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

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 PM2.5 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 12-24 h, 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. (c) 2015 Chinese Society of Particuology and Institute of Process Engineering, Chinese Academy of Sciences. Published by Elsevier B.V. All rights reserved.