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| Titel |
Assessing optimal set of implemented physical parameterization schemes in a multi-physics land surface model using genetic algorithm |
| VerfasserIn |
S. Hong, X. Yu, S. K. Park, Y.-S. Choi, B. Myoung |
| 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 ; 7, no. 5 ; Nr. 7, no. 5 (2014-10-29), S.2517-2529 |
| Datensatznummer |
250115747
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| Publikation (Nr.) |
 copernicus.org/gmd-7-2517-2014.pdf |
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| Zusammenfassung |
| Optimization of land surface models has been challenging due to the model
complexity and uncertainty. In this study, we performed scheme-based model
optimizations by designing a framework for coupling "the micro-genetic
algorithm" (micro-GA) and "the Noah land surface model with multiple physics
options" (Noah-MP). Micro-GA controls the scheme selections among eight different land surface
parameterization categories, each containing 2–4 schemes, in Noah-MP in
order to extract the optimal scheme combination that achieves the best skill
score. This coupling framework was successfully applied to the optimizations
of evapotranspiration and runoff simulations in terms of surface water
balance over the Han River basin in Korea, showing outstanding speeds in
searching for the optimal scheme combination. Taking advantage of the
natural selection mechanism in micro-GA, we explored the model sensitivity
to scheme selections and the scheme interrelationship during the micro-GA
evolution process. This information is helpful for better understanding
physical parameterizations and hence it is expected to be effectively used
for further optimizations with uncertain parameters in a specific set of
schemes. |
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