Magnetic Field-Constrained Ensemble Image Segmentation of Coronal Holes in Chromospheric Observations

TL;DR

This paper introduces STRIDE-CH, a novel ensemble segmentation method that combines chromospheric and magnetic data to improve coronal hole detection in solar observations, aiding space weather prediction.

Contribution

The paper presents a new segmentation approach that integrates chromospheric imagery and magnetic data, addressing challenges in coronal hole identification beyond traditional EUV-based methods.

Findings

Effective disambiguation of CHs from filaments and quiet Sun

Enhanced segmentation accuracy using combined radiative and magnetic properties

Provides confidence maps for CH presence likelihood

Abstract

Coronal Holes (CHs) are large-scale, low-density regions in the solar atmosphere which may expel high-speed solar wind streams that incite hazardous, geomagnetic storms. Coronal and solar wind models can predict these high-speed streams and the performance of the coronal model can be validated against segmented CH boundaries. We present a novel method named Sub-Transition Region Identification of Ensemble Coronal Holes (STRIDE-CH) to address prominent challenges in segmenting CHs with Extreme Ultraviolet (EUV) imagery. Ground-based, chromospheric He I 10830 {\AA} line imagery and underlying Fe I photospheric magnetograms are revisited to disambiguate CHs from filaments and quiet Sun, overcome obscuration by coronal loops, and complement established methods in the community which use space-borne, coronal EUV observations. Classical computer vision techniques are applied to constrain the radiative and magnetic properties of detected CHs, produce an ensemble of boundaries, and compile these boundaries in a confidence map that quantifies the likelihood of CH presence throughout the solar disk. This method is science-enabling towards future studies of CH formation and variability from a mid-atmospheric perspective.