Représentation de la pluie dans les modeles régionaux de climat et application à l'estimation des rendements du mil au Sénégal

The strong influence of climatic factors on agriculture and food security in sub-Saharan Africa in addition to climate change perspectives have prompted the scientific community to document the impacts of climate in this region. However, if many studies quantifying the impacts of climate rely on downscaling, very few address the uncertainty associated with their use. However, the choice of a particular method and of a particular regional model can strongly influence the final result since crop models are very sensitive to the quality of the input climate forcing. The objective of this study is to address this issue by analysing the dispersion of rainfall provided by eight regional models and how this dispersion spreads in the estimation of millet yields in Senegal. The SARRAH crop model is used to simulate millet yields. The study shows that there is a wide dispersion in the representation of rainfall from one regional model to another (and even sometimes for the same regional model with two sets of parameters) at both the seasonal and intra-seasonal scales. These biases introduce significant errors in estimating the agronomic impacts, which might invalidate conclusions about the impacts of climate change based on the use of a single regional model. The use of a bias correction method is indispensable.