气候变化领域集成服务门户(CCPortal): Impact of aerosol layering; complex aerosol mixing; and cloud coverage on high-resolution MAIAC aerosol optical depth measurements: Fusion of lidar; AERONET; satellite; and ground-based measurements

CCPortal

DOI	10.1016/j.atmosenv.2020.118163
	Impact of aerosol layering; complex aerosol mixing; and cloud coverage on high-resolution MAIAC aerosol optical depth measurements: Fusion of lidar; AERONET; satellite; and ground-based measurements
	Rogozovsky I.; Ansmann A.; Althausen D.; Heese B.; Engelmann R.; Hofer J.; Baars H.; Schechner Y.; Lyapustin A.; Chudnovsky A.
发表日期	2021
ISSN	1352-2310
卷号	247
英文摘要	Knowledge of the vertical distribution and layering of aerosols and identification of the corresponding aerosol sources are needed to improve our understanding of the spatial and temporal variability of aerosol pollution. To achieve this goal, we combined both passive and active remote-sensing techniques to provide a 3D view of local aerosol levels and regional to long-range pollution transport. We studied aerosol optical depth (AOD) data from the Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm at 1-km spatial resolution along with active multiwavelength polarization lidar observations of vertical aerosol profiles in Haifa, Israel, Aerosol Robotic Network (AERONET) sun photometer observations at the lidar site, and local-network observations of aerosol concentrations (PM2.5). This comprehensive dataset enabled analyzing the performance of the MAIAC AOD retrieval in cases of complex aerosol layering and mixing states which are typical of the Eastern Mediterranean. While satellite-derived and ground-based AOD measurements generally showed good agreement, 35 out of 100 measurements showed low correspondence. Analysis of those cases revealed that overestimation of AOD was mostly related to cloud-contaminated pixels and aerosol water-uptake effects in moist, cloud-free air at cloud level. Furthermore, AOD over- and underestimations were related to the presence of complex aerosol mixture and layering conditions, especially when dust was mixed with aged anthropogenic aerosol pollution and marine aerosols with lofted anthropogenic pollution. In these cases 50–70% of measurements were outside of the expected error limit. Perhaps these conditions are not considered in the MAIAC retrieval. Finally, we investigated the link between AOD spatial variability and the MAIAC AOD bias, and performed a cluster analysis corroborating the strong impact of cloud contamination on MAIAC AOD quality. Our observation-based results raise the importance of carefully analyzing the uncertainties in satellite AOD measurements that are used as an important input variable in numerous health-related exposure studies and climate models. © 2020 Elsevier Ltd
英文关键词	Aerosols; Climate models; Cluster analysis; Complex networks; Marine pollution; Mixing; Optical properties; Optical radar; Quality control; Remote sensing; Satellites; Uncertainty analysis; Aerosol optical depths; Aerosol robotic networks; Anthropogenic pollution; Ground based measurement; Multi-angle implementation of atmospheric corrections; Remote sensing techniques; Spatial and temporal variability; Vertical distributions; Air pollution; aerosol composition; algorithm; anthropogenic source; cluster analysis; lidar; optical depth; photometer; polarization; spatial resolution; three-dimensional modeling; Haifa [Israel]; Israel
语种	英语
来源期刊	Atmospheric Environment
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/169011
作者单位	Porter School of Earth Sciences and Environment, Faculty of Exact Sciences, Department of Geography and Human Environment, Tel Aviv University, Israel; Leibniz Institute for Tropospheric Research, Leipzig, Germany; Viterbi Faculty of Electrical Engineering, Technion – Israel Institute of Technology, Haifa, Israel; NASA Goddard Space Flight Center, Greenbelt, MD 20771, United States
推荐引用方式 GB/T 7714	Rogozovsky I.,Ansmann A.,Althausen D.,et al. Impact of aerosol layering; complex aerosol mixing; and cloud coverage on high-resolution MAIAC aerosol optical depth measurements: Fusion of lidar; AERONET; satellite; and ground-based measurements[J],2021,247.
APA	Rogozovsky I..,Ansmann A..,Althausen D..,Heese B..,Engelmann R..,...&Chudnovsky A..(2021).Impact of aerosol layering; complex aerosol mixing; and cloud coverage on high-resolution MAIAC aerosol optical depth measurements: Fusion of lidar; AERONET; satellite; and ground-based measurements.Atmospheric Environment,247.
MLA	Rogozovsky I.,et al."Impact of aerosol layering; complex aerosol mixing; and cloud coverage on high-resolution MAIAC aerosol optical depth measurements: Fusion of lidar; AERONET; satellite; and ground-based measurements".Atmospheric Environment 247(2021).