Fengyun 4A Land Aerosol Retrieval: Algorithm Development, Validation, and Comparison With Other Datasets

• Published in: IEEE transactions on geoscience and remote sensing Vol. 61; pp. 1 - 16
• Main Authors: Su, Xin, Wang, Lunche, Cao, Mengdan, Yang, Leiku, Zhang, Ming, Qin, Wenmin, Cao, Qian, Yang, Yikun, Li, Lei
• Format: Journal Article
• Language: English
• Published: New York IEEE 2023; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Advanced Geostationary Radiation Imager (AGRI); aerosol optical depth (AOD); Aerosols; Algorithms; Fengyun 4; land general aerosol (LaGA) algorithm; MODIS; Reflectivity; Satellite broadcasting; Satellites; Spatial resolution; surface reflectance (SR)
• ISSN: 0196-2892; 1558-0644
• DOI: 10.1109/TGRS.2023.3330544

The Advanced Geostationary Radiation Imager (AGRI) onboard the Fengyun 4A (FY-4A) satellite has high spatiotemporal resolution and provides useful spectral information that can be used to monitor aerosols and air pollution. The objective of this study is to propose the land general aerosol (LaGA) algorithm for retrieving aerosol information using AGRI data in the Asia region. First, the sensitivity analysis indicated that the AGRI blue band is more suitable for aerosol retrieval, and its red band is sensitive under high aerosol loading. Then, a real-time surface reflectance (SR) database was established using the atmosphere-corrected technique based on the background aerosol optical depth (AOD) library and regional aerosol model parameters. By comparing the AGRI observed reflectance with that calculated using a lookup table (LUT), the AGRI AOD with a 1-h resolution was obtained. The validation results indicated that the AGRI AOD, both at all moments (data volume: 12102) and the daily mean (data volume: 1766), exhibits a good agreement with AERONET AOD (<inline-formula> <tex-math notation="LaTeX">R > </tex-math></inline-formula> 0.830). Its performance was comparable to that of the Moderate-Resolution Imaging Spectroradiometer (MODIS) dark target (DT) AOD (expected error (EE), ± (0.05 + 20%<inline-formula> <tex-math notation="LaTeX">\tau _{\mathrm {AERONET}} </tex-math></inline-formula>): AGRI = 0.673 versus DT = 0.666), and Himawari-8 (H8) AOD (EE: AGRI = 0.698 versus H8 = 0.658). The pixel-by-pixel comparison demonstrated that <inline-formula> <tex-math notation="LaTeX">R </tex-math></inline-formula> between the AGRI and MODIS AODs was >0.6, and the mean bias (MB) between them was within ±0.05 in most of the study area. These results suggest the robustness of the proposed algorithm, and it has great potential for application in the follow-up Fengyun 4 series satellites.