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arXiv · 2306.15019

The Automatic Identification and Tracking of Coronal Flux Ropes -- Part I: Footpoints and Fluxes

Abstract

Investigating the early-stage evolution of an erupting flux rope from the Sun is important to understand the mechanisms of how it looses its stability and its space weather impacts. Our aim is to develop an efficient scheme for tracking the early dynamics of erupting solar flux ropes and use the algorithm to analyse its early-stage properties. The algorithm is tested on a data-driven simulation of an eruption that took place in active region AR12473. We investigate the modelled flux rope's footpoint movement and magnetic flux evolution and compare with observational data from the Solar Dynamics Observatory's Atmospheric Imaging Assembly in the 211 $\unicode{x212B}$ and 1600 $\unicode{x212B}$ channels. To carry out our analysis, we use the time-dependent data-driven magnetofrictional model (TMFM). We also perform another modelling run, where we stop the driving of the TMFM midway through the flux rope's rise through the simulation domain and evolve it instead with a zero-beta magnetohydrodynamic (MHD) approach. The developed algorithm successfully extracts a flux rope and its ascend through the simulation domain. We find that the movement of the modelled flux rope footpoints showcases similar trends in both TMFM and relaxation MHD run: they recede from their respective central location as the eruption progresses and the positive polarity footpoint region exhibits a more dynamic behaviour. The ultraviolet brightenings and extreme ultraviolet dimmings agree well with the models in terms of their dynamics. According to our modelling results, the toroidal magnetic flux in the flux rope first rises and then decreases. In our observational analysis, we capture the descending phase of toroidal flux. In conclusion, the extraction algorithm enables us to effectively study the flux rope's early dynamics and derive some of its key properties such as footpoint movement and toroidal magnetic flux.

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BibTeXRIS

Andreas Wagner, Emilia K. J. Kilpua, Ranadeep Sarkar, Daniel J. Price, Anshu Kumari, Farhad Daei, Jens Pomoell, Stefaan Poedts. 2023-06-26. The Automatic Identification and Tracking of Coronal Flux Ropes -- Part I: Footpoints and Fluxes. https://doi.org/10.1051/0004-6361%2F202346260

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