| Presentation Title: | Unveiling the uniqueness of solar flare precursors - do pre-event conditions of the upper solar atmosphere differ for flaring vs. non-flaring active regions? |
| Author(s): | Karin Dissauer (1), KD Leka (1,2), Graham Barnes (1), Eric L. Wagner (1)
(1) NorthWest Research Associates, 3380 Mitchell Lane, Boulder, CO 80301, USA
(2) Institute for Space-Earth Environmental Research, Nagoya University, Nagoya, Aichi 464-8601, JAPAN
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Abstract:
Observational case studies of the solar chromosphere and corona reveal increased levels of magnetic reorganization, dynamics, and temperature variation prior to solar energetic events. Here, we investigate whether parameters describing these activities can differentiate a region that will imminently produce a solar flare from one that will not.
We statistically analyze the coronal and chromospheric conditions of active regions prior to solar flares and during flare-quiet periods using a machine-learning ready dataset from the Atmospheric Imaging Assembly (AIA) onboard the Solar Dynamics Observatory (SDO) recently created by NWRA.
The AIA Active-Region Patches dataset (AARPs; Dissauer et al. 2023) comprises targeted extractions of AIA time-series data aligned with HMI active region patches (HARPs), downscaled spatially to active-region size and temporally to 13-minute intervals per hour at a 72-second cadence from 15:48-21:48 UT daily, enabling evaluation of short-lived features and long-term trends of pre-event dynamics and heating of the upper solar atmosphere using moment analysis of brightness images and running-difference images.
Temporal behavior is analyzed using linear regression on 6-hour time-series data for each parameter. The NWRA Classification Infrastructure (NCI), employing Non-Parametric Discriminant Analysis, is applied to over 32,000 samples across four flare-based event definitions to determine significant differences in pre-event conditions between flare-imminent and flare-quiet populations. We find top Brier Skill Scores in the 0.07 – 0.33 range, True Skill Statistics in the 0.68 – 0.82 range (both depending on event definition), and Receiver Operating Characteristic Skill Scores above 0.8.
Total emission can perform notably, although mean brightness measures do not, demonstrating the well-known active-region size/flare productivity relation. Once a region is flare productive, active-region coronal plasma appears to stay hot. The 94 Å filter data provide the most parameters with discriminating power, with indications that it benefits from sampling multiple physical regimes. In particular, classification success using higher-order moments of running-difference images indicates a propensity for flare-imminent regions to display short-lived, small-scale brightening events.
Focusing on small-scale brightening events revealed a clustering tendency at future flare locations, compared to a random appearance of brightenings during flare-quiet epochs. Preliminary results show that these clusters also tend to occur predominantly at strong polarity inversion lines, fan traces of coronal null points, and magnetic bald patch locations.