Which Upstream Solar Wind Conditions Matter Most in Predicting Bz within Coronal Mass Ejections

• Published in: arXiv.org
• Main Authors: Riley, Pete, Reiss, M A, Mostl, C
• Format: Paper Journal Article
• Language: English
• Published: Ithaca Cornell University Library, arXiv.org 30.03.2023
• Subjects: Compressive strength; Coronal mass ejection; Density; Field strength; Interplanetary magnetic field; Kinetic energy; Machine learning; Magnetic fields; Physics - Solar and Stellar Astrophysics; Physics - Space Physics; Sheaths; Solar wind; Upstream
• ISSN: 2331-8422
• DOI: 10.48550/arxiv.2303.17682

Accurately predicting the z-component of the interplanetary magnetic field, particularly during the passage of an interplanetary coronal mass ejection (ICME), is a crucial objective for space weather predictions. Currently, only a handful of techniques have been proposed and they remain limited in scope and accuracy. Recently, a robust machine learning (ML) technique was developed for predicting the minimum value of Bz within ICMEs based on a set of 42 'features', that is, variables calculated from measured quantities upstream of the ICME and within its sheath region. In this study, we investigate these so-called explanatory variables in more detail, focusing on those that were (1) statistically significant; and (2) most important. We find that number density and magnetic field strength accounted for a large proportion of the variability. These features capture the degree to which the ICME compresses the ambient solar wind ahead. Intuitively, this makes sense: Energy made available to CMEs as they erupt is partitioned into magnetic and kinetic energy. Thus, more powerful CMEs are launched with larger flux-rope fields (larger Bz), at greater speeds, resulting in more sheath compression (increased number density and total field strength).