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| Titel |
Embedding reconstruction methodology for short time series – application to large El Niño events |
| VerfasserIn |
H. F. Astudillo, F. A. Borotto, R. Abarca-del-Rio |
| 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 ; 17, no. 6 ; Nr. 17, no. 6 (2010-12-14), S.753-764 |
| Datensatznummer |
250013762
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| Publikation (Nr.) |
 copernicus.org/npg-17-753-2010.pdf |
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| Zusammenfassung |
| We propose an alternative approach for the embedding space reconstruction method for short time series.
An m-dimensional embedding space is reconstructed with a set of time delays including the relevant time
scales characterizing the dynamical properties of the system. By using a maximal predictability criterion a d-dimensional
subspace is selected with its associated set of time delays, in which a local nonlinear blind forecasting prediction performs
the best reconstruction of a particular event of a time series. An locally unfolded d-dimensional embedding space is then obtained.
The efficiency of the methodology, which is mathematically consistent with the fundamental definitions of
the local nonlinear long time-scale predictability, was tested with a chaotic time series of the Lorenz system.
When applied to the Southern Oscillation Index (SOI) (observational data associated with the El Niño-Southern
Oscillation phenomena (ENSO)) an optimal set of embedding parameters exists, that allows constructing the main
characteristics of the El Niño 1982–1983 and 1997–1998 events, directly from measurements up to 3 to 4 years in advance. |
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