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Titel |
Implementation and testing of a simple data assimilation algorithm in the regional air pollution forecast model, DEOM |
VerfasserIn |
J. Frydendall, J. Brandt, J. H. Christensen |
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 ; 9, no. 15 ; Nr. 9, no. 15 (2009-08-04), S.5475-5488 |
Datensatznummer |
250007554
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Publikation (Nr.) |
copernicus.org/acp-9-5475-2009.pdf |
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Zusammenfassung |
A simple data assimilation algorithm based on statistical interpolation has
been developed and coupled to a long-range chemistry transport model, the
Danish Eulerian Operational Model (DEOM), applied for air pollution
forecasting at the National Environmental Research Institute (NERI), Denmark.
In this paper, the algorithm and the results from experiments designed to
find the optimal setup of the algorithm are described. The algorithm has been
developed and optimized via eight different experiments where the results
from different model setups have been tested against measurements from the
EMEP (European Monitoring and Evaluation Programme) network covering a
half-year period, April–September 1999. The best performing setup of the
data assimilation algorithm for surface ozone concentrations has been found,
including the combination of determining the covariances using the
Hollingsworth method, varying the correlation length according to the number
of adjacent observation stations and applying the assimilation routine at
three successive hours during the morning. Improvements in the correlation
coefficient in the range of 0.1 to 0.21 between the results from the
reference and the optimal configuration of the data assimilation algorithm,
were found. The data assimilation algorithm will in the future be used in the
operational THOR integrated air pollution forecast system, which includes the
DEOM. |
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