Articles | Volume 20, issue 22
https://doi.org/10.5194/acp-20-13835-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-20-13835-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
17 Nov 2020
Research article |
| 17 Nov 2020
| 17 Nov 2020
Understanding processes that control dust spatial distributions with global climate models and satellite observations
Mingxuan Wu
Department of Atmospheric Science, University of Wyoming, Laramie, WY, USA
Atmospheric Sciences and Global Change Division, Pacific Northwest
National Laboratory, Richland, WA, USA
Xiaohong Liu
CORRESPONDING AUTHOR
Department of Atmospheric Science, University of Wyoming, Laramie, WY, USA
Department of Atmospheric Sciences, Texas A&M University, College Station, TX, USA
Hongbin Yu
NASA Goddard Space Flight Center, Greenbelt, MD, USA
Hailong Wang
Atmospheric Sciences and Global Change Division, Pacific Northwest
National Laboratory, Richland, WA, USA
Department of Atmospheric Science, University of Wyoming, Laramie, WY, USA
Department of Atmospheric Sciences, Texas A&M University, College Station, TX, USA
Kang Yang
Department of Atmospheric and Oceanic Sciences, University of Colorado Boulder, Boulder, CO, USA
Anton Darmenov
NASA Goddard Space Flight Center, Greenbelt, MD, USA
Chenglai Wu
Department of Atmospheric Science, University of Wyoming, Laramie, WY, USA
Zhien Wang
Department of Atmospheric and Oceanic Sciences, University of Colorado Boulder, Boulder, CO, USA
Department of Atmospheric Science, University of Wyoming, Laramie, WY, USA
Environmental Science Division, Argonne National Laboratory, Argonne, IL, USA
Ziming Ke
Department of Atmospheric Science, University of Wyoming, Laramie, WY, USA
Department of Atmospheric Sciences, Texas A&M University, College Station, TX, USA
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Latest update: 19 Apr 2024
Short summary
The spatiotemporal distributions of dust aerosol simulated by global climate models (GCMs) are highly uncertain. In this study, we evaluate dust extinction profiles, optical depth, and surface concentrations simulated in three GCMs and one reanalysis against multiple satellite retrievals and surface observations to gain process-level understanding. Our results highlight the importance of correctly representing dust emission, dry/wet deposition, and size distribution in GCMs.
The spatiotemporal distributions of dust aerosol simulated by global climate models (GCMs) are...
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