Modeling the Dispersal of an Active Region: Quantifying Energy Input into the Corona

TL;DR

This paper introduces a new method for modeling the evolution of coronal magnetic fields from magnetogram data, revealing how small-scale motions contribute significantly to coronal energy buildup over days.

Contribution

A novel technique for directly modeling non-linear force-free fields from magnetogram sequences, enabling long-term evolution studies of active regions.

Findings

Small-scale motions inject 2.5-3 x 10^{25} erg s^{-1} of free magnetic energy.

Most energy is stored in the low corona below 30 Mm.

Energy buildup over 4 days is about 10% of the potential field energy.

Abstract

In this paper a new technique for modeling non-linear force-free fields directly from line of sight magnetogram observations is presented. The technique uses sequences of magnetograms directly as lower boundary conditions to drive the evolution of coronal magnetic fields between successive force-free equilibria over long periods of time. It is illustrated by applying it to MDI observations of a decaying active region, NOAA AR 8005. The active region is modeled during a 4 day period around its central meridian passage. Over this time, the dispersal of the active region is dominated by random motions due to small scale convective cells. Through studying the build up of magnetic energy in the model, it is found that such small scale motions may inject anywhere from $2.5-3 \times 10^{25}$ erg s$^{-1}$ of free magnetic energy into the coronal field. Most of this energy is stored within the center of the active region in the low corona, below 30 Mm. After 4 days the build-up of free energy is 10% that of the corresponding potential field. This energy buildup, is sufficient to explain the radiative losses at coronal temperatures within the active region. Small scale convective motions therefore play an integral part in the energy balance of the corona. This new technique has wide ranging applications with the new high resolution, high cadence observations from the SDO:HMI and SDO:AIA instruments.