Articles | Volume 25, issue 4
https://doi.org/10.5194/acp-25-2311-2025
https://doi.org/10.5194/acp-25-2311-2025
Research article
 | 
21 Feb 2025
Research article |  | 21 Feb 2025

A global dust emission dataset for estimating dust radiative forcings in climate models

Danny M. Leung, Jasper F. Kok, Longlei Li, David M. Lawrence, Natalie M. Mahowald, Simone Tilmes, and Erik Kluzek

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Cited articles

Achakulwisut, P., Shen, L., and Mickley, L. J.: What Controls Springtime Fine Dust Variability in the Western United States? Investigating the 2002–2015 Increase in Fine Dust in the U.S. Southwest, J. Geophys. Res.-Atmos., 122, 12449–12467, https://doi.org/10.1002/2017JD027208, 2017. 
Adebiyi, A. A. and Kok, J. F.: Climate models miss most of the coarse dust in the atmosphere, Sci. Adv., 6, eaaz9507, https://doi.org/10.1126/sciadv.aaz9507, 2020. 
Andreae, M. O., Jones, C. D., and Cox, P. M.: Strong present-day aerosol cooling implies a hot future, Nature, 435, 1187–1190, https://doi.org/10.1038/nature03671, 2005. 
Avila, A., Queralt-Mitjans, I., and Alarcón, M.: Mineralogical composition of African dust delivered by red rains over northeastern Spain, J. Geophys. Res.-Atmos., 102, 21977–21996, https://doi.org/10.1029/97JD00485, 1997. 
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This study derives a gridded dust emission dataset for 1841–2000 by employing a combination of observed dust from core records and reanalyzed global dust cycle constraints. We evaluate the ability of global models to replicate the observed historical dust variability by using the emission dataset to force a historical simulation in an Earth system model. We show that prescribing our emissions forces the model to better match observations than other mechanistic models.
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