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| Titel |
Conditional nonlinear optimal perturbation and its applications |
| VerfasserIn |
M. Mu, W. S. Duan, B. Wang |
| 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 ; 10, no. 6 ; Nr. 10, no. 6, S.493-501 |
| Datensatznummer |
250008205
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| Publikation (Nr.) |
 copernicus.org/npg-10-493-2003.pdf |
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| Zusammenfassung |
| Conditional
nonlinear optimal perturbation (CNOP) is proposed to study the
predictability of numerical weather and climate prediction. A simple
coupled ocean-atmosphere model for ENSO is adopted as an example to show
its applicability. In the case of climatological mean state being the
basic state, it is shown that CNOP tends to evolve into El Niño or La
Niña event more probably than linear singular vector (LSV) on the
condition that CNOP and LSV are of the same magnitude of norm. CNOP is
also employed to study the prediction error of El Niño and La Niña
events. Comparisons between CNOP and LSV demonstrate that CNOP is more
applicable in studying the predictability of the models governing the
nonlinear motions of oceans and atmospheres. |
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