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| Titel |
A method to identify aperiodic disturbances in the ionosphere |
| VerfasserIn |
J.-S. Wang, Z. Chen, C.-M. Huang |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
0992-7689
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| Digitales Dokument |
URL |
| Erschienen |
In: Annales Geophysicae ; 32, no. 5 ; Nr. 32, no. 5 (2014-05-26), S.563-569 |
| Datensatznummer |
250121063
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| Publikation (Nr.) |
 copernicus.org/angeo-32-563-2014.pdf |
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| Zusammenfassung |
| In this paper, variations in the ionospheric F2 layer's
critical frequency are decomposed into their periodic and aperiodic
components. The latter include disturbances caused both by geophysical
impacts on the ionosphere and random noise. The spectral whitening method
(SWM), a signal-processing technique used in statistical estimation and/or
detection, was used to identify aperiodic components in the ionosphere. The
whitening algorithm adopted herein is used to divide the Fourier transform of the
observed data series by a real envelope function. As a result, periodic
components are suppressed and aperiodic components emerge as the dominant
contributors. Application to a synthetic data set based on significant
simulated periodic features of ionospheric observations containing
artificial (and, hence, controllable) disturbances was used to validate the
SWM for identification of aperiodic components. Although the random noise
was somewhat enhanced by post-processing, the artificial disturbances could
still be clearly identified. The SWM was then applied to real ionospheric
observations. It was found to be more sensitive than the often-used monthly
median method to identify geomagnetic effects. In addition, disturbances
detected by the SWM were characterized by a Gaussian-type probability
density function over all timescales, which further simplifies statistical
analysis and suggests that the disturbances thus identified can be compared
regardless of timescale. |
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