Abstract
This work is directed at creation of methods of study of the processes in the ionospheric–magnetospheric system during increased solar and geomagnetic activity. Method of modeling and analysis of the parameters of the ionosphere, which allows prediction of the data and identification of the anomalies during the ionospheric disturbances, are given. Computational solutions for determination and estimation of the geomagnetic disturbances are described. Method of determination of the anomalous changes in the time course of cosmic rays, which allows qualitative estimations of the moments of their origination, duration, and intensity, is suggested.
On the basis of the methods elaborated, the data on the periods of strong and moderate magnetic storms are complexly analyzed. Sharp oscillations in the electron density of the ionosphere with positive and negative phases, which originate in the regions analyzed during an increase in geomagnetic activity, are distinguished. Positive phases of the ionospheric disturbances from several hours to one and a half days long were formed before the beginning of the magnetic storms. At the moments of the increase in the electron concentration, a local increase is observed in the level of cosmic rays (several hours before the magnetic storms) that supported the solar nature of these effects. During the strongest geomagnetic disturbances, the electron concentration in the ionosphere decreased significantly and led to prolonged negative phases of ionospheric storms, which coincided with the decrease in the level of cosmic rays (a Forbush decrease).
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Oksana Viktorovna Mandrikova, born 1972. Graduated from Shevchenko Kiev State University, 1995. Received doctoral degree in 2009, Doctor of Technical Sciences. Head of Laboratory of System Analysis at the Institute of Cosmophysical Research and Radio Wave Propagation, Far East Branch, Russian Academy of Sciences, and Professor in the Department of Monitoring Systems, Kamchatka State Technical University. Scientific interests: Intellectual methods of analysis of geophysical data, wavelets, neuron networks, the ionosphere, the magnetosphere, cosmic weather.
More than 100 publications. Member of the Editorial Board of the journal Vestnik of Kamchatka State Technical University, member of the National Committee for Pattern Recognition and Image analysis, member of the international organization Asia Oceania Geosciences Society. Awarded a grant of the President of the Russian Federation for young doctors of sciences no. MD-2199.2011.9.
Yurii Aleksandrovich Polozov, born 1983. Graduated from Kamchatka State Technical University, 2005. Received candidate’s degree in 2011, Candidate of Technical Sciences. Senior researcher, Laboratory of System Analysis, Institute of Cosmophysical Research and Radio Wave Propagation, Far East Branch, Russian Academy of Sciences, and Docent, Department of Systems of Monitoring, Kamchatka State Technical University. Scientific interests: Analysis of complex signals, wavelets, neuron networks, ionospheric networks, ionospheric processes, anomalous features of signals. 17 publications. Received a grant of the Federal Program UMNIK, 2011, and a grant of the President of the Russian Federation (SP-2976.2013.5).
Igor Sergeevich Solovev, born 1986. Graduated from Kamchatka State Technical University, 2008, Received candidate’s degree in 2013, Candidate of Technical Sciences. Senior researcher, Laboratory of System Analysis, Institute of Cosmophysical Research and Radio Wave Propagation, Far East Branch, Russian Academy of Sciences, and Docent, Department of Systems of Monitoring, Kamchatka State Technical University. Scientific interests: Digital processing of data, wavelet transform, magnetic field of the Earth, magnetic storms. 46 publications. Received a grant of the Federal Program UMNIK, 2011.
Nadezhda Vladimirovna Fetisova, born 1987. Graduated from Kamchatka State Technical University, 2009. Junior researcher, Laboratory of System Analysis, Institute of Cosmophysical Research and Radio Wave Propagation, Far East Branch, Russian Academy of Sciences. Scientific interests: Analysis of complex signals, wavelets, models of autoregressive integrated moving average, ionospheric processes, anomalous features of signals. 18 publications.
Mikhail Stepanovich Kupriyanov, born 1951. Graduated from Omsk Polytechnical Insitute, 1975, and received doctoral degree in 1991, Doctor of Technical Sciences. Head of the Department of Computer Techniques, Ul’yanov (Lenin) St. Petersburg Electrotechnical University (LETI). Scientific interests: Theory and practical implementation of computer technologies and computer systems, intellectual methods and methods of supporting of high work capacity of information systems, distributed systems and technologies, microprocessing technologies, digital processing of signals, intellectual technologies. More than 100 publications. Received award Honored Worker of Higher Schools of Russian Federation and Laureate of Award of the Government of Russian Federation in the area of education.
Timur Lenarovich Zalyaev, born 1989. Graduated from Kamchatka State Technical University, 2011. Junior researcher, Laboratory of System Analysis, Institute of Cosmophysical Research and Radio Wave Propagation, Far East Branch, Russian Academy of Sciences. Scientific interests: Digital processing of data, wavelet tranform, cosmic rays, Forbush effects. 21 publications. Received a grant of the Federal Program UMNIK, 2013.
Aleksei Vladimirovich Dmitriev, born 1968. Graduated from Moscow State University, 1993, Received candidate’s degree in 1996, Candidate of Mathematical and Physical Sciences. Project-appointed research fellow, National Central University, Graduate Institute of Space Science Taiwan, Taoyuan City. Scientific interests: Plasma, plasma physics, space technologies. More than 140 publications. Member of the American Geophysical Union, member of editorial board of the journal of Terrestrial, Atmospheric and Oceanic Sciences.
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Mandrikova, O.V., Polozov, Y.A., Solovev, I.S. et al. Methods of analysis of geophysical data during increased solar activity. Pattern Recognit. Image Anal. 26, 406–418 (2016). https://doi.org/10.1134/S1054661816020103
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DOI: https://doi.org/10.1134/S1054661816020103