The characteristics of flare- and CME-productive solar active regions

TL;DR

This paper reviews the magnetic characteristics of solar active regions that produce flares and CMEs, discusses current prediction challenges, and highlights new parameters and data sources that could improve forecasting accuracy.

Contribution

It provides a comprehensive overview of recent advances in identifying magnetic and dynamic properties of active regions related to flare and CME production, emphasizing new predictors and observational techniques.

Findings

Common magnetic features in flare- and CME-productive regions

Challenges in magnetic field measurement and prediction

Emerging parameters from flow fields and spectral data

Abstract

Solar flares and coronal mass ejections (CMEs) cause immediate and adverse effects on the interplanetary space and geospace. The deeper understanding of the mechanisms that produce them and the construction of efficient prediction schemes are of paramount importance. The source regions of flares and CMEs exhibit some common morphological characteristics associated with strongly sheared magnetic polarity inversion lines, indicative of the complex magnetic configurations that store huge amounts of free magnetic energy and helicity. This knowledge is transformed into parameters that can help us distinguish efficiently between quiet, flare-, and CME-productive active regions. Nonetheless, flare and CME prediction still faces a number of challenges. The magnetic field information is constrained at the photosphere and accessed only from one vantage point of observation; the dynamic behavior of active regions is still not fully incorporated into predictions; the stochasticity of flares and CMEs renders their prediction probabilistic. To meet these challenges, new properties have been put forward to describe different aspects of magnetic energy storage mechanisms in active regions and offer the opportunity of parametric studies for over an entire solar cycle. This inventory of predictors now includes information from flow fields, transition region/coronal spectroscopy, data-driven modeling of the coronal magnetic field, as well as parameterizations of dynamic effects from time series. Further work towards these directions may help alleviate the current limitations in observing the magnetic field of higher atmospheric layers. This paper reviews these efforts as well as the importance of transforming new knowledge into more efficient predictors and including new types of data.