Climate Dynamics

, Volume 32, Issue 5, pp 615–634

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

Article

DOI: 10.1007/s00382-008-0440-4

Cite this article as:
Najac, J., Boé, J. & Terray, L. Clim Dyn (2009) 32: 615. doi:10.1007/s00382-008-0440-4

Abstract

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.

Keywords

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

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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