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Publication Date
1 March 2015

Derivation of an Observation-Based Map of North African Dust Emission

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Summary

By mass, aeolian dust is the most pervasive aerosol on the planet, and the largest fraction of all global dust emission is in North Africa. African dust emission and transport is both affected by—and affects—the climate. Once transported over the Atlantic, direct radiative forcing by dust both warms the atmosphere and cools the surface, contributing interannual-to-decadal scale variability of tropical Atlantic sea surface temperatures. A team of scientists, including a U.S. Department of Energy researcher at Pacific Northwest National Laboratory, developed a technique for creating a map of the annual mean emitted dust flux for North Africa. The map is based on retrievals of dust storm frequency from the satellite system, Meteosat Second Generation Spinning Enhanced Visible and InfraRed Imager (SEVIRI), and simulations of the relationship between dust storm frequency and emitted mass flux derived from the output of five models. They showed that these five models all agree that the Bodélé depression is one of the—if not the—most active dust sources in West Africa, both in terms of emission amount and frequency. None showed dust emission south of 12◦N. These results motivate the study of long-term variability of North Africa dust emission and transport, and how the environment affects regional dust emission.

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Acknowledgements

The authors would like to thank the two anonymous reviewers and the associate editor for their helpful and constructive comments on an earlier version of this manuscript. This work was supported by the French Agence Nationale de la Recherche (ANR) grant ANR-10-LABX-18-01 of the national Programme Investissements d’Avenir. Funding for this work was also provided by Laboratoire d’excellence Institute Pierre Simon Laplace (L-IPSL), a grant from the “Research in Paris” programme, and National Oceanographic and Atmospheric Administration Climate Program Office grant NA11OAR4310157. S. Fiedler acknowledges the research funding by the European Research Council grant 257543. C. Zhao acknowledges support by the U.S. DOE as part of the Regional and Global Climate Modeling program. The Pacific Northwest National Laboratory is operated for DOE by Battelle Memorial Institute under contract DE-AC05-76RL01830.

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