Methods of analysis of geophysical data during increased solar activity

O. V. Mandrikova, Yu A. Polozov, I. S. Solovev, N. V. Fetisova (Glushkova), T. L. Zalyaev, M. S. Kupriyanov, A. V. Dmitriev

Research output: Contribution to journalArticlepeer-review

7 Scopus citations

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).

Original languageEnglish
Pages (from-to)406-418
Number of pages13
JournalPattern Recognition and Image Analysis
Volume26
Issue number2
DOIs
StatePublished - 1 Apr 2016

Keywords

  • autoregressive integrated moving average model
  • critical frequency of the ionosphere
  • ionospheric disturbances
  • magnetic storm
  • variations in the geomagnetic field
  • wavelet transform

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