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New Significance Test Methods for Fourier Analysis of Geophysical Time Series : Volume 18, Issue 5 (27/09/2011)

By Zhang, Z.

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Book Id: WPLBN0003983339
Format Type: PDF Article :
File Size: Pages 10
Reproduction Date: 2015

Title: New Significance Test Methods for Fourier Analysis of Geophysical Time Series : Volume 18, Issue 5 (27/09/2011)  
Author: Zhang, Z.
Volume: Vol. 18, Issue 5
Language: English
Subject: Science, Nonlinear, Processes
Collections: Periodicals: Journal and Magazine Collection (Contemporary), Copernicus GmbH
Historic
Publication Date:
2011
Publisher: Copernicus Gmbh, Göttingen, Germany
Member Page: Copernicus Publications

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Moore, J., & Zhang, Z. (2011). New Significance Test Methods for Fourier Analysis of Geophysical Time Series : Volume 18, Issue 5 (27/09/2011). Retrieved from http://hawaiilibrary.net/


Description
Description: College of Global Change and Earth System Science, Beijing Normal University, China. 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.

Summary
New significance test methods for Fourier analysis of geophysical time series

Excerpt
Baldwin, M. P. and T. J. Dunkerton, Stratospheric harbingers of anomalous weather regimes, Science, 294, 581–584, 2001.; Brockwell, P. J. and Davis, R. A., Time series: Theory and Methods, Springer-Verlag, New York, 1991.; Chatfield, C.: The Analysis of Time Series: An Introduction, 4th Edn., Chapman and Hall, 1989.; Gilman, D. L., Fuglister, F. J., and Mitchell Jr., J. M.: On the power spectrum of red noise, J. Atmos. Sci., 20, 182–184, 1963.; Ghil, M., Allen, M. R., Dettinger, M. D., Ide, K., Kondrashov, D., Mann, M. E., Robertson, A. W., Saunders, A., Tian, Y., Varadi, F., and Yiou, P.: Advanced spectral methods for climatic time series, Rev. Geophys., 40, 1003–1043, 2002.; Jenkins, G. M. and Watts, D. G.: Spectral Analysis and Its Applications, Holden-Day, 1968.; Jevrejeva, S., Moore, J., and Grinsted, A.: Influence of the Arctic Oscillation and El Nino-Southern Oscillation (ENSO) on ice conditions in the Baltic Sea: The wavelet approach, J. Geophys. Res., 108, 4677–4687, 2003.; Jevrejeva, S., Moore, J., and Grinsted, A.: Oceanic and atmospheric transport of multiyear El Nino-Southern Oscillation (ENSO) signatures to the polar regions, Geophys. Res. Lett., 31, L24210/1-4, doi:10.1029/2004GL020871, 2004.; Kaplan, A., Cane, M., Kushnir, Y., Clement, A., Blumenthal, M., and Rajagopalan, B.: Analyses of global sea surface temperature 1856–1991, J. Geophys. Res., 103, 18567–18589, 1998.; Mann, M. E. and Lees, J. M.. Robust Estimation of Background Noise and Signal Detection in Climatic Time Series, Clim. Change, 33, 409–445, 1996.; Oppenheim, A. V. and Schafer, R. W.: Discrete-Time Signal Processing, Prentice-Hall, 1989.; Thompson, D. W. J. and Wallace, J. M.: The Arctic Oscillation signature in the winter geopotential height and temperature fields, Geophys. Res. Lett., 25, 1297–1300, 1998.; Torrence, C. and Compo, G. P.: A Practical Guide to Wavelet Analysis, B. Am. Meteorol. Soc., 79, 61–78, 1998; Zar, J. H.: Biostatistical Analysis, Prentice hall, New Jersey, 1999.

 

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