[en] Mountain regions are highly vulnerable to climate change and are likely to be among the areas most impacted by global warming. But climate projections for the end of the 21. century are developed with general circulation models of climate, which do not present a sufficient horizontal resolution to accurately evaluate the impacts of warming on these regions. Several techniques are then used to perform a spatial down-scaling (on the order of 10 km). There are two categories of down-scaling methods: dynamical methods that require significant computational resources for the achievement of regional climate simulations at high resolution, and statistical methods that require few resources but an observation dataset over a long period and of good quality. In this study, climate simulations of the global atmospheric model ARPEGE projections over France are down-scaled according to a dynamical method, performed with the ALADIN-Climate regional model, and a statistical method performed with the software DSClim developed at CERFACS. The two down-scaling methods are presented and the results on the climate of the French mountains are evaluated for the current climate. Both methods give similar results for average snowfall. However extreme events of total precipitation (droughts, intense precipitation events) are largely underestimated by the statistical method. Then, the results of both methods are compared for two future climate projections, according to the greenhouse gas emissions scenario A1B of IPCC. The two methods agree on fewer frost days, a significant decrease in the amounts of solid precipitation and an average increase in the percentage of dry days of more than 10%. The results obtained on Corsica are more heterogeneous but they are questionable because the reduced spatial domain is probably not very relevant regarding statistical sampling. (authors)

[en] After some comments on climate modelling (models, scenarios, uncertainties, regional predictions), the first part reports the study of several temperature indices (minimum, average and maximum daily temperature, number of days with abnormally high or low temperature, number of days of heat wave, number of days with negative temperatures, and so on.), precipitation indices (daily and extreme precipitations, dry periods, snow falls). It also discusses soil humidity index, strong wind index, river flow rate, and sea level. The second part reports simulation results for indices in metropolitan France according to the French Aladin-Climat, LMDZ and MAR models. The third volume reports evolutions and predictions of average sea level at the planet scale and along the French coasts, and discusses impacts related to sea level change (coast erosion, submersion, salt intrusion)

[en] This publication presents the results of the RexHySS programme (research programme on the impact of climate change on water resources and hydrological extremes in the Seine and Somme river watersheds) which quantified the impact of climate change on the Seine water resource while taking the main uncertainty origins into account. Two scenarios of greenhouse gas emission, six climate models, three dis-aggregation methods and five hydrological models have been used. After a recall of the greenhouse effect principle, the report describes climate evolution and climate change (time history, climate modelling, assessment of climate models and debates about climate evolution, necessity of using dis-aggregation methods), proposes an overview of climate predictions (scenarios of greenhouse gas emission, climate prediction by the IPCC, dis-aggregated climate predictions used for the Seine watershed). It reports an assessment of the Seine basin climate and of its evolutions, and an analysis of the impact on the Seine watershed hydrology (hydrological models, impact studies, impact of climate change on water assessment, application to the Seine flow rates in Poses, impact of climate change on piezometry).