Modeling study of a severe aerosol pollution event in December 2013 over Shanghai China： An application of chemical data assimilation

• Published in: Particuology 2015-06, Vol.20 (3), p.41-51
• Main Authors: Wu, Jian-Bin, Xu, Jianming, Pagowski, Mariusz, Geng, Fuhai, Gu, Songqiang, Zhou, Guangqiang, Xie, Ying, Yu, Zhongqi
• Format: Article
• Language: English
• Subjects: Aerosol pollution; Data assimilation; Forecasting; Initial condition; PM2.5; 上海; 中国; 化学模型; 应用; 气溶胶; 污染事件; 空气质量预测; 资料同化
• ISSN: 1674-2001; 2210-4291
• DOI: 10.1016/j.partic.2014.10.008

This study focuses on the importance of initial conditions to air-quality predictions. We ran assimilation experiments using the WRF-Chem model and grid-point statistical interpolation （GSI）, for a 9-day severe particulate matter pollution event that occurred in Shanghai in December 2013. In this application, GSI used a three-dimensional variational approach to assimilate ground-based PM2.s observations into the chemical model, to obtain initial fields for the aerosol species. In our results, data assimilation significantly reduced the errors when compared to a simulation without assimilation, and improved forecasts of PM2.5 concentrations. Despite a drop in skill directly after the assimilation, a positive effect was present in forecasts for at least 12-2413, and there was a slight improvement in the 48-h forecasts. In addition to performing well in Shanghai, the verification statistics for this assimilation experiment are encouraging for most of the surface stations in China.