| Author(s) and Co-Author(s) with Affiliation: Prithish Halder(Department of Physics and Astronomy, Jorgensen Hall, University of Nebraska, Lincoln, NE 68588, USA), Sudheer K. Mishra(Astronomical Observatory, Kyoto University, Sakyo, Kyoto 606-8502, Japan), Abhishekh K. Srivastava(Department of Physics, Indian Institute of Technology (BHU), Varanasi-221005, India), Ayumi Asai(Astronomical Observatory, Kyoto University, Sakyo, Kyoto 606-8502, Japan), Manik Sharma(Department of Physics, Indian Institute of Technology (BHU), Varanasi-221005, India), Peter A. Dowben(Department of Physics and Astronomy, Jorgensen Hall, University of Nebraska, Lincoln, NE 68588, USA) |
| Abstract: The accurate prediction of extreme solar flares relies on interpretative diagnostics that reflect the changing magnetic topology of active regions, beyond static complexity metrics. This study presents an in-depth spatiotemporal analysis of magnetic topology in the two most flare-productive active regions of Solar Cycle 25, NOAA AR 13664 and AR 13842, which generated multiple X-class and significant M-class flares. Using SDO/HMI vector magnetograms and EUV data from SDO/AIA, we analyze how magnetic helicity, winding flux, and polarity inversion line (PIL) features evolve from pre- to post-flare temporal ranges. We find that the magnetic winding flux exhibits systematic, localized increases during the flare precursor stage, whereas the helicity flux remains diffused. These winding increases are consistently near pre-existing or emerging flux-rope structures and appear minutes to hours before flares. Building on this, we propose a new winding-flux-based masked PIL framework that isolates stable and recurrent PIL structures linked to strong flaring activity. By tracking these masked PILs and the gradient of their intense segments, we identify localized regions that appear 3–7 hours before flare ignition and reliably locate flare trigger sites, even amid rapid magnetic reconfiguration following multiple eruptions. This approach is effective for recurring X-class flares, a regime where many existing forecasting methods struggle to perform. Our results demonstrate that magnetic winding and winding-based masked PIL metrics are robust and reliable early indicators of extreme solar flares. They offer a pathway to incorporate topological diagnostics into advanced physics-driven flare prediction and machine learning models, with significant implications for operational space-weather forecasting. |
