GSTDTAP
DOI10.5194/acp-19-13409-2019
Retrieval of aerosol components directly from satellite and ground-based measurements
Li, Lei1,2,3; Dubovik, Oleg3; Derimian, Yevgeny3; Schuster, Gregory L.4; Lapyonok, Tatyana3; Litvinov, Pavel5; Ducos, Fabrice3; Fuertes, David5; Chen, Cheng3; Li, Zhengqiang6; Lopatin, Anton5; Torres, Benjamin3; Che, Huizheng1,2
2019-11-04
发表期刊ATMOSPHERIC CHEMISTRY AND PHYSICS
ISSN1680-7316
EISSN1680-7324
出版年2019
卷号19期号:21页码:13409-13443
文章类型Article
语种英语
国家Peoples R China; France; USA
英文摘要

This study presents a novel methodology for the remote monitoring of aerosol components over large spatial and temporal domains. The concept is realized within the GRASP (Generalized Retrieval of Aerosol and Surface Properties) algorithm to directly infer aerosol components from the measured radiances. The observed aerosols are assumed to be mixtures of hydrated soluble particles embedded with black carbon, brown carbon, iron oxide, and other (non-absorbing) insoluble inclusions. The complex refractive indices of the dry components are fixed a priori (although the refractive index of the soluble host is allowed to vary with hydration), and the complex refractive indices of the mixture are computed using mixing rules. The volume fractions of these components are derived along with the size distribution and the fraction of spherical particles, as well as the spectral surface reflectance in cases when the satellite data are inverted. The retrieval is implemented as a statistically optimized fit in a continuous space of solutions. This contrasts with most conventional approaches in which the type of aerosol is either associated with a preassumed aerosol model that is included in a set of lookup tables, or determined from the analysis of the retrieved aerosol optical parameters (e.g., single scattering albedo, refractive index, among others, provided by the AERONET retrieval algorithm); here, we retrieve the aerosol components explicitly. The approach also bridges directly to the quantities used in global chemical transport models. We first tested the approach with synthetic data to estimate the uncertainty, and then applied it to real ground-based AERONET and spaceborne POLDER/PARASOL observations; thus, the study presents a first attempt to derive aerosol components from satellite observations specifically tied to global chemical transport model quantities. Our results indicate aerosol optical characteristics that are highly consistent with standard products (e.g., R of similar to 0.9 for aerosol optical thickness) and demonstrate an ability to separate intrinsic optical properties of fine- and coarse-sized aerosols. We applied our method to POLDER/PARASOL radiances on the global scale and obtained spatial and temporal patterns of the aerosol components that agree well with existing knowledge on aerosol sources and transport features. Finally, we discuss limitations and perspectives of this new technique.


领域地球科学
收录类别SCI-E
WOS记录号WOS:000495380900001
WOS关键词COMPLEX REFRACTIVE-INDEX ; OPTICAL-PROPERTIES ; DESERT DUST ; LIGHT-ABSORPTION ; ORGANIC-CARBON ; MINERAL DUST ; SOUTHERN AFRICA ; BLACK CARBON ; RADIATIVE PROPERTIES ; INVERSION ALGORITHM
WOS类目Environmental Sciences ; Meteorology & Atmospheric Sciences
WOS研究方向Environmental Sciences & Ecology ; Meteorology & Atmospheric Sciences
引用统计
被引频次:110[WOS]   [WOS记录]     [WOS相关记录]
文献类型期刊论文
条目标识符http://119.78.100.173/C666/handle/2XK7JSWQ/224037
专题环境与发展全球科技态势
作者单位1.Chinese Acad Meteorol Sci, CMA, State Key Lab Severe Weather LASW, Beijing 100081, Peoples R China;
2.Chinese Acad Meteorol Sci, CMA, Key Lab Atmospher Chem LAC, Beijing 100081, Peoples R China;
3.Univ Lille, CNRS, UMR 8518, LOA, F-59000 Lille, France;
4.NASA, Langley Res Ctr, Hampton, VA 23681 USA;
5.Univ Lille, Remote Sensing Developments, GRAS PSAS, Cite Sci, F-59655 Villeneuve Dascq, France;
6.Chinese Acad Sci, Inst Remote Sensing & Digital Earth, State Environm Protect Key Lab Satellite Remote S, Beijing 100101, Peoples R China
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GB/T 7714
Li, Lei,Dubovik, Oleg,Derimian, Yevgeny,et al. Retrieval of aerosol components directly from satellite and ground-based measurements[J]. ATMOSPHERIC CHEMISTRY AND PHYSICS,2019,19(21):13409-13443.
APA Li, Lei.,Dubovik, Oleg.,Derimian, Yevgeny.,Schuster, Gregory L..,Lapyonok, Tatyana.,...&Che, Huizheng.(2019).Retrieval of aerosol components directly from satellite and ground-based measurements.ATMOSPHERIC CHEMISTRY AND PHYSICS,19(21),13409-13443.
MLA Li, Lei,et al."Retrieval of aerosol components directly from satellite and ground-based measurements".ATMOSPHERIC CHEMISTRY AND PHYSICS 19.21(2019):13409-13443.
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