AbstractFY-4A is a geostationary meteorological satellite with four advanced payloads, which can be used to quantitatively detect the earth's atmospheric system with multi spectral and high spatial-temporal resolution. However, the applicable model limits the application of the FY-4A satellite data. In this paper, the empirical statistical model developed for the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor is extended for FY-4A Advanced Geosynchronous Radiation Imager (AGRI), and it is applied to observed data to evaluate the applicability of the model for AGRI measurements. To improve the accuracy of radiation estimation, the artificial intelligent particle swarm optimization (PSO) algorithm was used for model optimizing. Results show that the estimated radiation has diurnal variation, which accords with the characteristics of radiation variation. The estimated net surface shortwave radiation (Sn) and observed values show good correlation. However, large deviations from observations are found in the estimated values when the empirical model based on MODIS is directly used to process AGRI data. Thus, the empirical statistical model based on MODIS can be applied to AGRI data, but the empirical parameters need to be revised. Optimization of the empirical statistical model by the PSO algorithm can effectively improve the accuracy of radiation estimate. The Mean absolute percentage error (MAPE) of Sn estimated by optimized models is reduced to 15%. The MAPE of the net surface long-wave radiation (Ln) estimated by optimized models is reduced to 31%, and the MAPE of the net radiation (Rn) estimated by optimized models is reduced to 27%. However, for the uncertainty caused by error accumulation effect, the influence of PSO optimization on Rn is not as obvious as that of Ln. However, from the analysis of error distribution, it shows that PSO optimization does improve the estimation results of Rn. Based on AGRI data, the surface radiation can be estimated simply, and the regional or larger scale surface radiation retrieval can quickly realize by this method which has large application potential and popularization value.
Statistical model-based optimization for damage extent quantification
