Towards a Data-Optimized Coronal Magnetic Field Model (DOC-FM): Statistical Method for Diagnosing the Coronal Magnetic Field

Abstract:

Solar coronal mass ejections (CMEs) and solar flares are the main drivers of space weather. Their potential impact on Earth is determined by the morphology and orientation of the magnetic structure associated with these events and its evolution as it propagates into the interplanetary magnetic field. Knowing the 3D coronal magnetic field prior to the trigger of a CME is therefore one of the key features for predicting their geomagnetic effect. Since the magnetic field is essentially measured at the photosphere, one must rely on reconstruction models to obtain the 3D magnetic field in the corona. Hence, obtaining an accurate model of the real 3D coronal magnetic field is one of the cornerstones for precise Space Weather Forecasting. In this work, we propose a new method for data-constrained reconstruction of the 3D coronal magnetic field. Model-data fitting is achieved by optimizing a user-specified metric, $\mathcal{M}$, quantifying the difference between a dataset (including e.g. polarization, extreme-ultraviolet emission, X-ray emission) and its synthetic analogue. The synthetic data is produced by forward calculations applied to a 3D magnetic model that depends upon a finite set of parameters. After introducing the method, we present its validation on a synthetic test bed consisting of a coronal magnetic flux rope assumed to depend on four parameters, i.e. height in the corona, latitude, longitude, and tilt angle. A specific value of each parameter is used to generate a ground truth and the corresponding synthetic data. We show that, when $\mathcal{M}$ does not possess any degenerate minimum, our method performs well and the best-fit parameters provide a good approximation of the ground-truth parameters. We then show how using additional observations can help in removing any existing degeneracy. Finally, we discuss future plans for validation and application of our method to solar observations.