Application of the cross wavelet transform and wavelet coherence to geophysical time series

Many scientists have made use of the wavelet method in analyzing time series, often using popular free software. However, at present there are no similar easy to use wavelet packages for analyzing two time series together. We discuss the cross wavelet transform and wavelet coherence for examining re...

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Bibliographic Details
Published in:Nonlinear Processes in Geophysics
Main Authors: Grinsted, A., Moore, J. C., Jevrejeva, S.
Format: Article in Journal/Newspaper
Language:English
Published: Copernicus Publications 2004
Subjects:
Online Access:https://doi.org/10.5194/npg-11-561-2004
https://noa.gwlb.de/receive/cop_mods_00034548
https://noa.gwlb.de/servlets/MCRFileNodeServlet/cop_derivate_00034502/npg-11-561-2004.pdf
https://npg.copernicus.org/articles/11/561/2004/npg-11-561-2004.pdf
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Summary:Many scientists have made use of the wavelet method in analyzing time series, often using popular free software. However, at present there are no similar easy to use wavelet packages for analyzing two time series together. We discuss the cross wavelet transform and wavelet coherence for examining relationships in time frequency space between two time series. We demonstrate how phase angle statistics can be used to gain confidence in causal relationships and test mechanistic models of physical relationships between the time series. As an example of typical data where such analyses have proven useful, we apply the methods to the Arctic Oscillation index and the Baltic maximum sea ice extent record. Monte Carlo methods are used to assess the statistical significance against red noise backgrounds. A software package has been developed that allows users to perform the cross wavelet transform and wavelet coherence (www.pol.ac.uk/home/research/waveletcoherence/).