Combined Surface Flux Transport and Helioseismic Far-Side Active Region Model (FARM)

Area of Science:

• Solar Physics
• Helioseismology
• Space Weather

Background:

• Surface magnetic field maps are crucial for space-weather modeling but lack far-side observations.
• Surface flux transport (SFT) models estimate magnetic field evolution but are limited by observational gaps.
• Helioseismology offers a potential solution by imaging the Sun's far side using acoustic oscillations.

Purpose of the Study:

• To develop a novel approach for estimating far-side active region magnetic fields using helioseismic data.
• To integrate these far-side magnetic field estimates into an SFT model for improved space-weather predictions.
• To validate the accuracy of the new model by comparing its outputs with observational data.

Main Methods:

• A surface flux transport (SFT) model was calibrated using Earth-facing magnetograms from the Helioseismic and Magnetic Imager (HMI) on SDO.
• Helioseismic phase maps of the Sun's far side were computed using helioseismic holography.
• The conversion from helioseismic signals to magnetic field strengths was established, incorporating Hale's law for polarity assignment and flux balance.

Main Results:

• The study modeled 859 active regions from 2010 to 2024, revealing spatial correlations between magnetic fields and helioseismic phase shifts.
• Inclusion of far-side active regions increased the total unsigned magnetogram flux by an average of [value] (up to [value]).
• Comparisons with EUV observations showed substantial improvement in modeled open-field areas when far-side data was incorporated.

Conclusions:

• The combined surface flux transport and helioseismic Far-side Active Region Model (FARM) is a viable proof of concept.
• This approach significantly enhances the accuracy of solar magnetic field mapping, particularly for the Sun's far side.
• The improved magnetic field maps provide a substantial benefit for more accurate space-weather forecasting.