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Title: Modeling East Asian Dust and Its Radiative Feedbacks in CAM4-BAM

Abstract

East Asian dust and its radiative feedbacks are analyzed by the use of the fourth version of the Community Atmosphere Model (CAM4) with a bulk aerosol model parameterization (BAM) for the dust size distribution (CAM4-BAM). Two numerical experiments are conducted and intercompared: one with (Active) and one without (Passive) the radiative effects of dust aerosols. This CAM4-BAM captures the main spatial distribution of the dust aerosol optical depth (AOD) and the dust surface concentrations over East Asia, with positive correlations with the local observational data on annual and seasonal means. A comparative analysis of the Active and Passive experiments reveals that consideration of the dust-radiation interaction can significantly reduce dust emissions, loading, transport, and dry and wet depositions over East Asia, which is opposite to the enhanced dust cycle over North Africa. Further analysis of the contrasting dust-radiation feedbacks between North Africa and East Asia shows that over North Africa, the dust radiative forcing significantly increases the surface temperature and 10-m wind speed, whereas it decreases the surface temperature and the surface wind speeds over East Asia. These contrasting radiative effects, in turn, result in distinct dust cycle changes over these two regions. Thus, mechanistic analysis reveals that the radiativemore » contrasts between East Asia and North Africa are mainly due to the differences in their regional surface albedo, dust vertical distribution and size distribution.« less

Authors:
ORCiD logo [1]; ORCiD logo [2];  [3];  [1];  [4]; ORCiD logo [5]; ORCiD logo [1]; ORCiD logo [6]
  1. Chinese Academy of Sciences (CAS), Xi'an (China). Shaanxi Key Lab. of Accelerator Mass Spectrometry Technology and Application (SKLLQG) and Inst. of Earth Environment
  2. Chinese Academy of Sciences (CAS), Xi'an (China). Shaanxi Key Lab. of Accelerator Mass Spectrometry Technology and Application (SKLLQG) and Inst. of Earth Environment; Chinese Academy of Sciences (CAS), Beijing (China). College of Earth Sciences
  3. Chinese Academy of Meteorological Sciences, (CMA), Beijing (China). Key Lab. for Atmospheric Chemistry, Inst. of Atmospheric Composition
  4. Shaanxi Radio and TV Univ., Xi'an (China). School of Tourism and Hospitality Management
  5. Chinese Academy of Sciences (CAS), Beijing (China). State Key Lab. of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics, Inst. of Atmospheric Physics
  6. Brookhaven National Lab. (BNL), Upton, NY (United States). Environmental and Climate Sciences Dept.
Publication Date:
Research Org.:
Brookhaven National Lab. (BNL), Upton, NY (United States)
Sponsoring Org.:
USDOE Office of Science (SC), Biological and Environmental Research (BER); National Key Research and Development Program of China; National Natural Science Foundation of China (NNSFC)
OSTI Identifier:
1424979
Report Number(s):
BNL-200024-2018-JAAM
Journal ID: ISSN 2169-897X
Grant/Contract Number:  
SC0012704; 2016YFA0601904; 41690115; 41572150
Resource Type:
Accepted Manuscript
Journal Name:
Journal of Geophysical Research: Atmospheres
Additional Journal Information:
Journal Volume: 123; Journal Issue: 2; Journal ID: ISSN 2169-897X
Publisher:
American Geophysical Union
Country of Publication:
United States
Language:
English
Subject:
54 ENVIRONMENTAL SCIENCES

Citation Formats

Xie, Xiaoning, Liu, Xiaodong, Che, Huizheng, Xie, Xiaoxun, Wang, Hongli, Li, Jiandong, Shi, Zhengguo, and Liu, Yangang. Modeling East Asian Dust and Its Radiative Feedbacks in CAM4-BAM. United States: N. p., 2018. Web. doi:10.1002/2017JD027343.
Xie, Xiaoning, Liu, Xiaodong, Che, Huizheng, Xie, Xiaoxun, Wang, Hongli, Li, Jiandong, Shi, Zhengguo, & Liu, Yangang. Modeling East Asian Dust and Its Radiative Feedbacks in CAM4-BAM. United States. doi:10.1002/2017JD027343.
Xie, Xiaoning, Liu, Xiaodong, Che, Huizheng, Xie, Xiaoxun, Wang, Hongli, Li, Jiandong, Shi, Zhengguo, and Liu, Yangang. Thu . "Modeling East Asian Dust and Its Radiative Feedbacks in CAM4-BAM". United States. doi:10.1002/2017JD027343. https://www.osti.gov/servlets/purl/1424979.
@article{osti_1424979,
title = {Modeling East Asian Dust and Its Radiative Feedbacks in CAM4-BAM},
author = {Xie, Xiaoning and Liu, Xiaodong and Che, Huizheng and Xie, Xiaoxun and Wang, Hongli and Li, Jiandong and Shi, Zhengguo and Liu, Yangang},
abstractNote = {East Asian dust and its radiative feedbacks are analyzed by the use of the fourth version of the Community Atmosphere Model (CAM4) with a bulk aerosol model parameterization (BAM) for the dust size distribution (CAM4-BAM). Two numerical experiments are conducted and intercompared: one with (Active) and one without (Passive) the radiative effects of dust aerosols. This CAM4-BAM captures the main spatial distribution of the dust aerosol optical depth (AOD) and the dust surface concentrations over East Asia, with positive correlations with the local observational data on annual and seasonal means. A comparative analysis of the Active and Passive experiments reveals that consideration of the dust-radiation interaction can significantly reduce dust emissions, loading, transport, and dry and wet depositions over East Asia, which is opposite to the enhanced dust cycle over North Africa. Further analysis of the contrasting dust-radiation feedbacks between North Africa and East Asia shows that over North Africa, the dust radiative forcing significantly increases the surface temperature and 10-m wind speed, whereas it decreases the surface temperature and the surface wind speeds over East Asia. These contrasting radiative effects, in turn, result in distinct dust cycle changes over these two regions. Thus, mechanistic analysis reveals that the radiative contrasts between East Asia and North Africa are mainly due to the differences in their regional surface albedo, dust vertical distribution and size distribution.},
doi = {10.1002/2017JD027343},
journal = {Journal of Geophysical Research: Atmospheres},
number = 2,
volume = 123,
place = {United States},
year = {2018},
month = {1}
}

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