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Embedding Reconstruction Methodology for Short Time Series – Application to Large El Niño Events : Volume 17, Issue 6 (14/12/2010)

By Astudillo, H. F.

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Book Id: WPLBN0003976227
Format Type: PDF Article :
File Size: Pages 12
Reproduction Date: 2015

Title: Embedding Reconstruction Methodology for Short Time Series – Application to Large El Niño Events : Volume 17, Issue 6 (14/12/2010)  
Author: Astudillo, H. F.
Volume: Vol. 17, Issue 6
Language: English
Subject: Science, Nonlinear, Processes
Collections: Periodicals: Journal and Magazine Collection (Contemporary), Copernicus GmbH
Publication Date:
Publisher: Copernicus Gmbh, Göttingen, Germany
Member Page: Copernicus Publications


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Borotto, F. A., Abarca-Del-Rio, R., & Astudillo, H. F. (2010). Embedding Reconstruction Methodology for Short Time Series – Application to Large El Niño Events : Volume 17, Issue 6 (14/12/2010). Retrieved from

Description: Departamento de Física, Universidad de Concepción, Casilla 160-C, Concepción, Chile. 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.

Embedding reconstruction methodology for short time series – application to large El Niño events

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