Extremely high temperatures in France at the end of the century
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Power plant construction requires anticipation to achieve a liable dimensioning on the long functioning time of the installation. In the present climate change context, dimensioning towards extremely high temperature for installations intended to run until the 2070s or later implies an evaluation of plausible extreme values at this time scale. This study is devoted to such an estimation for France, using both observation series and climate model simulation results. The climate model results are taken from the European PRUDENCE (Prediction of Regional scenarios and Uncertainties for Defining European Climate change risks and Effects) project database of regional climate change scenarios for Europe. Comparison of high summer temperature distributions given by observations and climate models under current climate conditions, conducted using Generalized Extreme Value distribution, reveals that only a few models are able to correctly reproduce it. For these models, climate change under IPCC A2 and B2 scenarios leads to differences in the variability of high values, whose proportion has an important impact on future 100-year return levels.
KeywordsClimate change High temperature extremes Regional climate models
This work uses results from European Project PRUDENCE, supported by the European Commission Programme Energy, Environment and Sustainable Development under contract EVK2-2001-00156, and from French GICC-IMFREX project supported by the Department of Environment (MEDD). The author is grateful to Dr. O. B. Christensen (DMI) for preparing the database with regional scenarios and to Dr. M. Déqué for managing project IMFREX and preparing the database. Author’s thanks go to Professor Didier Dacunha-Castelle too, for his kind advises regarding statistical aspects of the study. Lastly, thanks to the reviewers whose comments have contributed to greatly improve the paper.
- Coles S (2001) An introduction to statistical modeling of extreme values. Springer Series in Statistics. Springer, BerlinGoogle Scholar
- Déqué M, Jones RG, Wild M, Giorgi F, Christensen JH, Hassel DC, Vidale PL, Rockel B, Jacob D, Kjellström E, de Castro M, Kucharski F, van den Hurk B (2005) Global high resolution versus Limited Area Model climate change projections over Europe: quantifying confidence level from PRUDENCE results. Clim Dyn 25(6):653–670CrossRefGoogle Scholar
- IPCC Third Assessment Report, 2001Google Scholar
- Leadbetter MR, Lindgren G, Rootzen H (1983) Extremes and related properties of random sequences and series. Springer, New YorkGoogle Scholar
- Meehl GA, Karl T, Easterling DR, Changnon S, Pielke R, Changnon D, Evans J, Groisman PY, Knutson TT, Kunkel KE, Mearns LO, Parmesan C, Pulwarty R, Root T, Sylves RT, Whetton P, Zwiers F (2000) An introduction to trends in extreme weather and climate projections: observations, socioeconomic impacts and model projections. Bull AMS 81(3):413–416CrossRefGoogle Scholar
- Moisselin J-M (2004) Long term reference series of Météo-France. In: Proceedings of the EMS/ECAC conference, NiceGoogle Scholar
- Nogaj M, Parey S, Dacunha-Castelle D (2007) Non-stationary extreme models and a climatic application. Nonlinear process in Geophys (in press)Google Scholar
- Prediction of Regional Scenarios and Uncertainties for Defining European Climate Change Risks and Effects: the PRUDENCE project. Climatic Change, volume 81, Supplement 1, May 2007Google Scholar