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| Titel |
Statistical characteristics of surrogate data based on geophysical measurements |
| VerfasserIn |
V. Venema, S. Bachner, H. W. Rust, C. Simmer |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1023-5809
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| Digitales Dokument |
URL |
| Erschienen |
In: Nonlinear Processes in Geophysics ; 13, no. 4 ; Nr. 13, no. 4 (2006-09-12), S.449-466 |
| Datensatznummer |
250011814
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| Publikation (Nr.) |
 copernicus.org/npg-13-449-2006.pdf |
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| Zusammenfassung |
| In this study, the statistical properties of a range of
measurements are compared with those of their surrogate time series. Seven
different records are studied, amongst others, historical time series of
mean daily temperature, daily rain sums and runoff from two rivers, and
cloud measurements. Seven different algorithms are used to generate the
surrogate time series. The best-known method is the iterative amplitude
adjusted Fourier transform (IAAFT) algorithm, which is able to reproduce the
measured distribution as well as the power spectrum. Using this setup, the
measurements and their surrogates are compared with respect to their power
spectrum, increment distribution, structure functions, annual percentiles
and return values. It is found that the surrogates that reproduce the power
spectrum and the distribution of the measurements are able to closely match
the increment distributions and the structure functions of the measurements,
but this often does not hold for surrogates that only mimic the power
spectrum of the measurement. However, even the best performing surrogates do
not have asymmetric increment distributions, i.e., they cannot reproduce
nonlinear dynamical processes that are asymmetric in time. Furthermore, we
have found deviations of the structure functions on small scales. |
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