Abstract
Method of joint analysis of ionospheric parameters and cosmic ray data is proposed. The method allowsto allocate anomalous changes in data before strong magnetic storms. The developed method is based on the application of wavelet transform, neural networks and classical autoregressive models. The application of the method has shown its effectiveness and the possibility of using in the problems of estimating space weather and predicting strong magnetic storms. The research was supported by RSF Grant, project No 14-11-00194.
Highlights
The work is aimed at studying processes in the near-Earth space during periods of increased solar activity and magnetic storms
In the article we performed a joint analysis of ionospheric parameters and galactic cosmic ray data (GCR)
GCR observations are used in a number of fundamental and applied studies related to monitoring and forecasting space weather [2,3]
Summary
The work is aimed at studying processes in the near-Earth space during periods of increased solar activity and magnetic storms. Its application allowed us to isolate the anomalous effects in the dynamics of GCR (increases that occur 820 hours before the onset of magnetic storms) [7, 10, 11] arising on the eve of geomagnetic storms These anomalies were first discovered by statistical analysis and described in [15]. In this paper, based on the joint analysis of the ionosphere parameters and GCR data on the eve of magnetic storms, anomalous increases in variations in the intensity of cosmic rays and the increase in the electron density of the ionosphere that arise during these periods are likely to be associated with the approaching events
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