Information Theory Analysis of the Solar Wind Magnetic Structures for Space Weather Prediction

Author

• Katherine Holland, Embry-Riddle Aeronautical UniversityFollow

ORCID Number

0009-0000-9153-9287

Date of Award

Spring 2026

Access Type

Dissertation - Open Access

Degree Name

Doctor of Philosophy in Engineering Physics

Department

Physical Sciences

Committee Chair

Katariina Nykyri

Committee Chair Email

nykyrik@erau.edu

First Committee Member

Xuanye Ma

First Committee Member Email

max@erau.edu

Second Committee Member

Matthew Zettergren

Second Committee Member Email

zettergm@erau.edu

Third Committee Member

Simon Wing

Third Committee Member Email

Simon.Wing@jhuapl.edu

College Dean

Jayathi Raghavan

Abstract

Forecasting space weather at Earth is highly complicated, because of the limited measurements of the dynamic processes in the Sun that span multiple temporal, spatial, and energy-scales. The solar wind is a highly structured, multi-scale, evolving plasma and consists of coronal mass ejections (CMEs), stream interaction regions (SIRs), expanding flux tubes (Borovsky, 2008), and interplanetary magnetic field (IMF) discontinuities and fluctuations. The aim of this research is to improve our understanding of the evolution and dissipation of different scale-size solar wind magnetic structures as they move from the Sun-Earth Lagrange point 1 (L1) to Earth's bow shock and, ultimately, to improve space weather forecasting.

In this paper, we use two years of data in the solar wind from the Advanced Composition Explorer (ACE) and Wind spacecraft, which orbit the Sun-Earth Lagrange L1 point, the Acceleration, Reconnection, Turbulence and Electrodynamics of the Moon's Interaction with the Sun (ARTEMIS) spacecraft, which orbit the moon, and the Magnetospheric Multiscale (MMS) spacecraft upstream of the Earth's bow shock to study the structure of the IMF. In the first analysis, we determine the lag times of IMF structures and their dependence on spacecraft positions by conducting an information theory analysis and comparing it with two traditional analysis methods: cross-correlation (CC) analysis and minimum variance of magnetic field analysis (MVAB). For the events with long time intervals (i.e., greater than four hours) and with small spatial separation between the MMS and ARTEMIS along the y_GSM direction (i.e., less than 40 Re, where Re is the Earth's radius), the lag times based on the CC and the mutual information (MI) analyses statistically agree with each other, with p-values of 1.675 x 10^-7 and 4.833 x 10^-9, with the confidence greater than 99%. Both the results based on the MI and CC analyses have a large deviation from the results from MVAB. For some of the events, such a deviation could be improved by taking the fast mode speed into account; however, p-tests showed that they were not statistically significant to the 95% confidence level.

In the second analysis, we analyzed the evolution and dissipation of different scale-size solar wind magnetic structures as they move from L1 to Earth's bow shock. Wavelet transforms of the magnetic field data were calculated for each spacecraft, and length scale wavelet transforms were calculated by dividing the absolute value of the ion velocity by the frequency. Six frequencies were selected (48 mHz, 17 mHz, 7.9 mHz, 5.2 mHz, 3 mHz, and 1.5 mHz), and time vectors of the powers for each frequency and corresponding length scale were used in the MI and CC analyses. Mutual information and cross correlation coefficients were calculated from wavelet transformations of both the Bx and Bz data for each length scale and each spacecraft combination. The results were compared to the minimum variance analysis (MVA) and the MVA with the fast mode speed added.

One event that gave good agreement between each of the three analyses was presented. For this event, MI and CC were plotted against lag time for each spacecraft combination, length scale, and coordinate of magnetic field used in the analysis. In the analysis of all 189 events, it was shown that many MI peaks exceeded three standard deviations above the mean, which were deemed significant with a confidence level greater than 99%. These lag times were collected and plotted in histograms, showing which length scales, spacecraft combinations, and magnetic field component used in the analysis, yielded which lag times and how many.

It was shown that only the long duration events had mutual information peaks three standard deviations above the mean for larger length scale scenarios. Therefore, the longer the event duration, the larger the length scale it was able to detect. Also, there was an obvious trend where higher length scale scenarios yielded higher MI values. However, the larger length scale scenarios had much fewer MI peaks above three standard deviations above the mean.

Solar wind parameters were also analyzed to determine whether there was any dependence on solar wind parameters and dissipation of the solar wind structures as they moved from L1, to the Moon, to Earth's bow shock. It was found that the ion speed, sound speed, Alfvén speed, and the fast mode speed had a correlation with the calculated lag time. There were also weak correlations of total magnetic field, average temperature, and density with calculated lag time. The correlation of plasma beta with mutual information or lag time could not be determined.

These analyses demonstrate that Information Theory analysis is useful for space weather prediction. Although it is susceptible to periodicities and solar wind discontinuities such as two spacecraft located in separate flux tubes, it is shown to be a better method than cross correlation and minimum variance analysis because it can take into account nonlinear correlations.

Scholarly Commons Citation

Holland, Katherine, "Information Theory Analysis of the Solar Wind Magnetic Structures for Space Weather Prediction" (2026). Doctoral Dissertations and Master's Theses. 971.
https://commons.erau.edu/edt/971