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| Data assimilation experiment on SO2 initial conditions in the Pearl River Delta |
| CHEN Yi-ang1,2, DENG Xue-jiao2, ZHU Bin1, DENG Tao2, GAO Yu-dong2 |
1. Key Laboratory of Meteorological Disaster, Ministry of Education, Joint International Research Laboratory of Climate and Environment Change, Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Key Laboratory for Aerosol-Cloud-Precipitation of China Meteorological Administration, Nanjing University of Information Science & Technology, Nanjing 210044, China;
2. Guangdong Provincial Key Laboratory of Regional Numerical Weather Prediction, Institute of Tropical and Marine Meteorology, China Meteorological Administration, Guangzhou 510080, China |
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Abstract Based on the WRF-CMAQ air quality model, the pollutant SO2 in the Pearl River Delta Region in December 2013 was assimilated to optimize the initial conditions using the optimal interpolation approach (OI) and the ensemble square root filter (EnSRF). The high values of the background error were mainly located in Jiangmen region in horizontal direction and were larger within the boundary layer in vertical direction. The background error was nearly constant below 400m and decreased with height above 400m. By comparing the SO2 concentration fields using assimilation with those not using assimilation, the results showed that assimilation could adjust the distribution pattern of the pollutant and make it more consistent with the observation field. Both assimilated methods could offer an initial field closer to the true situation. The sensitivity test showed that the optimal horizontal scale of the optimal interpolation method was 20km. The root mean square error decreasing percentage between the assimilation sites and the verification sites reached 73% and 39%, respectively. With the number of the assimilation site increasing, the optimization of the assimilation site had a declining trend.
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Received: 18 September 2016
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