Towards data-driven modeling and real-time prediction of solar flares and coronal mass ejections

TL;DR

This paper discusses the development of data-driven models and real-time prediction methods for solar flares and coronal mass ejections, aiming to improve space weather forecasting akin to terrestrial weather prediction.

Contribution

It outlines necessary advancements in model complexity, data access, and data assimilation techniques to enable accurate statistical forecasting of solar transient events.

Findings

Identifies key elements for solar event prediction

Proposes a framework similar to Earth weather forecasting

Highlights the need for improved data and modeling methods

Abstract

Modeling of transient events in the solar atmosphere requires the confluence of 3 critical elements: (1) model sophistication, (2) data availability, and (3) data assimilation. This white paper describes required advances that will enable statistical flare and CME forecasting (e.g. eruption probability and timing, estimation of strength, and CME details, such as speed and magnetic field orientation) similar to weather prediction on Earth.