Uncertainty in Aqua-MODIS Aerosol Retrieval Algorithms during COVID-19 Lockdown.

Bilal, M., Qiu, Z., Nichol, J.E., Mhawish, A., Ali, M.A., Khedher, K.M., de Leeuw, G., Yu, W., Tiwari. P., Nazeer, M., and Bleiweiss, M.P.

— This letter reports uncertainties in the AquaModerate 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.

Bibliographic data

Bilal, M., Qiu, Z., Nichol, J.E., Mhawish, A., Ali, M.A., Khedher, K.M., de Leeuw, G., Yu, W., Tiwari. P., Nazeer, M., and Bleiweiss, M.P. . Uncertainty in Aqua-MODIS Aerosol Retrieval Algorithms during COVID-19 Lockdown.
Journal: IEEE Geoscience and Remote Sensing Letters, Year: 2021, doi: 10.1109/LGRS.2021.3077189