Preliminary Retrieval and Validation of Aerosol Optical Depths from FY-4B Advanced Geostationary Radiation Imager Images

Author:

Zhou Dong1ORCID,Wang Qingxin2,Li Siwei134,Yang Jie14

Affiliation:

1. Hubei Key Laboratory of Quantitative Remote Sensing of Land and Atmosphere, School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079, China

2. College of Geography and Environmental Sciences, Zhejiang Normal University, Jinhua 321004, China

3. State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China

4. Hubei Luojia Laboratory, Wuhan University, Wuhan 430079, China

Abstract

Fengyun-4B (FY-4B) is the latest Chinese next-generation geostationary meteorological satellite. The Advanced Geostationary Radiation Imager (AGRI) aboard FY-4B is equipped with 15 spectral bands, from visible to infrared, suitable for aerosol optical depth (AOD) retrieval. In this study, an overland AOD retrieval algorithm was developed for the FY-4B AGRI. Considering the large directional variation in the FY-4B AGRI reflectances, a bidirectional reflectance distribution function (BRDF) database was built, through which to estimate land surface reflectance/albedo. Seasonal aerosol models, based on four geographical regions in China, were developed between 2016 and 2022 using AERONET aerosol products, to improve their applicability to regional distribution differences and seasonal variations in aerosol types. AGRI AODs were retrieved using this new method over China from September 2022 to August 2023 and validated against ground-based measurements. The AGRI, Advanced Himawari Imager (AHI), and Moderate-Resolution Imaging Spectroradiometer (MODIS) official land aerosol products were also evaluated for comparison purposes. The results showed that the AGRI AOD retrievals were highly consistent with the AERONET AOD measurements, with a correlation coefficient (R) of 0.88, root mean square error (RMSE) of 0.14, and proportion that met an expected error (EE) of 65.04%. Intercomparisons between the AGRI AOD and other operational AOD products showed that the AGRI AOD retrievals achieved better performance results than the AGRI, AHI, and MODIS official AOD products. Moreover, the AGRI AOD retrievals showed high spatial integrity and stable performance at different times and regions, as well as under different aerosol loadings and characteristics. These results demonstrate the robustness of the new aerosol retrieval method and the potential of FY-4B AGRI measurements for the monitoring of aerosols with high accuracy and temporal resolutions.

Funder

National Natural Science Foundation of China

Open Research Program of the International Research Center of Big Data for Sustainable Development Goals

China Postdoctoral Science Foundation

Wuhan University Specific Fund for Major School-level Internationalization Initiatives

Publisher

MDPI AG

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