 |
| Titel |
Modeling study of a severe aerosol pollution event in December 2013 over Shanghai China: An application of chemical data assimilation |
| VerfasserIn |
Jian-Bin Wu, Jianming Xu, Mariusz Pagowski, Fuhai Geng, Songqiang Gu, Guangqiang Zhou, Ying Xie, Zhongqi Yu |
| Konferenz |
EGU General Assembly 2015
|
| Medientyp |
Artikel
|
| Sprache |
Englisch
|
| Digitales Dokument |
PDF |
| Erschienen |
In: GRA - Volume 17 (2015) |
| Datensatznummer |
250104867
|
| Publikation (Nr.) |
 EGU/EGU2015-4307.pdf |
|
|
|
|
|
| Zusammenfassung |
| 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. |
|
|
|
|
|
|