Four-dimensional variational assimilation for SO2 emission and its application around the COVID-19 lockdown in the spring 2020 over China
Yiwen Hu,Zengliang Zang,Xiaoyan Ma,Yi Li,Yanfei Liang,Wei You,Xiaobin Pan,and Zhijin Li
Yiwen Hu
Key Laboratory for Aerosol–Cloud–Precipitation of China Meteorological
Administration, Nanjing University of Information Science & Technology,
Nanjing 210044, China
College of Meteorology and Oceanography, National University of
Defense Technology, Changsha 410073, China
Key Laboratory for Aerosol–Cloud–Precipitation of China Meteorological
Administration, Nanjing University of Information Science & Technology,
Nanjing 210044, China
Yi Li
College of Meteorology and Oceanography, National University of
Defense Technology, Changsha 410073, China
Yanfei Liang
No. 32145 Unit of PLA, Xinxiang 453000, China
Wei You
College of Meteorology and Oceanography, National University of
Defense Technology, Changsha 410073, China
Xiaobin Pan
College of Meteorology and Oceanography, National University of
Defense Technology, Changsha 410073, China
This study developed a four-dimensional variational assimilation (4DVAR) system based on WRF–Chem to optimise SO2 emissions. The 4DVAR system was applied to obtain the SO2 emissions during the early period of the COVID-19 pandemic over China. The results showed that the 4DVAR system effectively optimised emissions to describe the actual changes in SO2 emissions related to the COVID lockdown, and it can thus be used to improve the accuracy of forecasts.
This study developed a four-dimensional variational assimilation (4DVAR) system based on...
