干旱区生态环境知识资源中心(Arid): The impact of different aerosol layering conditions on the high-resolution MODIS/MAIAC AOD retrieval bias: The uncertainty analysis

Arid

DOI	10.1016/j.atmosenv.2023.119930
	The impact of different aerosol layering conditions on the high-resolution MODIS/MAIAC AOD retrieval bias: The uncertainty analysis
	Rogozovsky, Irina; Ohneiser, Kevin; Lyapustin, Alexei; Ansmann, Albert; Chudnovsky, Alexandra
通讯作者	Rogozovsky, I ; Chudnovsky, A
来源期刊	ATMOSPHERIC ENVIRONMENT
ISSN	1352-2310
EISSN	1873-2844
出版年	2023
卷号	309
英文摘要	The Eastern Mediterranean/Middle East (EMME) region belongs to one of the most polluted and vulnerable to climate change related areas in the world. To monitor these changes, comprehensive set of measurements need to be conducted. Ground-level monitoring sites provide continuous measurements, yet their spatial coverage in EMME is very limited. Satellite data largely expand spatial coverage, however, retrieval accuracy over arid regions with bright surface background, mixed with urban and industrial sources, remains challenging. In this study, we analyzed the agreement between aerosol optical depth (AOD) data from the Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm at 1-km spatial resolution and corresponding ground-based Aerosol Robotic Network (AERONET) measurements, using data from September 2019 to October 2022 in Tel Aviv, Israel. We identified all overestimation and underestimation MAIAC AOD measurements, relative to AERONET, and used multiwavelength polarization lidar observations of vertical aerosol profiles to characterize these conditions. Our findings suggest that under clear atmospheric conditions (AOD<0.12), MAIAC overestimation prevails, while under dusty (AOD>0.3), and partially cloudy conditions, MAIAC underestimation prevails. We found that dust component (high particle depolarization ratio, and low Angstrom exponent) is often presented in cases of underestimation, while a single layer overestimation cases typically related to anthropogenic pollution. The two-layers overestimation cases tend to have marine aerosols at the bottom and mixed pollution sources at the top. Our study highlights the importance of studying the different layering conditions that largely bias the MAIAC AOD retrieval accuracy. This knowledge is highly important since AOD is widely used as input variable in numerous modeling studies and air quality applications and rarely prepossessed for such a bias.
英文关键词	Aerosol optical depth (AOD) Multi-angle implementation of atmospheric correction (MAIAC) Polly-lidar Atmospheric vertical profile MAIAC AOD bias
类型	Article
语种	英语
开放获取类型	Bronze
收录类别	SCI-E
WOS记录号	WOS:001148640100001
WOS关键词	OPTICAL DEPTH ; ATMOSPHERIC CORRECTION ; TEMPORAL VARIABILITY ; PM2.5 CONCENTRATIONS ; LIDAR OBSERVATIONS ; MODIS SATELLITE ; POLLUTION ; EASTERN ; DUST ; POLARIZATION
WOS类目	Environmental Sciences ; Meteorology & Atmospheric Sciences
WOS研究方向	Environmental Sciences & Ecology ; Meteorology & Atmospheric Sciences
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/395494
推荐引用方式 GB/T 7714	Rogozovsky, Irina,Ohneiser, Kevin,Lyapustin, Alexei,et al. The impact of different aerosol layering conditions on the high-resolution MODIS/MAIAC AOD retrieval bias: The uncertainty analysis[J],2023,309.
APA	Rogozovsky, Irina,Ohneiser, Kevin,Lyapustin, Alexei,Ansmann, Albert,&Chudnovsky, Alexandra.(2023).The impact of different aerosol layering conditions on the high-resolution MODIS/MAIAC AOD retrieval bias: The uncertainty analysis.ATMOSPHERIC ENVIRONMENT,309.
MLA	Rogozovsky, Irina,et al."The impact of different aerosol layering conditions on the high-resolution MODIS/MAIAC AOD retrieval bias: The uncertainty analysis".ATMOSPHERIC ENVIRONMENT 309(2023).