Publication: Variability and predictability of West African Droughts: a review on the role of sea surface temperature anomalies
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2015-05
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Abstract
The Sahel experienced a severe drought during the 1970s and 1980s after wet periods in the 1950s and 1960s. Although rainfall partially recovered since the 1990s, the drought had devastating impacts on society. Most studies agree that this dry period resulted primarily from remote effects of sea surface temperature (SST) anomalies amplified by local land surface-atmosphere interactions. This paper reviews advances made during the last decade to better understand the impact of global SST variability on West African rainfall at interannual to decadal time scales. At interannual time scales, a warming of the equatorial Atlantic and Pacific/Indian Oceans results in rainfall reduction over the Sahel, and positive SST anomalies over the Mediterranean Sea tend to be associated with increased rainfall. At decadal time scales, warming over the tropics leads to drought over the Sahel, whereas warming over the North Atlantic promotes increased rainfall. Prediction systems have evolved from seasonal to decadal forecasting. The agreement among future projections has improved from CMIP3 to CMIP5, with a general tendency for slightly wetter conditions over the central part of the Sahel, drier conditions over the western part, and a delay in the monsoon onset. The role of the Indian Ocean, the stationarity of teleconnections, the determination of the leader ocean basin in driving decadal variability, the anthropogenic role, the reduction of the model rainfall spread, and the improvement of some model components are among the most important remaining questions that continue to be the focus of current international projects.
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© 2015 American Meteorological Society. Artículo firmado por 25 autores.
Belen Rodríguez-Fonseca, Elsa Mohino, and C. Roberto Mechoso wrote and organized this review. We thank additional contributions by the other authors as follows. Section 1:William Lau, Edward K. Vizy, Kerry Cook, and Serge Janicot; section 2a: Teresa Losada and Irene Polo; section 2b: Marco Gaetani and Bernard Fontaine; section 2c: David P. Rowell; section 2d: Juergen Bader; section 2e: Aurore Voldoire and David P. Rowell; section 3b: Yongkang Xue and Fred Kucharski; section 4: Alberto Arribas, Andrew Colman, and M. Vellinga; section 5: Javier Garcia-Serrano, Francisco Doblas Reyes, Lisa Goddard, and Marco Gaetani; and section 6: Cyril Caminade, Michela Biasutti, Leonard Druyan, Edward K. Vizy, and Kerry Cook.
This work was supported by Spanish projects MINECO CGL2011-13564-E and GL2012-38923-C02-01. Support from the U.S. National Science Foundation (Awards SES-1048946, ATM-1036604, AGS-1041477, and AGS-1115506) is gratefully acknowledged. Also gratefully acknowledged are the GCM modeling groups, the Program for Climate Model Diagnosis and Intercomparison (PCMDI), and the World Climate Research Programme's Working Group on Coupled Modeling (WGCM) for their roles in making available the WCRP CMIP5 multimodel dataset. Support of this dataset is provided by the Office of Science, U.S. Department of Energy (DOE). We acknowledge the EU QWECI, PREFACE, and SPECS projects both funded by the European Commission's Seventh Framework Research Programme under Grant Agreements 243964, 603521, and 308378 respectively. Based on a French initiative, AMMA was built by an international scientific group and is currently funded by a large number of agencies, especially from France, the United Kingdom, the United States, and Africa. It has been the beneficiary of a major financial contribution from the European Community's Sixth Framework Research Programme. The authors are grateful to Ashlynn Fiss for her help in improving this manuscript.
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