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| Titel |
Variational data assimilation with superparameterization |
| VerfasserIn |
I. Grooms, Y. Lee |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
2198-5634
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| Digitales Dokument |
URL |
| Erschienen |
In: Nonlinear Processes in Geophysics Discussions ; 2, no. 2 ; Nr. 2, no. 2 (2015-03-20), S.513-536 |
| Datensatznummer |
250115155
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| Publikation (Nr.) |
 copernicus.org/npgd-2-513-2015.pdf |
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| Zusammenfassung |
| Superparameterization (SP) is a multiscale computational approach
wherein a large scale atmosphere or ocean model is coupled to an
array of simulations of small scale dynamics on periodic domains
embedded into the computational grid of the large scale model. SP
has been successfully developed in global atmosphere and climate
models, and is a promising approach for new applications. The
authors develop a 3D-Var variational data assimilation framework for
use with SP; the relatively low cost and simplicity of 3D-Var in
comparison with ensemble approaches makes it a natural fit for
relatively expensive multiscale SP models. To demonstrate the
assimilation framework in a simple model, the authors develop a new
system of ordinary differential equations similar to the two-scale
Lorenz-'96 model. The system has one set of variables denoted
{Yi}, with large and small scale parts, and the SP
approximation to the system is straightforward. With the new
assimilation framework the SP model approximates the large scale
dynamics of the true system accurately. |
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