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| Titel |
ENSO dynamics in current climate models: an investigation using nonlinear dimensionality reduction |
| VerfasserIn |
I. Ross, P. J. Valdes, S. Wiggins |
| 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 ; 15, no. 2 ; Nr. 15, no. 2 (2008-04-22), S.339-363 |
| Datensatznummer |
250012621
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| Publikation (Nr.) |
 copernicus.org/npg-15-339-2008.pdf |
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| Zusammenfassung |
| Linear dimensionality reduction techniques, notably principal
component analysis, are widely used in climate data analysis as a
means to aid in the interpretation of datasets of high dimensionality.
These linear methods may not be appropriate for the analysis of data
arising from nonlinear processes occurring in the climate system.
Numerous techniques for nonlinear dimensionality reduction have been
developed recently that may provide a potentially useful tool for the
identification of low-dimensional manifolds in climate data sets
arising from nonlinear dynamics. Here, we apply Isomap, one such
technique, to the study of El Niño/Southern Oscillation
variability in tropical Pacific sea surface temperatures, comparing
observational data with simulations from a number of current coupled
atmosphere-ocean general circulation models. We use Isomap to examine
El Niño variability in the different datasets and assess the
suitability of the Isomap approach for climate data analysis. We
conclude that, for the application presented here, analysis using
Isomap does not provide additional information beyond that already
provided by principal component analysis. |
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