Climatic Change

, Volume 81, Supplement 1, pp 53–70 | Cite as

An intercomparison of regional climate simulations for Europe: assessing uncertainties in model projections

  • M. Déqué
  • D. P. Rowell
  • D. Lüthi
  • F. Giorgi
  • J. H. Christensen
  • B. Rockel
  • D. Jacob
  • E. Kjellström
  • M. de Castro
  • B. van den Hurk


Ten regional climate models (RCM) have been integrated with the standard forcings of the PRUDENCE experiment: IPCC-SRES A2 radiative forcing and Hadley Centre boundary conditions. The response over Europe, calculated as the difference between the 2071–2100 and the 1961–1990 means can be viewed as an expected value about which various uncertainties exist. Uncertainties are measured here by variance in eight sub-European boxes. Four sources of uncertainty can be evaluated with the material provided by the PRUDENCE project. Sampling uncertainty is due to the fact that the model climate is estimated as an average over a finite number of years (30). Model uncertainty is due to the fact that the models use different techniques to discretize the equations and to represent sub-grid effects. Radiative uncertainty is due to the fact that IPCC-SRES A2 is merely one hypothesis. Some RCMs have been run with another scenario of greenhouse gas concentration (IPCC-SRES B2). Boundary uncertainty is due to the fact that the regional models have been run under the constraint of the same global model. Some RCMs have been run with other boundary forcings. The contribution of the different sources varies according to the field, the region and the season, but the role of boundary forcing is generally greater than the role of the RCM, in particular for temperature. Maps of minimum expected 2m temperature and precipitation responses for the IPCC-A2 scenario show that, despite the above mentioned uncertainties, the signal from the PRUDENCE ensemble is significant.


Regional Climate Model Root Mean Square Difference Danish Meteorological Institute Hadley Centre High Resolution Regional Climate Model 
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.


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Copyright information

© Springer Science+Business Media, B.V. 2007

Authors and Affiliations

  • M. Déqué
    • 1
  • D. P. Rowell
    • 2
  • D. Lüthi
    • 3
  • F. Giorgi
    • 4
  • J. H. Christensen
    • 5
  • B. Rockel
    • 6
  • D. Jacob
    • 7
  • E. Kjellström
    • 8
  • M. de Castro
    • 9
  • B. van den Hurk
    • 10
  1. 1.Météo-FranceCentre National de Recherches MétéorologiquesToulouse Cedex 01France
  2. 2.Met OfficeHadley Centre for Climate Prediction and ResearchExeter, DevonUK
  3. 3.Swiss Federal Institute of Technology, Institute for Atmospheric and Climate Science, ETHZürichSwitzerland
  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.KNMIDe BiltThe Netherlands

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