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What are the dominant features of rainfall leading to realistic large‐scale crop yield simulations in West Africa?
Author(s) -
Berg Alexis,
Sultan Benjamin,
de NobletDucoudré Nathalie
Publication year - 2010
Publication title -
geophysical research letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.007
H-Index - 273
eISSN - 1944-8007
pISSN - 0094-8276
DOI - 10.1029/2009gl041923
Subject(s) - scale (ratio) , yield (engineering) , climatology , environmental science , range (aeronautics) , spatial ecology , climate change , crop , sensitivity (control systems) , meteorology , geography , geology , cartography , engineering , ecology , aerospace engineering , electronic engineering , forestry , oceanography , materials science , metallurgy , biology
A large‐scale crop model is forced by a range of climate datasets over West Africa to test the sensitivity of simulated yields to errors in input rainfall. The model skill, defined as the correlation between observed and simulated yield anomalies over 1968–1990 at the country scale, is used for assessment. We show that there are two essential rainfall features for the model to skillfully simulate interannual yield variability at the country scale: cumulative annual variability and frequency. At such a scale, providing additional information on intraseasonal variability, such as the chronology of rain events, does not improve the model skill. We suggest that such information is relevant at smaller spatial scales but is not spatially consistent enough to impact large‐scale yield variability.