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| Titel |
On closure parameter estimation in chaotic systems |
| VerfasserIn |
J. Hakkarainen, A. Ilin, A. Solonen, M. Laine, H. Haario, J. Tamminen, E. Oja, H. Järvinen |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1023-5809
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| Digitales Dokument |
URL |
| Erschienen |
In: Nonlinear Processes in Geophysics ; 19, no. 1 ; Nr. 19, no. 1 (2012-02-15), S.127-143 |
| Datensatznummer |
250014169
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| Publikation (Nr.) |
 copernicus.org/npg-19-127-2012.pdf |
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| Zusammenfassung |
| Many dynamical models, such as numerical weather prediction and climate models,
contain so called closure parameters. These parameters usually appear in physical
parameterizations of sub-grid scale processes, and they act as
"tuning handles" of the models. Currently, the values of
these parameters are specified mostly manually, but
the increasing complexity of the models calls for more algorithmic
ways to perform the tuning. Traditionally, parameters of dynamical
systems are estimated by directly comparing the model simulations to
observed data using, for instance, a least squares
approach. However, if the models are chaotic, the classical approach
can be ineffective, since small errors in the initial conditions can
lead to large, unpredictable deviations from the observations. In
this paper, we study numerical methods available for estimating
closure parameters in chaotic models. We discuss three techniques:
off-line likelihood calculations using filtering methods, the state
augmentation method, and the approach that utilizes summary
statistics from long model simulations. The properties of the
methods are studied using a modified version of the Lorenz 95
system, where the effect of fast variables are described using a
simple parameterization. |
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