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Structure of forecast error covariance in coupled atmosphere-chemistry data assimilation

Title
Structure of forecast error covariance in coupled atmosphere-chemistry data assimilation
Authors
Park, S. K.Lim, S.Zupanski, M.
Ewha Authors
박선기
SCOPUS Author ID
박선기scopus
Issue Date
2015
Journal Title
GEOSCIENTIFIC MODEL DEVELOPMENT
ISSN
1991-959XJCR Link1991-9603JCR Link
Citation
vol. 8, no. 5, pp. 1315 - 1320
Publisher
COPERNICUS GESELLSCHAFT MBH
Indexed
SCIE; SCOPUS WOS scopus
Abstract
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.
DOI
10.5194/gmd-8-1315-2015
Appears in Collections:
엘텍공과대학 > 환경공학전공 > Journal papers
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