Global S&T Development Trend Analysis Platform of Resources and Environment
DOI | 10.1029/2018JD029009 |
Toward Improving Short-Term Predictions of Fine Particulate Matter Over the United States Via Assimilation of Satellite Aerosol Optical Depth Retrievals | |
Kumar, Rajesh1; Delle Monache, Luca1; Bresch, Jamie1; Saide, Pablo E.2; Tang, Youhua3; Liu, Zhiquan1; da Silva, Arlindo M.4; Alessandrini, Stefano1; Pfister, Gabriele1; Edwards, David1; Lee, Pius3; Djalalova, Irina5 | |
2019-03-16 | |
发表期刊 | JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES
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ISSN | 2169-897X |
EISSN | 2169-8996 |
出版年 | 2019 |
卷号 | 124期号:5页码:2753-2773 |
文章类型 | Article |
语种 | 英语 |
国家 | USA |
英文摘要 | This study develops a new approach to improve simulations of the particulate matter of aerodynamic diameter smaller than 2.5 mu m (PM2.5) in the Community Multiscale Air Quality (CMAQ) model via assimilation of Moderate Resolution Imaging Spectroradiometer (MODIS) aerosol optical depth (AOD) retrievals using the Gridpoint Statistical Interpolation (GSI) system. In contrast to previous studies that only consider errors due to transport, our computation of the background error covariance matrix incorporates uncertainties in anthropogenic emissions. To understand the impact of this approach, three experiments (one background and two assimilations) are performed over the contiguous United States (CONUS) from 15 July to 14 August 2014. The background CMAQ experiment significantly underestimates both the MODIS AOD and surface PM2.5 levels. MODIS AOD assimilation pushes both the CMAQ AOD and surface PM2.5 distributions toward the observed distributions, but CMAQ still underestimates the observations. Averaged over CONUS, the two assimilation experiments with and without including the anthropogenic emission uncertainties improve the correlation coefficient between the model and independent observations of PM2.5 by similar to 67% and similar to 48%, respectively, and reduces the mean bias by similar to 38% and similar to 10%, respectively. The assimilation improves the model performance everywhere over CONUS, except the New York and Wisconsin, where CMAQ overestimates the observed PM2.5 during nighttime after assimilation likely because of overcorrection of aerosol mass concentrations by the AOD assimilation. Future work should incorporate uncertainties in other processes (biomass burning and biogenic emissions, deposition, chemistry, transport, and boundary conditions) to further enhance the value of assimilating spaceborne AOD retrievals. |
英文关键词 | air quality PM2.5 CMAQ GSI MODIS AOD |
领域 | 气候变化 |
收录类别 | SCI-E |
WOS记录号 | WOS:000462139800022 |
WOS关键词 | GOVERNING EQUATIONS ; BOUNDARY-LAYER ; MODEL ; CMAQ ; VERSION ; IMPLEMENTATION ; CHEMISTRY ; PARTICLE ; IMPACT |
WOS类目 | Meteorology & Atmospheric Sciences |
WOS研究方向 | Meteorology & Atmospheric Sciences |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://119.78.100.173/C666/handle/2XK7JSWQ/181686 |
专题 | 气候变化 |
作者单位 | 1.Natl Ctr Atmospher Res, POB 3000, Boulder, CO 80307 USA; 2.Univ Calif Los Angeles, Inst Environm & Sustainabil, Dept Atmospher & Ocean Sci, Los Angeles, CA USA; 3.NOAA, College Pk, MD USA; 4.NASA, Goddard Space Flight Ctr, Greenbelt, MD USA; 5.NOAA, Phys Sci Div, Cooperat Inst Res Sci, Earth Syst Lab, Boulder, CO USA |
推荐引用方式 GB/T 7714 | Kumar, Rajesh,Delle Monache, Luca,Bresch, Jamie,et al. Toward Improving Short-Term Predictions of Fine Particulate Matter Over the United States Via Assimilation of Satellite Aerosol Optical Depth Retrievals[J]. JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES,2019,124(5):2753-2773. |
APA | Kumar, Rajesh.,Delle Monache, Luca.,Bresch, Jamie.,Saide, Pablo E..,Tang, Youhua.,...&Djalalova, Irina.(2019).Toward Improving Short-Term Predictions of Fine Particulate Matter Over the United States Via Assimilation of Satellite Aerosol Optical Depth Retrievals.JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES,124(5),2753-2773. |
MLA | Kumar, Rajesh,et al."Toward Improving Short-Term Predictions of Fine Particulate Matter Over the United States Via Assimilation of Satellite Aerosol Optical Depth Retrievals".JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES 124.5(2019):2753-2773. |
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