Geoeffectiveness of Coronal Mass Ejections in the SOHO era

TL;DR

This study develops a probabilistic forecasting model for geomagnetic storm intensity based on CME and solar flare parameters, quantifying their relationships to improve space weather prediction accuracy.

Contribution

It introduces an empirical statistical model that predicts geomagnetic storm severity using remote solar observations, incorporating effects of CME properties and successive events.

Findings

Initial CME speed and width are key predictors.

Source position and flare class significantly influence storm probability.

Successive CMEs alter the likelihood of intense geomagnetic storms.

Abstract

The main objective of the study is to determine the probability distributions of the geomagnetic Dst index as a function of the coronal mass ejection (CME) and solar flare parameters for the purpose of establishing a probabilistic forecast tool for the geomagnetic storm intensity. Several CME and flare parameters as well as the effect of successive-CME occurrence in changing the probability for a certain range of Dst index values, were examined. The results confirm some of already known relationships between remotely-observed properties of solar eruptive events and geomagnetic storms, namely the importance of initial CME speed, apparent width, source position, and the associated solar flare class. In this paper we quantify these relationships in a form to be used for space weather forecasting in future. The results of the statistical study are employed to construct an empirical statistical model for predicting the probability of the geomagnetic storm intensity based on remote solar observations of CMEs and flares.