Remote sensing retrieval and seasonal variation analysis of particulate matter concentration based on FY-4A/AGRI
DONG Yan1,2, XU Dan1,2, BAO Yan-song1,2, XU Meng-jie1,2, GU Ying-jie1,2
1. Key Laboratory of Aerosol and Cloud Precipitation, China Meteorological Administration, Joint Laboratory of Meteorological Environment Satellite Engineering and Application, Collaborative Innovation Center for Meteorological Disaster Forecast and Early Warning and Evaluation, Nanjing University of Information Science and Technology, Nanjing 210044, China; 2. School of Atmospheric Physics, Nanjing University of Information Science and Technology, Nanjing 210044, China
Abstract：By using the 6S Radiation Transfer Model, the correlation between AOD and visibility was analysed, with the AOD/aerosol-scale-height/visibility model established. Then the physical model of AOD and near-surface PM2.5 concentration was constructed, with a vertical correction of AOD in atmospheric column. To improve the inversion accuracy, the ground relative humidity data was adopted for analysis. The results show that the retrieved PM2.5 concentration based on FY-4A was in consist with the ground-based data of Air Quality Monitoring Network, with a high calculation efficiency. Compared with the surface observation network, the correlation coefficient of AGRI was no less than that of MODIS and VIIRS, and the root mean square error and relative error of AGRI were smaller. For seasonal analysis, the AGRI retrieval result of winter had higher accuracy, because the fine particulate matter of the lower layer was the principal of the atmospheric column aerosol in winter. And the correlation coefficient of summer was relatively lower than that of the other three seasons. In general, the retrieval accuracy of PM2.5 using FY-4A/AGRI data was reliable, with led to the all-weather and real-time monitoring of regional aerosols.
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