Articles | Volume 22, issue 19
https://doi.org/10.5194/acp-22-13183-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-22-13183-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
14 Oct 2022
Research article |
| 14 Oct 2022
| 14 Oct 2022
Four-dimensional variational assimilation for SO2 emission and its application around the COVID-19 lockdown in the spring 2020 over China
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
Zengliang Zang
CORRESPONDING AUTHOR
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
Zhijin Li
Department of Atmospheric and Oceanic Sciences, Fudan University,
Shanghai 200031, China
Joint Institute for Regional Earth System Science and Engineering, University of California, Los Angeles, California 91109, USA
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Short summary
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...
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