학술논문

Uncertainty in Aqua-MODIS Aerosol Retrieval Algorithms During COVID-19 Lockdown
Document Type
Periodical
Source
IEEE Geoscience and Remote Sensing Letters IEEE Geosci. Remote Sensing Lett. Geoscience and Remote Sensing Letters, IEEE. 19:1-5 2022
Subject
Geoscience
Power, Energy and Industry Applications
Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Computing and Processing
Signal Processing and Analysis
Aerosols
COVID-19
Uncertainty
MODIS
Loading
Adaptive optics
Atmospheric measurements
Aerosol optical depth (AOD)
AErosol RObotic NETwork (AERONET)
dark target (DT)
deep blue (DB)
lockdown
multiangle implementation of atmospheric correction (MAIAC)
Language
ISSN
1545-598X
1558-0571
Abstract
This letter reports uncertainties in the Aqua-Moderate Resolution Imaging Spectroradiometer (MODIS) Level 2 dark target (DT), deep blue (DB), and multiangle implementation of atmospheric correction (MAIAC) aerosol optical depth (AOD) during the COVID-19 lockdown period (February–May 2020) compared to the pre-COVID-19 period (February–May 2019). Validation of AOD retrievals was conducted against AErosol RObotic NETwork (AERONET) Version 3 Level 1.5 AOD data obtained from three sites located in urban (Beijing_CAMS and Beijing_RADI) and suburban (XiangHe) areas of China. The results show the poor performance of the DT and DB algorithms compared to the MAIAC algorithm, which performed better during the lockdown period. Overall, all MODIS algorithms overestimated the AOD and showed higher positive bias under high aerosol loading conditions during lockdown than during prelockdown. This is mainly attributed to the overestimation of the aerosol single-scattering albedo (SSA), which was found higher during lockdown than during the same period in 2019.