Climate Dynamics

, Volume 25, Issue 6, pp 653–670 | Cite as

Global high resolution versus Limited Area Model climate change projections over Europe: quantifying confidence level from PRUDENCE results

  • M. DéquéEmail author
  • R. G. Jones
  • M. Wild
  • F. Giorgi
  • J. H. Christensen
  • D. C. Hassell
  • P. L. Vidale
  • B. Rockel
  • D. Jacob
  • E. Kjellström
  • M. de. Castro
  • F. Kucharski
  • B. van den Hurk


Four high resolution atmospheric general circulation models (GCMs) have been integrated with the standard forcings of the PRUDENCE experiment: IPCC-SRES A2 radiative forcing and Hadley Centre sea surface temperature and sea-ice extent. The response over Europe, calculated as the difference between the 2071–2100 and the 1961–1990 means is compared with the same diagnostic obtained with nine Regional Climate Models (RCM) all driven by the Hadley Centre atmospheric GCM. The seasonal mean response for 2m temperature and precipitation is investigated. For temperature, GCMs and RCMs behave similarly, except that GCMs exhibit a larger spread. However, during summer, the spread of the RCMs—in particular in terms of precipitation—is larger than that of the GCMs. This indicates that the European summer climate is strongly controlled by parameterized physics and/or high-resolution processes. The temperature response is larger than the systematic error. The situation is different for precipitation. The model bias is twice as large as the climate response. The confidence in PRUDENCE results comes from the fact that the models have a similar response to the IPCC-SRES A2 forcing, whereas their systematic errors are more spread. In addition, GCM precipitation response is slightly but significantly different from that of the RCMs.


Regional Climate Model Root Mean Square Difference Empirical Orthogonal Function Atmospheric General Circulation Model Precipitation Response 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



This work was supported by the European Commission Programme Energy, Environment and Sustainable Development under contract EVK2-2001-00156 (PRUDENCE). The French contribution was partly supported by the GICC-IMFREX contract of the Department of Environment (MEDD). The authors are grateful to Dr. O. B. Christensen (DMI) for preparing the database with regional scenarios.


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Copyright information

© Springer-Verlag 2005

Authors and Affiliations

  • M. Déqué
    • 1
    Email author
  • R. G. Jones
    • 2
  • M. Wild
    • 3
  • F. Giorgi
    • 4
  • J. H. Christensen
    • 5
  • D. C. Hassell
    • 2
  • P. L. Vidale
    • 3
  • B. Rockel
    • 6
  • D. Jacob
    • 7
  • E. Kjellström
    • 8
  • M. de. Castro
    • 9
  • F. Kucharski
    • 4
  • B. van den Hurk
    • 10
  1. 1.Météo-FranceCentre National de Recherches MétéorologiquesToulouse Cedex 01France
  2. 2.Met OfficeHadley Centre for Climate Prediction and ResearchDevonUK
  3. 3.Institute for Atmospheric and Climate Science, ETHSwiss Federal Institute of TechnologyZürichSwitzerland
  4. 4.Abdus Salam International Centre for Theoretical PhysicsTriesteItaly
  5. 5.Danish Meteorological InstituteCopenhagen ØDenmark
  6. 6.GKSS Forschungszentrum Geesthacht GmbHInstitute of Coastal ResearchGeesthachtGermany
  7. 7.Max-Planck-Institut für MeteorologieHamburgGermany
  8. 8.Swedish Meteorological and Hydrological InstituteNorrköpingSweden
  9. 9.Dept. de Ciencias AmbientalesUniversidad de Castilla La ManchaToledoSpain
  10. 10.KNMIAE De BiltNetherland

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