Simultaneous assimilation of Fengyun-4A and Himawari-8 aerosol optical depth retrieval to improve air quality simulations during one storm event over East Asia

• Published in: Frontiers in Earth Science
• Main Authors: Xia, Xiaoli, Min, Jinzhong, Sun, Shangpeng, Chen, Xu
• Format: Article in Journal/Newspaper
• Language: unknown
• Published: Frontiers Media SA 2023
• Subjects: General Earth and Planetary Sciences; Aerosol Robotic Network
• Online Access: http://dx.doi.org/10.3389/feart.2023.1057299; https://www.frontiersin.org/articles/10.3389/feart.2023.1057299/full

Aerosols are the main components of air pollutants, which are closely related to haze, dust storm and air pollution. In this study, an aerosol data assimilation system was developed using Gridpoint Statistical Interpolation (GSI) system to assimilate the Aerosol Optical Depth (AOD) observations from FY4 and Himawari-8 for the first time and applied in the heavy dust case over east Asia in March 2018. Three parallel experiments assimilated AOD from FY4, Himawari-8 and both the FY4 and Himawari-8 respectively and a control experiment which did not employ DA were performed. The hourly aerosol analyses and forecasts are compared with the assimilated FY-4 AOD, Himawari-8 AOD and independent AOD from Aerosol Robotic Network (AERONET). The results showed that all forms of DA experiments improved a low Bias and the RMSE reduced about 20%. The aerosol data assimilation with observations from both the FY-4 and Himawari-8 satellites substantially improved aerosol analyses and subsequent forecasts with more abundant aerosol observation information, especially over the northwest of China. This study indicates that the new generation geostationary meteorological satellites have potential to dramatically contribute to air quality forecasting.