Fengyun 4A Land Aerosol Retrieval: Algorithm Development, Validation, and Comparison With Other Datasets
Xin Su, Lunche Wang, Mengdan Cao, Leiku Yang, Ming Zhang, Wenmin Qin, Qian Cao, Yikun Yang, Lei Li
Abstract
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 AOD library and regional aerosol model parameters. By comparing the AGRI observed reflectance with that calculated using a lookup table, the AGRI aerosol optical depth (AOD) with a 1-h resolution was obtained. The validation results indicated that the AGRI AOD, both at all moments (data volume: 12,102) and the daily mean (data volume: 1,766), exhibit a good agreement with AERONET AOD (R > 0.830). Its performance was comparable to that of the MOdIs dark target (DT) AOD (expected error (EE), ± (0.05 + 20%τ <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">AERONET</sub> ): AGRI = 0.673 vs. DT = 0.666) and Himawari-8 (H8) AOD (EE: AGRI = 0.698 vs. H8 = 0.658). The pixel-by-pixel comparison demonstrated that the R between the AGRI and MODIS AODs was >0.6, and the mean bias 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.