Articles | Volume 24, issue 4
https://doi.org/10.5194/acp-24-2287-2024
https://doi.org/10.5194/acp-24-2287-2024
Research article
 | 
22 Feb 2024
Research article |  | 22 Feb 2024

A new process-based and scale-aware desert dust emission scheme for global climate models – Part II: Evaluation in the Community Earth System Model version 2 (CESM2)

Danny M. Leung, Jasper F. Kok, Longlei Li, Natalie M. Mahowald, David M. Lawrence, Simone Tilmes, Erik Kluzek, Martina Klose, and Carlos Pérez García-Pando

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A global dust emission dataset for estimating dust radiative forcings in climate models
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Importance of different parameterization changes for the updated dust cycle modeling in the Community Atmosphere Model (version 6.1)
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Subject: Aerosols | Research Activity: Atmospheric Modelling and Data Analysis | Altitude Range: Troposphere | Science Focus: Physics (physical properties and processes)
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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 U.S. 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, [data set], https://aeronet.gsfc.nasa.gov/ (last access: 4 March 2022), 2022. 
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Short summary
This study uses a premier Earth system model to evaluate a new desert dust emission scheme proposed in our companion paper. We show that our scheme accounts for more dust emission physics, hence matching better against observations than other existing dust emission schemes do. Our scheme's dust emissions also couple tightly with meteorology, hence likely improving the modeled dust sensitivity to climate change. We believe this work is vital for improving dust representation in climate models.
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