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GEOLINKS International Conference 2020, Book 1



Dr. Laurențiu Asimopolos, Dr. Natalia-Silvia Asimopolos, Asist. Prof. Adrian-Aristide Asimopolos


The purpose of this study was to analyze the associated spectrum of geomagnetic field, frequencies intensity and the time of occurrence. We calculated the variation of the correlation coefficients, with mobile windows of various sizes, for the recorded magnetic components at different latitudes and latitudes.
We included in our study the observatories: Surlari (USA), Honolulu (HON), Scott Base (SBA), Kakioka (KAK), Tihany (THY), Uppsala (UPS), Wingst (WNG) and Yellowknife (YKC). We used the data of these observatories from INTERMAGNET for the biggest geomagnetic storm from the last two Solar Cycles.
We have used for this purpose a series of filtering algorithms, spectral analysis and wavelet with different mother functions at different levels.
In the paper, we show the Fourier and wavelet analysis of geomagnetic data recorded at different observatories regarding geomagnetic storms. Fourier analysis highlights predominant frequencies of magnetic field components. Wavelet analysis provides information about the frequency ranges of magnetic fields, which contain long time intervals for medium frequency information and short time intervals for highlight frequencies, details of the analyzed signals. Also, the wavelet analysis allows us to decompose geomagnetic signals in different waves. The analyzes presented are significant for the studied of the geomagnetic storm. The data for the next days after the storm showed a mitigation of the perturbations and a transition to a quiet day of the geomagnetic field.
In both, the Fourier Transformation and the Wavelet Transformation, transformation evaluation involves the calculation of a scalar product between the analyzed signal and a set of signals that form a particular base in the vector space of the finite energy signals. Fourier representation use an orthogonal vectors base, whereas in the case of wavelet there is the possibility to use also bases consisting of independent linear non-orthogonal vectors. Unlike the Fourier transform, which depends only on a single parameter, wavelet transform type depends on two parameters, a and b. As a result, the graphical representation of the spectrum is different, wavelet analysis bringing more information about geomagnetic pattern of each observatory with that own specific conditions.



geomagnetic storm, spectral analysis, Fourier transform, wavelet analysis

GEOLINKS International Conference, Conference Proceedings, ISSN 2603-5472, ISBN 978-619-7495-07-2, ANALYSES OF GEOMAGNETIC DATA SETS FROM OBSERVATORIES AND CORRELATION BETWEEN THEM, 13-22 pp, DOI paper 10.32008/GEOLINKS2020/B1/V2/01
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