Data-driven coronal evolutionary model of active region 11944.

Abstract:

Recent availability of systematic measurements of vector magnetic fields and Doppler velocities has allowed us to utilize a data-driven approach for modeling observed active regions (AR), a crucial step for understanding the nature of solar flare initiation. We use a sequence of vector magnetograms and Dopplergrams from the Helioseismic and Magnetic Imager (HMI) aboard the SDO to drive magnetofrictional (MF) model of the coronal magnetic field in the the vicinity of AR 11944, where an X1.2 flare on January 7 2014 occurred. To drive the coronal field we impose a time-dependent boundary condition based on temporal sequences of magnetic and electric fields at the bottom of the computational domain, i.e. the photosphere. To derive the electric fields we use a recently improved poloidal-toroidal decomposition (PTD), which we call the ``PTD-Doppler-FLCT-Ideal'' or PDFI technique. We investigate the results of the simulated coronal evolution, compare those with EUV observations from Atmospheric Imaging Assembly (AIA) and discuss what we could learn from them. This work is a a collaborative effort from the UC Berkeley Space Sciences Laboratory (SSL), Stanford University, and Lockheed-Martin and is a part of Coronal Global Evolutionary (CGEM) Model, funded jointly by NASA and NSF.