An Evolution and Eruption of the Coronal Magnetic Field through a Data-driven MHD Simulation

• Published in: The Astrophysical journal Vol. 946; no. 1; pp. 46 - 72
• Main Authors: Inoue, Satoshi, Hayashi, Keiji, Miyoshi, Takahiro
• Format: Journal Article
• Language: English
• Published: Philadelphia The American Astronomical Society 01.03.2023; IOP Publishing
• Subjects: Astrophysics; Corona; Coronal magnetic fields; Electric fields; Magnetic fields; Magnetic flux; Magnetohydrodynamical simulations; Magnetohydrodynamics; Numerical methods; Photosphere; Photospheric magnetic fields; Simulation; Solar active region magnetic fields; Solar corona; Solar coronal mass ejections; Solar flares; Solar magnetic field; Sunspots
• ISSN: 0004-637X; 1538-4357
• DOI: 10.3847/1538-4357/ac9eaa

We present a newly developed data-driven magnetohydrodynamics (MHD) simulation code under a zero- β approximation based on a method proposed by Hayashi et al. 2018 and 2019. Although many data-driven MHD simulations have been developed and conducted, there are not many studies on how accurately those simulations can reproduce the phenomena observed in the solar corona. In this study, we investigated the performance of our data-driven simulation quantitatively using ground-truth data. The ground-truth data was produced by an MHD simulation in which the magnetic field is twisted by the sunspot motions. A magnetic flux rope (MFR) is created by the cancellation of the magnetic flux at the polarity inversion line due to the converging flow on the sunspot, which eventually leads to the eruption of the MFR. We attempted to reproduce these dynamics using the data-driven MHD simulation. The coronal magnetic fields are driven by the electric fields, which are obtained from a time series of the photospheric magnetic field that is extracted from the ground-truth data, on the surface. As a result, the data-driven simulation could capture the subsequent MHD processes, the twisted coronal magnetic field and formation of the MFR, and also its eruption. We report these results and compare them with the ground-truth data, and discuss how to improve the accuracy and optimize the numerical method.