Evolution Des Indices Pluviométriques Extrêmes Par L'analyse De Modèles Climatiques Régionaux Du Programme CORDEX: Les Projections Climatiques Sur Le Sénégal

Abstract

This study aims at characterizing the extreme rainfall events over West Africa particularly in the Sahel region and Senegal by 2100 (far future) under the greenhouse gas emission scenario RCP8.5 by analyzing the simulations of four (4) regional climate models (RCMs) of CORDEX (Regional COordinated climate Downscaling Experiment) program. The study of these extreme climate indices is crucial for the understanding of the impacts of climate change on some vital socio-economic sectors such as the agriculture in Sahel and Senegal. The results show that almost all the RCMs predict a decrease of the rainfall over most parts of the Sahel region particularly over the Western Sahel. The analysis of the climate indices such as the highest one day precipitation amount, the 99th percentile and the maximum dry spell length (CDD) shows that the RCMs (except CanRCM4) project an increase of these exceptional rainfall events over the Sahel (especially over the Western Sahel) by 2100. In Senegal, the RCMs (except RCA4) agree on a decrease of the precipitation and the number of wet days by 2100. When considering the evolution of rainfall events intensity, the highest one day precipitation amount and the 99th percentile, the RCMs (except CanRCM4) predict an increase of the extreme events which may translate into strong floods in Senegal. As for the dry and wet sequences, the RCMs projections (except those of RCA4) show an increase (respectively a decrease) of the maximum dry spell length (respectively of the maximum wet spell length) in Senegal. This increase in extreme rainfall indices may translate into a strengthening of natural disasters such as floods and drought. This work can be considered as a support for the policymakers in West Africa and particularly in Senegal for the better long-term planning of water resources and disaster management as wells as the build of a resilient agricultural system.