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

TL;DR

This paper presents a new magnetic cloud prediction model that forecasts key properties of Earth-directed CMEs, improving space weather prediction by accurately estimating magnetic profiles and storm durations without intensive computations.

Contribution

The novel MCP model integrates diverse techniques to predict magnetic field vectors, impact timing, and storm duration efficiently, validated against real observations of ten MCs at 1 AU.

Findings

Eight MCs had a root mean square deviation of less than 0.1 in magnetic profile predictions.

Seven MCs' passage durations were accurately predicted within the model's range.

The approach demonstrates viability for space weather forecasting based on near-Sun CME analysis.

Abstract

Coronal Mass Ejections (CMEs) are energetic storms in the Sun that result in the ejection of large-scale magnetic clouds (MCs) in interplanetary space that contain enhanced magnetic fields with coherently changing field direction. The severity of geomagnetic perturbations depends on the direction and strength of the interplanetary magnetic field (IMF), as well as the speed and duration of passage of the storm. The coupling between the heliospheric environment and Earth's magnetosphere is the strongest when the IMF direction is persistently southward for a prolonged period. Predicting the magnetic profile of such Earth-directed CMEs is crucial for estimating their geomagnetic impact. We aim to build upon and integrate diverse techniques towards 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. A novelty of our scheme is the ability to predict the passage duration of the storm without recourse to computationally intensive, time-dependent dynamical equations. Our methodology 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 deviation of less than 0.1 between predicted and observed magnetic profiles and the passage duration of seven MCs fall within the predicted range. Based on the success of this approach, we conclude that predicting the near-Earth properties of MCs based on analysis and modelling of near-Sun CME observations is a viable endeavor with potential benefits for space weather assessment.