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| Titel |
Skill in forecasting extreme ozone pollution episodes with a global atmospheric chemistry model |
| VerfasserIn |
J. L. Schnell, C. D. Holmes, A. Jangam, M. J. Prather |
| 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 ; 14, no. 15 ; Nr. 14, no. 15 (2014-08-04), S.7721-7739 |
| Datensatznummer |
250118918
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| Publikation (Nr.) |
 copernicus.org/acp-14-7721-2014.pdf |
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| Zusammenfassung |
| From the ensemble of stations that monitor surface air quality over the
United States and Europe, we identify extreme ozone pollution events and find
that they occur predominantly in clustered, multiday episodes with spatial
extents of more than 1000 km. Such scales are amenable to forecasting with
current global atmospheric chemistry models. We develop an objective mapping
algorithm that uses the heterogeneous observations of the individual surface
sites to calculate surface ozone averaged over 1° by 1° grid
cells, matching the resolution of a global model. Air quality extreme (AQX)
events are identified locally as statistical extremes of the ozone
climatology and not as air quality exceedances. With the University of
California, Irvine chemistry-transport model (UCI CTM) we find there is skill
in hindcasting these extreme episodes, and thus identify a new diagnostic
using global chemistry–climate models (CCMs) to identify changes in the
characteristics of extreme pollution episodes in a warming climate. |
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