Climate Dynamics

, Volume 32, Issue 5, pp 615–634 | Cite as

A multi-model ensemble approach for assessment of climate change impact on surface winds in France

  • Julien NajacEmail author
  • Julien Boé
  • Laurent Terray


Statistical downscaling of 14 coupled atmosphere-ocean general circulation models (AOGCM) is presented to assess potential changes of the 10 m wind speeds in France. First, a statistical downscaling method is introduced to estimate daily mean 10 m wind speed at specific sites using general circulation model output. Daily 850 hPa wind field has been selected as the large scale circulation predictor. The method is based on a classification of the daily wind fields into a few synoptic weather types and multiple linear regressions. Years are divided into an extended winter season from October to March and an extended summer season from April to September, and the procedure is conducted separately for each season. ERA40 reanalysis and observed station data have been used to build and validate the downscaling algorithm over France for the period 1974–2002. The method is then applied to 14 AOGCMs of the coupled model intercomparison project phase 3 (CMIP3) multi-model dataset. Three time periods are focused on: a historical period (1971–2000) from the climate of the twentieth century experiment and two climate projection periods (2046–2065 and 2081–2100) from the IPCC SRES A1B experiment. Evolution of the 10 m wind speed in France and associated uncertainties are discussed. Significant changes are depicted, in particular a decrease of the wind speed in the Mediterranean area. Sources of those changes are investigated by quantifying the effects of changes in the weather type occurrences, and modifications of the distribution of the days within the weather types.


Statistical downscaling Wind energy Climate change Multi-model ensemble Impact study 



J. Najac Ph.D. grant was partly supported by Electricité de France (EDF). ECMWF ERA-40 data were obtained from the ECMWF data server. The authors are grateful to the Division de la Climatologie (DCLIM) at Météo-France for providing the SQR dataset. We acknowledge the modeling groups, the Program for Climate Model Diagnosis and Intercomparison (PCMDI) and the WCRP’s Working Group on Coupled Modeling (WGCM) for their roles in making available the WCRP CMIP3 multi-model dataset. Support of this dataset is provided by the Office of Science, U.S. Department of Energy. Some statistical calculations have been performed with Statpack, developed by P. Terray (IPSL/LOCEAN). We would like to thank S. Parey, C. Fil-Tardieu and C. Cassou for stimulating discussion about this work, and the anonymous reviewers for their constructive comments which helped to improve this article.


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Copyright information

© Springer-Verlag 2008

Authors and Affiliations

  1. 1.Climate Modeling and Global Change TeamCERFACS/CNRS, SUC URA1875Toulouse Cedex 1France

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