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

Research output: Contribution to journalJournal articleResearchpeer-review

Standard

Application of the cross wavelet transform and wavelet coherence to geophysical time series. / Grinsted, Aslak; Moore, J C; Jevrejeva, S.

In: Nonlinear Processes in Geophysics, Vol. 11, 2004, p. 561-566.

Research output: Contribution to journalJournal articleResearchpeer-review

Harvard

Grinsted, A, Moore, JC & Jevrejeva, S 2004, 'Application of the cross wavelet transform and wavelet coherence to geophysical time series', Nonlinear Processes in Geophysics, vol. 11, pp. 561-566.

APA

Grinsted, A., Moore, J. C., & Jevrejeva, S. (2004). Application of the cross wavelet transform and wavelet coherence to geophysical time series. Nonlinear Processes in Geophysics, 11, 561-566.

Vancouver

Grinsted A, Moore JC, Jevrejeva S. Application of the cross wavelet transform and wavelet coherence to geophysical time series. Nonlinear Processes in Geophysics. 2004;11:561-566.

Author

Grinsted, Aslak ; Moore, J C ; Jevrejeva, S. / Application of the cross wavelet transform and wavelet coherence to geophysical time series. In: Nonlinear Processes in Geophysics. 2004 ; Vol. 11. pp. 561-566.

Bibtex

@article{5d414110e62c11ddbf70000ea68e967b,
title = "Application of the cross wavelet transform and wavelet coherence to geophysical time series",
abstract = "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/).",
author = "Aslak Grinsted and Moore, {J C} and S Jevrejeva",
year = "2004",
language = "English",
volume = "11",
pages = "561--566",
journal = "Nonlinear Processes in Geophysics",
issn = "1023-5809",
publisher = "Copernicus GmbH",

}

RIS

TY - JOUR

T1 - Application of the cross wavelet transform and wavelet coherence to geophysical time series

AU - Grinsted, Aslak

AU - Moore, J C

AU - Jevrejeva, S

PY - 2004

Y1 - 2004

N2 - 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/).

AB - 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/).

M3 - Journal article

VL - 11

SP - 561

EP - 566

JO - Nonlinear Processes in Geophysics

JF - Nonlinear Processes in Geophysics

SN - 1023-5809

ER -

ID: 9832592