Russian Journal of Earth Sciences Russian Journal of Earth Sciences Russian Journal of Earth Sciences 1681-1208 46867 ОРИГИНАЛЬНЫЕ СТАТЬИ ORIGINAL ARTICLES ОРИГИНАЛЬНЫЕ СТАТЬИ A technique for detection of ULF Pc3 waves and their statistical analysis A technique for detection of ULF Pc3 waves and their statistical analysis Bogoutdinov Sh R Bogoutdinov Sh R Yagova N V Yagova N V Pilipenko V A Pilipenko V A Agayan S M Agayan S M Geophysical Center of the Russian Academy of Sciences GC RAS ru Geophysical Center of the Russian Academy of Sciences GC RAS ru Schmidt Institute of Physics of the Earth of the Russian Academy of Sciences IPE RAS ru Schmidt Institute of Physics of the Earth of the Russian Academy of Sciences IPE RAS ru Geophysical Center of the Russian Academy of Sciences GC RAS ru Geophysical Center of the Russian Academy of Sciences GC RAS ru Geophysical Center of the Russian Academy of Sciences GC RAS ru Geophysical Center of the Russian Academy of Sciences GC RAS ru 18 6 1 13 10 11 2021 https://rjes.ru/en/nauka/article/46867/view

The results of different algorithms for automatic detection of wave packets in geomagnetic records are compared: the approach based on the Fourier transform in a running time window F-method, and the approach based on discrete perfect set DPS analysis. Using 1-sec data from a mid-latitude INTERMAGNET station we determined with both algorithms such statistical properties of Pc3 geomagnetic pulsations in the frequency range 30--80 mHz as diurnal variations, frequency occurrence, amplitude probability distributions, etc. The diurnal distributions of the occurrence probability determined by both methods have a wide peak around noon hours and a small enhancement during nighttime hours. The advantage of the DPS analysis is the possibility to determine duration of a wave packet. This method shows that average duration of dayside wave packets is statistically longer than that of the nighttime events. Statistical distributions over power/amplitude can be used to infer some conclusions about physical mechanisms of signals. The distribution obtained with the F-method differs for two horizontal components: $H$ component distribution is vulnerable to the magnetospheric resonance effect and reveals parabolic dependence in log-log scale, whereas non-resonant $D$ component has a power-law distribution. The DPS-method provides almost exponential decay of probability with amplitude for both components. The difference between statistical results of two methods is probably caused by different dependences of detection sensitivity to signal amplitude.

The results of different algorithms for automatic detection of wave packets in geomagnetic records are compared: the approach based on the Fourier transform in a running time window F-method, and the approach based on discrete perfect set DPS analysis. Using 1-sec data from a mid-latitude INTERMAGNET station we determined with both algorithms such statistical properties of Pc3 geomagnetic pulsations in the frequency range 30--80 mHz as diurnal variations, frequency occurrence, amplitude probability distributions, etc. The diurnal distributions of the occurrence probability determined by both methods have a wide peak around noon hours and a small enhancement during nighttime hours. The advantage of the DPS analysis is the possibility to determine duration of a wave packet. This method shows that average duration of dayside wave packets is statistically longer than that of the nighttime events. Statistical distributions over power/amplitude can be used to infer some conclusions about physical mechanisms of signals. The distribution obtained with the F-method differs for two horizontal components: $H$ component distribution is vulnerable to the magnetospheric resonance effect and reveals parabolic dependence in log-log scale, whereas non-resonant $D$ component has a power-law distribution. The DPS-method provides almost exponential decay of probability with amplitude for both components. The difference between statistical results of two methods is probably caused by different dependences of detection sensitivity to signal amplitude.

 geomagnetic pulsations ionosphere magnetosphere automatic signal detection geomagnetic pulsations ionosphere magnetosphere automatic signal detection

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