Examination of Long-Term Fengyun-4 AGRI Reflective Solar Bands Calibration Using Cloud Targets

Chengjie Sun, Chao Liu, Feng Lu, Fukun Wang, Ran Xu, Zhiwei Wang, Shihao Tang, Byung-Ju Sohn

Abstract: Fengyun-4 (FY-4) is a series of Chinese operational geostationary meteorological satellites, providing crucial data for weather forecasting, climate prediction, and environmental monitoring. Advanced geostationary radiation imagers (AGRIs) onboard the FY-4A and FY-4B satellites play a key role in observing the Earth’s surface, oceans, and atmosphere. However, their calibration stability is still uncertain, which clearly limits corresponding downstream applications. This study evaluates the long-term radiometric stability of AGRI reflective solar bands (RSBs) using a general cloud target (CT) calibration method, covering the periods from March 2018 to December 2024 for FY-4A/AGRI and from June 2022 to December 2024 for FY-4B/AGRI. By utilizing MODIS cloud products as references for cloud properties, we simulate the top-of-atmosphere (TOA) reflectances of CTs through the Discrete Ordinates Radiative Transfer (DISORT) model and compare results with observed reflectances to infer the instrumental calibration stability. Our results indicate that the radiometric responses of AGRI exhibit significant degradation in visible (VIS) bands, while showing relatively smaller degradation rates in near- and shortwave-infrared bands. Specifically, the annual degradation rates for band 1 ( $0.47~\mu $ m) of FY-4A/AGRI and FY-4B/AGRI are 4.3% and 8.8%, respectively. Both AGRIs demonstrate comparable degradation rates of approximately 3.5% for band 2 ( $0.65~\mu $ m). In contrast, bands 3 ( $0.83~\mu $ m), 5 ( $1.61~\mu $ m), and 6 ( $2.25~\mu $ m) show annual degradation rates around −1.0%, despite they exhibit notable fluctuations. The operational calibration of FY-4B/AGRI is more accurate than that of FY-4A/AGRI and with smaller fluctuations. By fitting the time series of relative errors (REs) between simulated and current calibrated reflectances, we calculate daily recalibration coefficients and effectively recalibrate the long-term data, with a calibration accuracy within ±3%. This study demonstrates that the CT-based calibration method can successfully track the radiometric stability of AGRI and provide a robust calibration solution to ensure data stability and accuracy.

External IDs:dblp:journals/tgrs/SunLLWXWTS25