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Advanced spectral methods for climatic time series

Reviews of Geophysics

By:
, , , , , , , , , ,

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Abstract

The analysis of univariate or multivariate time series provides crucial information to describe, understand, and predict climatic variability. The discovery and implementation of a number of novel methods for extracting useful information from time series has recently revitalized this classical field of study. Considerable progress has also been made in interpreting the information so obtained in terms of dynamical systems theory. In this review we describe the connections between time series analysis and nonlinear dynamics, discuss signal- to-noise enhancement, and present some of the novel methods for spectral analysis. The various steps, as well as the advantages and disadvantages of these methods, are illustrated by their application to an important climatic time series, the Southern Oscillation Index. This index captures major features of interannual climate variability and is used extensively in its prediction. Regional and global sea surface temperature data sets are used to illustrate multivariate spectral methods. Open questions and further prospects conclude the review.

Additional Publication Details

Publication type:
Article
Publication Subtype:
Journal Article
Title:
Advanced spectral methods for climatic time series
Series title:
Reviews of Geophysics
Volume
40
Issue:
1
Year Published:
2002
Language:
English
Larger Work Type:
Article
Larger Work Subtype:
Journal Article
Larger Work Title:
Reviews of Geophysics
First page:
3
Last page:
1
Number of Pages:
-1