arXiv subjects

Shea Hess Webber

Publications and source records attributed to Shea Hess Webber.

3 recordsLinked to original sources

arXiv2026

A Probabilistic Framework for Incorporating Helioseismic Far-Side Active Regions into SFT Models

Surface Flux Transport (SFT) models are routinely used to model the Sun's photospheric magnetic field and provide inner boundary conditions for coronal and heliospheric models, yet they remain fundamentally limited by the lack of direct information about flux emergence on the far side of the Sun. To address this, we develop a framework for incorporating helioseismic images of far-side active regions (HIFAR), into the Advective Flux Transport (AFT) model. Using near-simultaneous magnetic flux maps (HIFARM) inferred from HIFAR, and STEREO/EUVI 304 A observations from 2010 May 13 to 2014 August 18, we develop a logistic regression model to estimate the probability that a helioseismic detection corresponds to an AR based on descriptors of magnetic flux, field strength, and location. The model achieves a precision of 0.93 for active region (AR) detections at a probability threshold of 0.73, selected to reject 90% of "ghost" ARs. We also derive an empirical scaling relationship between HIFARM and AFT flux to place HIFARM on the AFT flux scale and demonstrate that the framework reproduces the flux evolution of ARs consistent with near-side observations over multiple solar rotations. At the global scale, we find that conventional near-side-driven AFT simulations underestimate the total unsigned magnetic flux by ~10-20% of the Sun's total magnetic flux budget. The probabilistic AR detection model and the complete framework developed in this work provide a practical pathway for incorporating helioseismic far-side ARs into SFT models, a step toward realistic modeling of full-Sun magnetic field.

astro-ph.SR↗

arXiv2022

Inferring Maps of the Sun's Far-side Unsigned Magnetic Flux from Far-side Helioseismic Images using Machine Learning Techniques

Accurate modeling of the Sun's coronal magnetic field and solar wind structures require inputs of the solar global magnetic field, including both the near and far sides, but the Sun's far-side magnetic field cannot be directly observed. However, the Sun's far-side active regions are routinely monitored by helioseismic imaging methods, which only require continuous near-side observations. It is therefore both feasible and useful to estimate the far-side magnetic-flux maps using the far-side helioseismic images despite their relatively low spatial resolution and large uncertainties. In this work, we train two machine-learning models to achieve this goal. The first machine-learning training pairs simultaneous SDO/HMI-observed magnetic-flux maps and SDO/AIA-observed EUV 304$Å$ images, and the resulting model can convert 304$Å$ images into magnetic-flux maps. This model is then applied on the STEREO/EUVI-observed far-side 304$Å$ images, available for about 4.3 years, for the far-side magnetic-flux maps. These EUV-converted magnetic-flux maps are then paired with simultaneous far-side helioseismic images for a second machine-learning training, and the resulting model can convert far-side helioseismic images into magnetic-flux maps. These helioseismically derived far-side magnetic-flux maps, despite their limitations in spatial resolution and accuracy, can be routinely available on a daily basis, providing useful magnetic information on the Sun's far side using only the near-side observations.

astro-ph.SR↗

arXiv2019

Imaging the Sun's Far-Side Active Regions by Applying Multiple Measurement Schemes on Multi-Skip Acoustic Waves

Being able to image active regions on the Sun's far side is useful for modeling the global-scale magnetic field around the Sun, and for predicting the arrival of major active regions that rotate around the limb onto the near side. Helioseismic methods have already been developed to image the Sun's far-side active regions using near-side high-cadence Doppler-velocity observations; however, the existing methods primarily explore the 3-, 4-, and 5-skip helioseismic waves, leaving room for further improvement in the imaging quality by including waves with more multi-skip waves. Taking advantage of the facts that 6-skip waves have the same target-annuli geometry as 3- and 4-skip waves, and that 8-skip waves have the same target-annuli geometry as 4-skip waves, we further develop a time--distance helioseismic code to include a total of 14 sets of measurement schemes. We then apply the new code on the SDO/HMI-observed Dopplergrams, and find that the new code provides substantial improvements over the existing codes in mapping newly-emerged active regions and active regions near both far-side limbs. Comparing 3 months of far-side helioseismic images with the STEREO/EUVI-observed 304A images, we find that 97.3% of the helioseismically detected far-side active regions that are larger than a certain size correspond to an observed region with strong EUV brightening. The high reliability of the new imaging tool will potentially allow us to further calibrate the far-side helioseismic images into maps of magnetic flux.

astro-ph.SR↗