Title

Untangling the Solar Wind Drivers of Radiation Belt: An Information Theoretical Approach

Document Type

Contribution to Book

Publication Date

2018

Abstract

The solar wind-magnetosphere system is nonlinear. The solar wind drivers of geosynchronous electrons with an energy range of 1.8–3.5 MeV are investigated using mutual information (MI), conditional mutual information (CMI), and transfer entropy (TE). These information theoretical tools can establish linear and nonlinear relationships, as well as information transfer. The information transfer from solar wind velocity (Vsw) to geosynchronous MeV electron flux (Je) peaks with a lag time (τ) of 2 days. As previously reported, Je is anticorrelated with solar wind density (nsw) with a lag of 1 day. However, this lag time and anticorrelation can be attributed at least partly to the Je(t + 2 days) correlation with Vsw(t) and nsw(t + 1 day) anticorrelation with Vsw(t). Analyses of solar wind driving of the magnetosphere need to consider the large lag times, up to 3 days, in the (Vsw, nsw) anticorrelation. Using CMI to remove the effects of Vsw, the response of Je to nsw is 30% smaller and has a lag time of h, suggesting that the MeV electron loss mechanism due to nsw or solar wind dynamic pressure has to start operating in nsw transfers about 36% as much information as Vsw (the primary driver) to Je. Nonstationarity in the system dynamics is investigated using windowed TE. When the data is ordered according to high or low TE, it is possible to understand details of the triangle distribution that has been identified between Je(t + 2 days) versus Vsw(t).

First Page

150

Last Page

176

Book Title

Machine Learning Techniques for Space Weather

Editor

Camporeale, Enrico, Simon Wing, and Jay Johnson

Publisher

Elsevier

City

Cambridge, MA

Edition

1st

ISBN

9780128117880

DOI

10.1016/B978-0-12-811788-0.00006-8

First Department

Engineering and Computer Science

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