We present a method of conducting data-driven simulations of solar active regions and flux emergence with the MURaM radiative magnetohydrodynamics (MHD) code. The horizontal electric field that is derived from the full velocity and magnetic vectors is implemented at the photospheric (bottom) boundary to drive the induction equation. The energy equation accounts for thermal conduction along magnetic fields, optically thin radiative loss, and heating of coronal plasma by viscous and resistive dissipation, which allows for a realistic presentation of the thermodynamic properties of coronal plasma that are key to predicting the observational features of solar active regions and eruptions. To validate this method, the photospheric data from a comprehensive radiative MHD simulation of solar eruption (the ground truth) are used to drive a series of numerical experiments. The data-driven simulation reproduces the accumulation of free magnetic energy over the course of flux emergence in the ground truth with an error of 3%. The onset time is approximately 8 minutes delayed compared to the ground truth. However, a precursor-like signature can be identified at the correct onset time. The data-driven simulation captures key eruption-related emission features and plasma dynamics of the ground truth flare over a wide temperature span, from
Poynting flux is the flux of magnetic energy, which is responsible for chromospheric and coronal heating in the solar atmosphere. It is defined as a cross product of the electric and magnetic fields, and in ideal MHD conditions it can be expressed in terms of the magnetic field and plasma velocity. Poynting flux has been computed for active regions and plages, but estimating it in the quiet Sun (QS) remains challenging due to resolution effects and polarimetric noise. However, with the upcoming DKIST capabilities, such estimations will become more feasible than ever before. Here, we study QS Poynting flux in SUNRISE/IMaX observations and MURaM simulations. We explore two methods for inferring transverse velocities from observations—FLCT and a neural network–based method DeepVel—and show DeepVel to be the more suitable method in the context of small-scale QS flows. We investigate the effect of azimuthal ambiguity on Poynting flux estimates, and we describe a new method for azimuth disambiguation. Finally, we use two methods for obtaining the electric field. The first method relies on an idealized Ohm’s law, whereas the second is a state-of-the-art inductive electric field inversion method PDFI_SS. We compare the resulting Poynting flux values with theoretical estimates for chromospheric and coronal energy losses and find that some of the Poynting flux estimates are sufficient to match the losses. Using MURaM simulations, we show that photospheric Poynting fluxes vary significantly with optical depth, and that there is an observational bias that results in underestimated Poynting fluxes due to an unaccounted shear term contribution.
more » « less- NSF-PAR ID:
- 10468384
- Publisher / Repository:
- DOI PREFIX: 10.3847
- Date Published:
- Journal Name:
- The Astrophysical Journal
- Volume:
- 956
- Issue:
- 2
- ISSN:
- 0004-637X
- Format(s):
- Medium: X Size: Article No. 83
- Size(s):
- ["Article No. 83"]
- Sponsoring Org:
- National Science Foundation
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