DOI: 10.1016/j.atmosenv.2014.06.044
Scopus记录号: 2-s2.0-84903387529
论文题名: Clear-sky aerosol optical depth over East China estimated from visibility measurements and chemical transport modeling
作者: Lin J ; , van Donkelaar A ; , Xin J ; , Che H ; , Wang Y
刊名: Atmospheric Environment
ISSN: 0168-2563
EISSN: 1573-515X
出版年: 2014
卷: 95 起始页码: 258
结束页码: 267
语种: 英语
英文关键词: Aerosol optical depth
; Chemical transport model
; China
; Daytime variation
; Seasonal variation
; Visibility
Scopus关键词: Atmospheric aerosols
; Data processing
; Radiometers
; Aerosol optical depths
; Chemical transport models
; China
; Daytime variation
; Seasonal variation
; Visibility
; black carbon
; carbon monoxide
; nitrogen oxide
; organic carbon
; sulfur dioxide
; volatile organic compound
; clear sky
; climate effect
; data set
; estimation method
; MODIS
; optical depth
; particle motion
; spatiotemporal analysis
; visibility
; aerosol
; article
; China
; cloud
; dry deposition
; optical depth
; priority journal
; remote sensing
; seasonal variation
; thermodynamics
; visibility
; wet deposition
; China
Scopus学科分类: Environmental Science: Water Science and Technology
; Earth and Planetary Sciences: Earth-Surface Processes
; Environmental Science: Environmental Chemistry
英文摘要: Horizontal visibility measured at ground meteorological stations provides an under-exploited source of information for studying the interdecadal variation of aerosols and their climatic impacts. Here we propose to use a 3-hourly visibility dataset to infer aerosol optical depth (AOD) over East China, using the nested GEOS-Chem chemical transport model to interpret the spatiotemporally varying relations between columnar and near-surface aerosols. Our analysis is focused in 2006 under cloud-free conditions. We evaluate the visibility-inferred AOD using MODIS/Terra and MODIS/Aqua AOD datasets, after validating MODIS data against three ground AOD measurement networks (AERONET, CARSNET and CSHNET). We find that the two MODIS datasets agree with ground-based AOD measurements, with negative mean biases of 0.05-0.08 and Reduced Major Axis regression slopes around unity. Visibility-inferred AOD roughly capture the general spatiotemporal patterns of the two MODIS datasets with negligible mean differences. The inferred AOD reproduce the seasonal variability (correlation exceeds 0.9) and the slight AOD growth from the late morning to early afternoon shown in the MODIS datasets, suggesting the validity of our AOD inference method. Future research will extend the visibility-based AOD inference to study the long-term variability of AOD. © 2014 The Authors.
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资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/81303
Appears in Collections: 气候变化事实与影响
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作者单位: Laboratory for Climate and Ocean-Atmosphere Studies, Department of Atmospheric and Oceanic Sciences, School of Physics, Peking University, Beijing, 100871, China; Department of Physics and Atmospheric Science, Dalhousie University, Halifax, Canada; State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, 100029, China; Key Laboratory of Atmospheric Chemistry (LAC), Institute of Atmospheric Composition, Chinese Academy of Meteorological Sciences (CAMS), CMA, Beijing, 100081, China
Recommended Citation:
Lin J,, van Donkelaar A,, Xin J,et al. Clear-sky aerosol optical depth over East China estimated from visibility measurements and chemical transport modeling[J]. Atmospheric Environment,2014-01-01,95