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| Titel |
Improvement of ozone forecast over Beijing based on ensemble Kalman filter with simultaneous adjustment of initial conditions and emissions |
| VerfasserIn |
X. Tang, J. Zhu, Z. F. Wang, A. Gbaguidi |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1680-7316
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| Digitales Dokument |
URL |
| Erschienen |
In: Atmospheric Chemistry and Physics ; 11, no. 24 ; Nr. 11, no. 24 (2011-12-20), S.12901-12916 |
| Datensatznummer |
250010285
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| Publikation (Nr.) |
 copernicus.org/acp-11-12901-2011.pdf |
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| Zusammenfassung |
| In order to improve the surface ozone forecast over Beijing and surrounding
regions, data assimilation method integrated into a high-resolution regional
air quality model and a regional air quality monitoring network are
employed. Several advanced data assimilation strategies based on ensemble
Kalman filter are designed to adjust O3 initial conditions, NOx initial
conditions and emissions, VOCs initial conditions and emissions separately
or jointly through assimilating ozone observations. As a result, adjusting
precursor initial conditions demonstrates potential improvement of the
1-h ozone forecast almost as great as shown by adjusting precursor
emissions. Nevertheless, either adjusting precursor initial conditions or
emissions show deficiency in improving the short-term ozone forecast at
suburban areas. Adjusting ozone initial values brings significant
improvement to the 1-h ozone forecast, and its limitations lie in the
difficulty in improving the 1-h forecast at some urban site. A
simultaneous adjustment of the above five variables is found to be able to
reduce these limitations and display an overall better performance in
improving both the 1-h and 24-h ozone forecast over these areas. The
root mean square errors of 1-h ozone forecast at urban sites and suburban
sites decrease by 51% and 58% respectively compared with those in free
run. Through these experiments, we found that assimilating local ozone
observations is determinant for ozone forecast over the observational area,
while assimilating remote ozone observations could reduce the uncertainty in
regional transport ozone. |
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