New significance test methods for Fourier analysis of geophysical time series

When one applies the discrete Fourier transform to analyze finite-length time series, discontinuities at the data boundaries will distort its Fourier power spectrum. In this paper, based on a rigid statistics framework, we present a new significance test method which can extract the intrinsic featur...

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Bibliographic Details
Published in:Nonlinear Processes in Geophysics
Main Authors: Z. Zhang, J. Moore
Format: Article in Journal/Newspaper
Language:English
Published: Copernicus Publications 2011
Subjects:
Q
Online Access:https://doi.org/10.5194/npg-18-643-2011
https://doaj.org/article/a304f69228094d6ba26e015b9d59e661
Description
Summary:When one applies the discrete Fourier transform to analyze finite-length time series, discontinuities at the data boundaries will distort its Fourier power spectrum. In this paper, based on a rigid statistics framework, we present a new significance test method which can extract the intrinsic feature of a geophysical time series very well. We show the difference in significance level compared with traditional Fourier tests by analyzing the Arctic Oscillation (AO) and the Nino3.4 time series. In the AO, we find significant peaks at about 2.8, 4.3, and 5.7 yr periods and in Nino3.4 at about 12 yr period in tests against red noise. These peaks are not significant in traditional tests.