Publications

Lin, YJ; Tian, PF; Tang, CG; Pang, ST; Zhang, L (2022). Combining CALIPSO and AERONET Data to Classify Aerosols Globally. IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 60, 4105812.

Abstract
Angstrom exponent (AE) and aerosol optical depth (AOD) obtained from the aerosol robotic network (AERONET) and volume depolarization ratio (VDR) obtained from the cloud-aerosol Lidar with orthogonal polarization (CALIOP) from March 2018 to February 2019 were used in our study. Data used in this study are direct observation, avoiding the limitations and uncertainties from the inversion process, and providing accurate information about the aerosol properties. Both instruments were within colocation criteria of a 40-km radius and +/- 2 h were defined as coincident cases. Six aerosol types were differentiated using the threshold method based on the AE, AOD, and VDR data. Discussion of the aerosol classification yielded the following results: 1) clean marine aerosols were the most abundant and widely distributed aerosols, followed by other types of aerosol (33.2%), polluted dust aerosols (26.8%), natural dust aerosols (2.3%), biomass burning aerosols (1.8%), and clean continental aerosols (1.1%); 2) clean marine aerosols were mainly distributed in North America and Europe, and polluted dust aerosols frequently appeared on the edges or downwind of deserts; and 3) the aerosols controlled by natural conditions (e.g., natural dust aerosols) were sensitive to seasonal variations, whereas those controlled by anthropogenic activities (e.g., polluted dust aerosols) were not. This study provides a new method for the collaborative observation of aerosol types with ground-based and satellite data. It is rare to provide annual global distribution of aerosol types and their seasonal variations; these results provide a reference for understanding the global aerosol distribution status.

DOI:
10.1109/TGRS.2021.3138085

ISSN:
1558-0644