of GrazGrazAustria
  3. 3.Climate Service CenterHamburgGermany
  4. 4.Department of Meteorology and Environment ProtectionCharles UniversityPragueCzech Republic
  5. 5.Institut National de l’Environnement industriel et des risques (INERIS)Verneuil en HalatteFrance
  6. 6.Météo-France/CNRM, CNRS/GAMEToulouseFrance
  7. 7.Department Applied Mathematics and Computer ScienceUniversidad de CantabriaSantanderSpain
  8. 8.Instituto de Física de CantabriaCSIC—UCSantanderSpain
  9. 9.Centre de Recherche Public—Gabriel LippmannBelvauxLuxembourg
  10. 10.Croatian Meteorological and Hydrological Service (DHMZ)ZagrebCroatia
  11. 11.Department of Meteorology and Climatology, School of GeologyAristotle University of ThessalonikiThessalonikiGreece
  12. 12.Chair of Environmental MeteorologyBrandenburg University of Technology (BTU) CottbusCottbusGermany
  13. 13.Institute for Atmospheric and Climate ScienceETH ZurichZurichSwitzerland
  14. 14.Uni ResearchBjerknes Center for Climate ResearchBergenNorway
  15. 15.Swedish Meteorological and Hydrological InstituteNorrköpingSweden
  16. 16.Environment CanadaCanadian Centre for Climate Modelling and AnalysisVictoriaBritish Columbia
  17. 17.Max-Planck-Institut für MeteorologieHamburgGermany
  18. 18.Royal Netherlands Meteorological Institute (KNMI)De BiltThe Netherlands
  19. 19.Institute of Physics and MeteorologyUniversity of HohenheimStuttgartGermany

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