Speaker
Description
An important direction within the core project of the Geological Institute of Romania, entitled "Geomagnetism, a modern tool in space weather forecasting and rapid response to associated natural hazards for the protection of critical infrastructures and national air traffic security", is the study of geomagnetic storms and the methodology for complex analysis of these phenomena. In the present work, we used data from the geomagnetic observatories of the INTERMAGNET network, sampled at 1 minute, for the day of January 1, when a major geomagnetic storm occurred. The geomagnetic field varies in time and space, being a signal composed of periodic and non-periodic elements and is monitored in a three-axial system. In the paper, based on these data, we use spectral evaluation (Fourier, wavelet, signal decomposition into approximations and details with various functions on different levels, etc.) to analyze various geomagnetic phenomena (such as: geomagnetic storms, disturbances, etc.) and their degree of occurrence. The superiority of the wavelet methodology over Fourier consists in obtaining information in the form of a three-dimensional graph (time, frequency, amplitude). The precise specification of the time duration of a geomagnetic signal decreases the accuracy of its spectral information and vice versa, according to the Heisenberg uncertainty principle. Thus, we obtain good temporal accuracy for high-frequency phenomena (at the expense of the accuracy of the amplitude of these frequencies), respectively, we will be able to know with greater accuracy the amplitude of the low-frequency components existing in the signal, without strictly localizing the moments in which they appear. The wavelet technique allowed us to analyze the local components of the magnetic field through variable frequency windows and different functions, such as: Haar, Daubechies, Biorthogonal, Coiflets, Symlets, Morlet, Meyer and Mexican Hat. Windows with longer time intervals allowed us to extract low-frequency information, average window times led us to extract medium-frequency information, and very narrow windows highlight high frequencies or details of the analyzed signals. The model of the disturbed geomagnetic field is composed of periodic oscillations plus non-periodic oscillations given by the impact of the solar wind on the terrestrial magnetosphere. Wavelet coherence is applicable to the analysis of non-stationary signals and uses the analytical Morlet wavelet, being able to detect events such as geomagnetic field anomalies, change points and transitions. The arrows in the coherence plot indicate the phase relationship between the two signals at each time point and frequency (or period). The phase angle of the cross-spectrum is the same as the phase difference between the signals. The direction of the arrows in regions of high coherence can help to understand the phase relationship. From the data analyzed from geomagnetic observatories for the three-axial components and the total field, very good wavelet correlation and coherence were found during the geomagnetic storm.
