Articles | Volume 26, issue 9
https://doi.org/10.5194/acp-26-6321-2026
https://doi.org/10.5194/acp-26-6321-2026
Research article
 | 
12 May 2026
Research article |  | 12 May 2026

Vegetation drag partition effects redistribute dust globally

Siqing Xu, Yves Balkanski, Philippe Ciais, and Jean Sciare

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Cited articles

Achakulwisut, P., Anenberg, S. C., Neumann, J. E., Penn, S. L., Weiss, N., Crimmins, A., Fann, N., Martinich, J., Roman, H., and Mickley, L. J.: Effects of increasing aridity on ambient dust and public health in the US Southwest under climate change, GeoHealth, 3, 127–144, https://doi.org/10.1029/2019GH000187, 2019. 
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. 
Adebiyi, A. A., Kok, J. F., Wang, Y., Ito, A., Ridley, D. A., Nabat, P., and Zhao, C.: Dust Constraints from joint Observational-Modelling-experiMental analysis (DustCOMM): comparison with measurements and model simulations, Atmos. Chem. Phys., 20, 829–863, https://doi.org/10.5194/acp-20-829-2020, 2020. 
AERONET: Aerosol Robotic Network, AERONET [data set], https://aeronet.gsfc.nasa.gov/ (last access: 20 February 2026), 2025. 
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Short summary
Uncertainty in dust emission estimates stems from simplified surface parameterizations. We incorporate dynamic vegetation cover into the dust emission scheme of an Earth System Model. Including vegetation reduces global dust emissions by 23 % and redistributes regional contributions by suppressing emissions in grass-covered dryland, improving agreement with observations of the global dust cycle. This work establishes a framework for advancing the representation of land–atmosphere feedbacks.
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