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| Titel |
HAAR WAVELET ANALYSIS OF CLIMATIC TIME SERIES |
| VerfasserIn |
Zhihua Zhang, John Moore, Aslak Grinsted |
| Konferenz |
EGU General Assembly 2014
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| Medientyp |
Artikel
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| Sprache |
Englisch
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| Digitales Dokument |
PDF |
| Erschienen |
In: GRA - Volume 16 (2014) |
| Datensatznummer |
250087286
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| Publikation (Nr.) |
 EGU/EGU2014-1318.pdf |
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| Zusammenfassung |
| In order to extract the intrinsic information of climatic time series from background red noise,
we will first give an analytic formula on the distribution of Haar wavelet power spectra of red
noise in a rigorous statistical framework. The relation between scale aand Fourier period T for
the Morlet wavelet is a= 0.97T . However, for Haar wavelet, the corresponding formula is a=
0.37T . Since for any time series of time step δt and total length Nδt, the range of scales is
from the smallest resolvable scale 2δt to the largest scale Nδt in wavelet-based time series
analysis, by using the Haar wavelet analysis, one can extract more low frequency intrinsic
information. Finally, we use our method to analyze Arctic Oscillation which is a key aspect of
climate variability in the Northern Hemisphere, and discover a great change in
fundamental properties of the AO,—commonly called a regime shift or tripping
point.
Our partial results have been published as follows:
[1] Z. Zhang, J.C. Moore and A. Grinsted, Haar wavelet analysis of climatic time series,
Int. J. Wavelets, Multiresol. & Inf. Process., in press, 2013
[2] Z. Zhang, J.C. Moore, Comment on "Significance tests for the wavelet power and the
wavelet power spectrum", Ann. Geophys., 30:12, 2012 |
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