Presentation #127.13 in the session “Solar Physics Division (SPD): Flares”.
Although solar energetic events are powered by the evolution of the underlying magnetic field, it is still impossible to deterministically predict when an active region will flare or not solely based on this information. Observational case studies of the solar chromosphere and corona reveal increased levels of magnetic reorganization, dynamics and temperature variation prior to solar energetic events, however whether these activities play a role in event initiation is still unclear.
In order to investigate this question, we statistically analyze the coronal and chromospheric conditions prior to solar flares and during flare-quiet periods using data from the Atmospheric Imaging Assembly (AIA) onboard the Solar Dynamics Observatory (SDO).
We create and use AIA Active Region Patches (AARPs), region-targeted extractions of AIA time-series data in (extreme-) ultraviolet, matched to the HMI Active Region Patches (HARPs), for 2010-2018. The pre-event dynamics and heating of the upper solar atmosphere is characterized using high-order moments to parameterize brightness images, running-difference images as well as emission measure, temperature, and density images, derived from Differential Emission Measure (DEM) analysis. The temporal behavior is captured by the slope and intercept of a linear fit over a 7hr time-series of each parameter.
The NWRA Classification Infrastructure (NCI), a well-established statistical classifier system based on Non-Parametric Discriminant Analysis, and standard skill scores are used to statistically evaluate if parameters describing the pre-event conditions significantly differ for flaring-imminent vs. flare-quiet populations. Early results and their physical implications will be presented.
We note that AARPs present a newly developed AIA data product which will be freely available to the scientific community later in 2021. AARPs are presently constructed daily, from 15:48-21:48 UT in 13 min intervals each hour with a time cadence of 72 s, suitable for DEM Analysis. AARPs will be available with the study’s publication and at www.nwra.com/AARP