Understanding processes that control dust spatial distributions with global climate models and satellite observations
Dust aerosol is important in modulating the climate system at local and global scales, yet its spatiotemporal distributions simulated by global climate models (GCMs) are highly uncertain. In this study, we evaluate the spatiotemporal variations of dust extinction profiles and dust optical depth (DOD...
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ftosti:oai:osti.gov:1725865 2023-07-30T04:07:03+02:00 Understanding processes that control dust spatial distributions with global climate models and satellite observations Wu, Mingxuan Liu, Xiaohong Yu, Hongbin Wang, Hailong Shi, Yang Yang, Kang Darmenov, Anton Wu, Chenglai Wang, Zhien Luo, Tao Feng, Yan Ke, Ziming 2023-07-03 application/pdf http://www.osti.gov/servlets/purl/1725865 https://www.osti.gov/biblio/1725865 https://doi.org/10.5194/acp-20-13835-2020 unknown http://www.osti.gov/servlets/purl/1725865 https://www.osti.gov/biblio/1725865 https://doi.org/10.5194/acp-20-13835-2020 doi:10.5194/acp-20-13835-2020 54 ENVIRONMENTAL SCIENCES 2023 ftosti https://doi.org/10.5194/acp-20-13835-2020 2023-07-11T09:55:49Z Dust aerosol is important in modulating the climate system at local and global scales, yet its spatiotemporal distributions simulated by global climate models (GCMs) are highly uncertain. In this study, we evaluate the spatiotemporal variations of dust extinction profiles and dust optical depth (DOD) simulated by the Community Earth System Model version 1 (CESM1) and version 2 (CESM2), the Energy Exascale Earth System Model version 1 (E3SMv1), and the Modern-Era Retrospective analysis for Research and Applications version 2 (MERRA-2) against satellite retrievals from Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP), Moderate Resolution Imaging Spectroradiometer (MODIS), and Multi-angle Imaging SpectroRadiometer (MISR). We find that CESM1, CESM2, and E3SMv1 underestimate dust transport to remote regions. E3SMv1 performs better than CESM1 and CESM2 in simulating dust transport and the northern hemispheric DOD due to its higher mass fraction of fine dust. CESM2 performs the worst in the Northern Hemisphere due to its lower dust emission than in the other two models but has a better dust simulation over the Southern Ocean due to the overestimation of dust emission in the Southern Hemisphere. DOD from MERRA-2 agrees well with CALIOP DOD in remote regions due to its higher mass fraction of fine dust and the assimilation of aerosol optical depth. The large disagreements in the dust extinction profiles and DOD among CALIOP, MODIS, and MISR retrievals make the model evaluation of dust spatial distributions challenging. Our study indicates the importance of representing dust emission, dry/wet deposition, and size distribution in GCMs in correctly simulating dust spatiotemporal distributions. Other/Unknown Material Southern Ocean SciTec Connect (Office of Scientific and Technical Information - OSTI, U.S. Department of Energy) Southern Ocean Merra ENVELOPE(12.615,12.615,65.816,65.816) Atmospheric Chemistry and Physics 20 22 13835 13855 |
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Open Polar |
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SciTec Connect (Office of Scientific and Technical Information - OSTI, U.S. Department of Energy) |
op_collection_id |
ftosti |
language |
unknown |
topic |
54 ENVIRONMENTAL SCIENCES |
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54 ENVIRONMENTAL SCIENCES Wu, Mingxuan Liu, Xiaohong Yu, Hongbin Wang, Hailong Shi, Yang Yang, Kang Darmenov, Anton Wu, Chenglai Wang, Zhien Luo, Tao Feng, Yan Ke, Ziming Understanding processes that control dust spatial distributions with global climate models and satellite observations |
topic_facet |
54 ENVIRONMENTAL SCIENCES |
description |
Dust aerosol is important in modulating the climate system at local and global scales, yet its spatiotemporal distributions simulated by global climate models (GCMs) are highly uncertain. In this study, we evaluate the spatiotemporal variations of dust extinction profiles and dust optical depth (DOD) simulated by the Community Earth System Model version 1 (CESM1) and version 2 (CESM2), the Energy Exascale Earth System Model version 1 (E3SMv1), and the Modern-Era Retrospective analysis for Research and Applications version 2 (MERRA-2) against satellite retrievals from Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP), Moderate Resolution Imaging Spectroradiometer (MODIS), and Multi-angle Imaging SpectroRadiometer (MISR). We find that CESM1, CESM2, and E3SMv1 underestimate dust transport to remote regions. E3SMv1 performs better than CESM1 and CESM2 in simulating dust transport and the northern hemispheric DOD due to its higher mass fraction of fine dust. CESM2 performs the worst in the Northern Hemisphere due to its lower dust emission than in the other two models but has a better dust simulation over the Southern Ocean due to the overestimation of dust emission in the Southern Hemisphere. DOD from MERRA-2 agrees well with CALIOP DOD in remote regions due to its higher mass fraction of fine dust and the assimilation of aerosol optical depth. The large disagreements in the dust extinction profiles and DOD among CALIOP, MODIS, and MISR retrievals make the model evaluation of dust spatial distributions challenging. Our study indicates the importance of representing dust emission, dry/wet deposition, and size distribution in GCMs in correctly simulating dust spatiotemporal distributions. |
author |
Wu, Mingxuan Liu, Xiaohong Yu, Hongbin Wang, Hailong Shi, Yang Yang, Kang Darmenov, Anton Wu, Chenglai Wang, Zhien Luo, Tao Feng, Yan Ke, Ziming |
author_facet |
Wu, Mingxuan Liu, Xiaohong Yu, Hongbin Wang, Hailong Shi, Yang Yang, Kang Darmenov, Anton Wu, Chenglai Wang, Zhien Luo, Tao Feng, Yan Ke, Ziming |
author_sort |
Wu, Mingxuan |
title |
Understanding processes that control dust spatial distributions with global climate models and satellite observations |
title_short |
Understanding processes that control dust spatial distributions with global climate models and satellite observations |
title_full |
Understanding processes that control dust spatial distributions with global climate models and satellite observations |
title_fullStr |
Understanding processes that control dust spatial distributions with global climate models and satellite observations |
title_full_unstemmed |
Understanding processes that control dust spatial distributions with global climate models and satellite observations |
title_sort |
understanding processes that control dust spatial distributions with global climate models and satellite observations |
publishDate |
2023 |
url |
http://www.osti.gov/servlets/purl/1725865 https://www.osti.gov/biblio/1725865 https://doi.org/10.5194/acp-20-13835-2020 |
long_lat |
ENVELOPE(12.615,12.615,65.816,65.816) |
geographic |
Southern Ocean Merra |
geographic_facet |
Southern Ocean Merra |
genre |
Southern Ocean |
genre_facet |
Southern Ocean |
op_relation |
http://www.osti.gov/servlets/purl/1725865 https://www.osti.gov/biblio/1725865 https://doi.org/10.5194/acp-20-13835-2020 doi:10.5194/acp-20-13835-2020 |
op_doi |
https://doi.org/10.5194/acp-20-13835-2020 |
container_title |
Atmospheric Chemistry and Physics |
container_volume |
20 |
container_issue |
22 |
container_start_page |
13835 |
op_container_end_page |
13855 |
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