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Coupling climate and crop models
B. Sultan a , A. Alhassane, P. Oettli, S. Traoré, C. Baron, B. Muller b , and M. Dingkuhn b
a) IPSL/CNRS, 4 Place Jussieu, 75252 Paris Cedex
b) CIRAD, Montpellier, France
Global circulation models (GCM) are increasingly capable
of making relevant predictions of seasonal and long-term
climate variability, thus improving prospects of predicting
impact on crop yields. This is particularly important for
semi-arid West Africa where climate variability and drought
threaten food security. Translating GCM outputs into
attainable crop yields is difficult because GCM grid boxes
are of larger scale than the processes governing yield,
involving partitioning of rain among runoff, evaporation,
transpiration, drainage and storage at plot scale. This study
will analyze the bias introduced to crop simulation when
climatic data is aggregated spatially or in time, resulting in
loss of relevant variation. It will also show some
downscaling perspectives and results from the AMMA
program focused on the use of IPCC AR5 simulations to
estimate future yields in West Africa.