A New Space Weather Tool for Identifying Eruptive Active Regions

TL;DR

This paper introduces a new real-time operational metric combining observations and simulations to identify eruptive active regions on the Sun, aiding space weather prediction efforts.

Contribution

It presents a novel metric that distinguishes eruptive from non-eruptive active regions using magnetograms and 3D simulations, advancing space weather forecasting capabilities.

Findings

The metric accurately identifies eruptive regions with observable eruption signatures.

Longer magnetogram time series improve the robustness of eruption risk categorization.

The approach enables categorization into high, medium, and low eruption risk levels.

Abstract

One of the main goals of solar physics is the timely identification of eruptive active regions. Space missions such as Solar Orbiter or future Space Weather forecasting missions would largely benefit from this achievement. Our aim is to produce a relatively simple technique that can provide real time indications or predictions that an active region will produce an eruption. We expand on the theoretical work of \citet{Pagano2019fp} that was able to distinguish eruptive from non-eruptive active regions. From this we introduce a new operational metric that uses a combination of observed line-of-sight magnetograms, 3D data-driven simulations and the projection of the 3D simulations forward in time. Results show that the new metric correctly distinguishes active regions as eruptive when observable signatures of eruption have been identified and as non-eruptive when there are no observable signatures of eruption. After successfully distinguishing eruptive from non-eruptive active regions we illustrate how this metric may be used in a "real-time" operational sense were three levels of warning are categorised. These categories are: high risk (red), medium risk (amber) and low risk (green) of eruption. Through considering individual cases we find that the separation into eruptive and non-eruptive active regions is more robust the longer the time series of observed magnetograms used to simulate the build up of magnetic stress and free magnetic energy within the active region. Finally, we conclude that this proof of concept study delivers promising results where the ability to categorise the risk of an eruption is a major achievement.