Magnetic cloud prediction model for forecasting space weather relevant properties of Earth-directed coronal mass ejections

¹ Department of Physics, University of Helsinki, PO Box 64 00014 Helsinki, Finland
e-mail: sanchita.pal@helsinki.fi
² Center of Excellence in Space Sciences India, Indian Institute of Science Education and Research Kolkata, Mohanpur, 741246 West Bengal, India
³ Department of Physical Sciences, Indian Institute of Science Education and Research Kolkata, Mohanpur, 741246 West Bengal, India

Received: 10 March 2022
Accepted: 2 June 2022

Abstract

Context. Coronal mass ejections (CMEs) are major eruptive events on the Sun that result in the ejection of large-scale magnetic clouds (MCs) in interplanetary space, consisting of plasma with enhanced magnetic fields whose direction changes coherently when measured in situ. The severity of CME-induced geomagnetic perturbations and space weather impacts depends on the direction and strength of the interplanetary magnetic field (IMF), as well as on the speed and duration of the passage of the magnetic cloud associated with the storm. The coupling between the heliospheric environment and Earth’s magnetosphere is strongest when the IMF direction is persistently southward (i.e. negative B_z) for a prolonged period. Predicting the magnetic profile of such Earth-directed CMEs is therefore critical for estimating their space weather consequences; this remains an outstanding challenge, however.

Aims. Our aim is to build upon and integrate diverse techniques towards the development of a comprehensive magnetic cloud prediction (MCP) model that can forecast the magnetic field vectors, Earth-impact time, speed, and duration of passage of solar storms.

Methods. The configuration of a CME is approximated as a radially expanding force-free cylindrical structure. Combining near-Sun geometrical, magnetic, and kinematic properties of CMEs with the probabilistic drag-based model and cylindrical force-free model, we propose a method for predicting the Earth-arrival time, propagation speed, and magnetic vectors of MCs during their passage through 1 AU. Our model is able to predict the passage duration of the storm without recourse to computationally intensive time-dependent dynamical equations.

Results. Our method is validated by comparing the MCP model output with observations of ten MCs at 1 AU. In our sample, we find that eight MCs show a root mean square (rms) deviation smaller than 0.1 between the predicted and observed magnetic profiles, and the passage durations of seven MCs fall within the predicted range.

Conclusions. Based on the success of this approach, we conclude that predicting the near-Earth properties of MCs based on an analysis and modelling of near-Sun CME observations is a viable endeavour with potential applications for the development of early-warning systems for space weather and enabling mitigation strategies.