Preliminary investigation of the multivariate relations between program-selected forbush decreases, worldwide lightning frequency, sunspot number and other solar-terrestrial drivers

The European Physical Journal Plus - Tập 137 - Trang 1-19 - 2022
O. Okike1, J. A. Alhassan2
1Department of Industrial Physics, Faculty of Science, Ebonyi State University, Abakaliki, Nigeria
2Department of Physics and Astronomy, University of Nigeria, Nsukka, Nigeria

Tóm tắt

Solar wind disturbances such as coronal mass ejections and their interplanetary counterparts and corotating interaction regions are interconnected with solar-terrestrial parameters such as cosmic rays, solar wind, geomagnetic storm, lightning, interplanetary magnetic field, among others. Data selection remains a challenging problem in solar-terrestrial studies. While manual selection of Forbush decreases (FDs) is subjective, automated methods are not widely used within the field. We demonstrate that Forbush events algorithm selection technique is an improvement over the common but inefficient manual method. Additionally, a simple coincident computer program was used to select other solar-terrestrial variables using the FD date as the input data. We used models/tools capable of handling simultaneous multidimensional variables to study the complex interrelationships within the Sun–Earth space. Forbush effects (FEs) selected by the IZMIRAN group was used to validate our results. Fourier transform technique and an R-based algorithm were used to identify FDs from Sanae neutron monitor data. In order to select other solar/geophysical variables, the program-selected FD dates were used as input data for the coincident algorithm. The large number of variables selected were analyzed using principal component analysis and multiple regression models. Several analyses showed that variability in solar-terrestrial parameters happens simultaneously with FDs. We conclude that data fluctuations within the Sun–Earth region might be induced simultaneously by common solar events and should be investigated using multidimensional models.

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