Retrieval of hourly aerosol single scattering albedo over land using geostationary satellite data

• Published in: npj Climate and Atmospheric Science
• Main Authors: Jiang, X., Xue, Y., de Leeuw, G., Jin, C., Zhang, S., Sun, Y., Wu, S.
• Format: Article in Journal/Newspaper
• Language: unknown
• Published: Nature 2024
• Subjects: single scattering albedo (SSA); aerosol; Atmospheric chemistry; Environmental monitoring; Aerosol Robotic Network
• Online Access: https://doi.org/10.1038/s41612-024-00690-6; https://repository.derby.ac.uk/download/c80d9044b3075d036ee830f3ae841fb873b0d7e53513f7251deeff2110c193a5/1382535/s41612-024-00690-6.pdf

The single scattering albedo (SSA) of aerosol particles is one of the key variables that determine aerosol radiative forcing. Herein, an Algorithm for the retrieval of Single scattering albedo over Land (ASL) is proposed for application to full-disk data from the advanced Himawari imager (AHI) sensor flying on board the Himawari-8 satellite. In this algorithm, an atmospheric radiative transfer model known as the USM (the top of the atmosphere reflectance as the sum of Un-scattered, Single-scattered, and Multiple-scattered components) is used to calculate the SSA instead of predetermining the aerosol model; the USM is constrained by the surface bidirectional reflectance distribution function shape and aerosol optical depth (AOD) in the retrieval process. Combining two consecutive observations and a 2 * 2 pixel window, the optimal estimation algorithm is adopted to obtain the optimal solution for the aerosol SSA. These SSA results are evaluated by comparing with aerosol robotic network (AERONET) data. Linear regression shows that SSAASL = 0.60*SSSAERONET + 0.38, with a correlation coefficient (0.7284), mean absolute error (0.0319), mean bias error (0.00324), root mean square error (0.0427), and ~80.11% of the ASL SSA data within an uncertainty of ±0.05 of the AERONET data. A comparison of the ASL SSA products with collocated Himawari-8 SSA products (Version 03, officially released by the Japan Meteorological Agency (JMA), referred to herein as JMA SSA) shows that the accuracy of the ASL SSA is better than that of the JMA SSA products. For the SSA retrieval in large AODs (>0.4), the validation metrics vs. AERONET data are better.