ADVANCED SPECTRAL METHODS FOR CLIMATIC TIME SERIES
University of California, Los Angeles · NOAA National Centers for Environmental Prediction · +7 more institutions
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…
Citation impact
- FWCI
- 31.36
- Percentile
- 100%
- References
- 271
Authors
11- MGMichael GhilCorresponding
University of California, Los Angeles, NOAA National Centers for Environmental Prediction, Institute of Geophysics
- MRM. R. Allen
United States Geological Survey
- MDMichael D. Dettinger
University of Virginia
- KIKayo Ide
University of California, Los Angeles, Institute of Geophysics
- DKDmitri Kondrashov
University of California, Los Angeles, Institute of Geophysics
Topics & keywords
- Univariate
- Series (stratigraphy)
- Time series
- Multivariate statistics
- Computer science
- Spectral analysis
- Field (mathematics)
- Singular spectrum analysis
- Climate action