Harnessing time-dependent data-driven modeling to capture the initiation and low-coronal dynamics of coronal mass ejections

Accurate characterization of the magnetic field via modeling is a promising path for advancing our understanding of the formation and dynamics of eruption-prone structures in the corona. While extrapolations provide a snapshot in time of the topology of the low-coronal magnetic field, their value in determining the properties of the magnetic field during eruptions is limited. Time-dependent modelling, on the other hand, has the potential to model the complete evolution of the active-region coronal magnetic fields from emergence to eruption and thereby advance beyond the current paradigm of static extrapolations.

In this work, we present results of our time-dependent simulations of the evolution of active region magnetic fields. The model is driven by the photospheric electric field inverted from a time-sequence of HMI vector magnetograms. Using our experience from modeling several active regions, we discuss the capability of the model to capture the essential dynamics of the eruption. We also focus on how the modeling enables us to characterize the associated coronal mass ejection (CME) by computing quantities such as the magnetic flux and twist of the ejected flux rope. Finally, we discuss recent results of our efforts to extend our modeling to global scales including coronal holes as well as coupling the data-driven model with magnetohydrodynamic simulations in order to capture the dynamics of the erupting CMEs in greater detail.