Validating Coronal Magnetic Field Models Using Gaussian Separation

TL;DR

This study evaluates the accuracy of NLFFF coronal magnetic field models using Gaussian separation to compare model currents with observed vector magnetogram data, highlighting differences in flux rope signatures.

Contribution

It introduces Gaussian separation as a new validation method for NLFFF models, comparing two modeling approaches on active region AR 11429.

Findings

Both models reproduce coronal current signatures along the main PIL.

CFIT model significantly alters flux rope signatures and footpoints.

Differences are due to boundary data modifications and model assumptions.

Abstract

Nonlinear Force-free Field (NLFFF) models are widely used to investigate coronal magnetic field structure in solar active regions, but methods to validate them remain limited. Here, we use Gaussian separation, recently applied to solar vector magnetogram data, to assess the accuracy of NLFFF models constructed with two methods: optimization and the current-field iteration (CFIT) implementation of the Grad-Rubin method. Gaussian separation partitions the photospheric vector magnetic field into three components associated with currents flowing below, above, and passing through the photosphere, respectively. Comparing the photospheric field components due to coronal currents in an NLFFF model with those in the original vector magnetogram data provides a check on the accuracy of the model's coronal currents. We consider NLFFF models constructed for the active region AR 11429. The photospheric signatures of coronal currents in both the models and the vector magnetogram data indicate currents flowing above and parallel to central, sheared polarity inversion lines (PILs), consistent with other recent studies. We find that while both models reproduce the coronal current signatures along the upper section of the main PIL, the CFIT model significantly alters the signature of a flux rope along the lower section of the PIL, including shifting its positive-polarity footpoint. These differences arise from modifications to the vector magnetogram boundary data when solving the NLFFF equations, and from the assumptions underlying the models. We propose Gaussian separation as a useful tool to validate coronal magnetic field models, in addition to existing methods.