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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.

Article / Publication Data
Available Metadata
Accepted On
October 21, 2014
Early Online Release
February 10, 2015
Fiscal Year
Peer Reviewed
Publication Name
Published On
June 01, 2015
Publisher Name
Science Direct
Print Volume
Page Range
Submitted On
July 29, 2014


Not available


Authors who have authored or contributed to this publication.

  • Jian-Bin Wu - lead None
  • Mariusz Pagowski - third Gsl
    Cooperative Institute for Research in Environmental Sciences, University of Colorado Boulder
    NOAA/Global Systems Laboratory