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

Authors

Simon Wing, Johns Hopkins UniversityFollow
Jay R. Johnson, Andrews UniversityFollow
Enrico Camporeale, Limburg Universitair Centrum
Geoffrey D. Reeves, Los Alamos National Laboratory

Document Type

Contribution to Book

Publication Date

2018

Keywords

Radiation belt, Relativistic electrons, Solar wind drivers, Nonlinear relationships, Information theory, Triangle distribution, Untangling drivers

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 (V_sw) to geosynchronous MeV electron flux (J_e) peaks with a lag time (τ) of 2 days. As previously reported, J_e is anticorrelated with solar wind density (n_sw) with a lag of 1 day. However, this lag time and anticorrelation can be attributed at least partly to the J_e(t + 2 days) correlation with V_sw(t) and n_sw(t + 1 day) anticorrelation with V_sw(t). Analyses of solar wind driving of the magnetosphere need to consider the large lag times, up to 3 days, in the (V_sw, n_sw) anticorrelation. Using CMI to remove the effects of V_sw, the response of J_e to n_sw is 30% smaller and has a lag time of h, suggesting that the MeV electron loss mechanism due to n_sw or solar wind dynamic pressure has to start operating in n_sw transfers about 36% as much information as V_sw (the primary driver) to J_e. 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 J_e(t + 2 days) versus V_sw(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

https://doi.org/10.1016/B978-0-12-811788-0.00006-8

First Department

Engineering

Recommended Citation

Wing, Simon; Johnson, Jay R.; Camporeale, Enrico; and Reeves, Geoffrey D., "Untangling the Solar Wind Drivers of Radiation Belt: An Information Theoretical Approach" (2018). Faculty Publications. 796.
https://digitalcommons.andrews.edu/pubs/796