Publications

Zhang, ZY; Li, J; Dong, YM; Zhang, CZ; Ying, T; Li, QR (2024). Long-Term Trends in Aerosol Single Scattering Albedo Cause Bias in MODIS Aerosol Optical Depth Trends. IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 62, 4109209.

Abstract
Satellite observations are widely used in large-scale aerosol monitoring. In the past 20 years, aerosol compositions have changed substantially worldwide, especially over developing regions, such as East and South Asia, which leads to long-term trends in aerosol single scattering albedo (SSA). However, major satellite aerosol retrieval algorithms, such as the widely used dark-target (DT) algorithm by the moderate-resolution imaging spectroradiometer (MODIS), apply the same set of aerosol models over time with almost a constant SSA, which may have defects in capturing the actual aerosol optical depth (AOD) trend. In this work, we use MODIS-Aqua observations as an example to investigate the impact of SSA trends on the satellite-retrieved AOD trend. A series of sensitivity experiments using radiative transfer simulations with different surface conditions and aerosol loadings indicate that +/- 0.06 SSA change may lead to 30% AOD retrieval uncertainties, and increased surface albedo and aerosol loading would enhance this error. An analysis at four representative sites in the aerosol robotic network (AERONET) where significant long-term SSA trends are observed, namely Beijing, Kanpur, Barcelona, and Carpentras, shows that the operational MODIS products at all four sites suffer from distinct biases in the AOD trends. By replacing the prescribed SSAs with those observed by AERONET in the MODIS algorithm, the retrieved AOD trend biases are largely corrected. This study points out the importance of aerosol scattering and absorption properties in MODIS-like AOD retrieval algorithms. It is, therefore, urgent to establish long-term monitoring of SSA globally.

DOI:
10.1109/TGRS.2024.3424981

ISSN:
1558-0644