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| Titel |
Structure of forecast error covariance in coupled atmosphere–chemistry data assimilation |
| VerfasserIn |
S. K. Park, S. Lim, M. Zupanski |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1991-959X
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| Digitales Dokument |
URL |
| Erschienen |
In: Geoscientific Model Development ; 8, no. 5 ; Nr. 8, no. 5 (2015-05-05), S.1315-1320 |
| Datensatznummer |
250116336
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| Publikation (Nr.) |
 copernicus.org/gmd-8-1315-2015.pdf |
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| Zusammenfassung |
| In this study, we examined the structure of an ensemble-based coupled
atmosphere–chemistry forecast error covariance. The Weather Research and
Forecasting (WRF) model coupled with Chemistry (WRF-Chem), a coupled
atmosphere–chemistry model, was used to create an ensemble error covariance.
The control variable includes both the dynamical and chemistry model
variables. A synthetic single observation experiment was designed in order to
evaluate the cross-variable components of a coupled error covariance. The
results indicate that the coupled error covariance has important
cross-variable components that allow a physically meaningful adjustment of
all control variables. The additional benefit of the coupled error covariance
is that a cross-component impact is allowed; e.g., atmospheric observations
can exert an impact on chemistry analysis, and vice versa. Given the
realistic structure of ensemble forecast error covariance produced by the
WRF-Chem, we anticipate that the ensemble-based coupled atmosphere–chemistry
data assimilation will respond similarly to assimilation of real
observations. |
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