Predictive Capabilities of Avalanche Models for Solar Flares

TL;DR

This paper evaluates avalanche models for solar flare prediction, showing stochastic models lack predictive power for specific events, while deterministic models can effectively forecast large flares, proposing a new efficient prediction approach.

Contribution

It introduces a novel approach using deterministic avalanche models for predicting large solar flares, overcoming limitations of stochastic models.

Findings

Stochastic avalanche models are unreliable for specific flare predictions.

Deterministically driven models can predict large solar flares effectively.

Proposes a computationally inexpensive method for large flare forecasting.

Abstract

We assess the predictive capabilities of various classes of avalanche models for solar flares. We demonstrate that avalanche models cannot generally be used to predict specific events due to their high sensitivity to their embedded stochastic process. We show that deterministically driven models can nevertheless alleviate this caveat and be efficiently used for large events predictions. Our results promote a new approach for large (typically X-class) solar flares predictions based on simple and computationally inexpensive avalanche models.