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

A. Malanushenko (HAO/NCAR); G. Chintzoglou (LMSAL); G. H. Fisher (U. of Berkeley); M. C. M. Cheung; M. Dikpati; M. D. Kazachenko (CU/NSO); M. Rempel; T. Y. Chen (Columbia); X. Sun (U. of Hawaii); Y. Fan

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

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arxiv 2212.14384 v1 pith:3EH7LR5X submitted 2022-12-29 astro-ph.IM astro-ph.SRphysics.data-anphysics.space-phstat.CO

M. Rempel , Y. Fan , M. Dikpati , A. Malanushenko (HAO/NCAR) , M. D. Kazachenko (CU/NSO) , M. C. M. Cheung , G. Chintzoglou (LMSAL) , X. Sun (U. of Hawaii)

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G. H. Fisher (U. of Berkeley) T. Y. Chen (Columbia)

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keywords datamodelingpredictionsolaradvancesassimilationatmosphereavailability

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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.

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