Solar Imaging Data Analytics: A Selective Overview of Challenges and Opportunities
Yang Chen, Ward Manchester, Meng Jin, Alexei Pevtsov

TL;DR
This paper provides an overview of solar imaging data challenges and opportunities, highlighting data-driven methods for solar eruption prediction, available resources, and future research directions.
Contribution
It offers a comprehensive summary of current solar eruption forecasting models, data products, and discusses promising statistical and computational research avenues.
Findings
Summarizes state-of-the-art solar eruption forecasting models.
Describes available solar imaging data products and software.
Identifies promising future research directions in statistical modeling.
Abstract
We give a gentle introduction to solar imaging data, focusing on the challenges and opportunities of data-driven approaches for solar eruptions. The various solar phenomenon prediction problems that might benefit from statistical methods are presented. Available data products and software are described. State-of-the-art solar eruption forecasting models with data-driven approaches are summarized and discussed. Based on the characteristics of the datasets and state-of-the-art approaches, we point out several promising directions to explore from statistical modeling and computational perspectives.
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Taxonomy
TopicsSolar Radiation and Photovoltaics
