Didier Francois

Détection du changement régional par rééchantillonnage de séries chronologiques : application aux précipitations dans l’espace rhéno-mosan

Regional change detection through a boostrap resampling procedure: application to rainfall time series in the upper Rhine-Meuse area A boostrap resampling method has been applied to rainfall data (point times series and field values) to get the empirical distribution function of the number of significant tests. By preserving the cross-correlation structure of the network/field, this distribution shows the field significance. The region of interest is a mesoscale area with a semi-oceanic climate (90 000 km2, North-Eastern France and surrounding areas). Over the last decades winter westerly rainfall (seasonal amounts and maximum daily intensities) were subject to abrupt and gradual changes having a regional coherence. Topographical conditions are likely to modulate the spatial patterns and magnitude of changes. Statistical analysis of seasonal rainfall amounts downscaled on the French part of the Meuse basin for the end of the century yields a local and regional significant only for summer rainfall. Definitely, field significance and type of change vary according to the rainfall characteristics and their spatial persistency. Regional analysis of change in climate time series should be based on “early bird” sites or grid points poorly correlated in space and whose climate information is maximizing the signal to noise ratio.