On the Non-Kolmogorov Nature of Flare-Productive Solar Active Regions

Abstract

A magnetic power spectral analysis is performed on 53 solar active regions, observed from August 2011 to July 2012. Magnetic field data obtained from the Helioseismic and Magnetic Imager, inverted as Active Region Patches, are used to study the evolution of the magnetic power index as each region rotates across the solar disk. Active regions are classified based on the number, and sizes, of solar flares they produce, in order to study the relationship between flare productivity and the magnetic power index. The choice of window size and inertial range plays a key role in determining the correct magnetic power index. The overall distribution of magnetic power indices has a range of 1.0 − 2.5. Flare-quiet regions peak at a value of 1.6, however flare-productive regions peak at a value of 2.2. Overall, the histogram of the distribution of power indices of flare-productive active regions is well separated from flare-quiet active regions. Only 12% of flare-quiet regions exhibit an index greater than 2, whereas 90% of flare-productive regions exhibit an index greater than 2. Flare-quiet regions exhibit a high temporal variance (i.e, the index fluctuates between high and low values), whereas flare-productive regions maintain an index greater than 2 for several days. This shows the importance of including the temporal evolution of active regions in flare prediction studies, and highlights the potential of a 2-3 day prediction window for space weather applications.

On the possibility to probe the flare productivity of an active region on the early stage of emergence

“…Findings reported by Abramenko (2005b) and Abramenko & Yurchyshyn (2010) were recently supported by Mandage & McAteer (2016) who studied magnetic power spectra of 53 ARs observed by SDO/HMI. The ARs were divided into two subsets of flare-quiet and flare-productive (produced at least one M1 class flare) ARs.…”

“…The low-frequency (large-scale) limit of the inertial range relies on the scale where the dominant energy injection occurs (injection range). Thus, Mandage & McAteer (2016) argued that this limit may depend on the size of magnetic elements in the AR. The high-frequency (low-scale) limit is determined either by the dissipation, or, as in our case, by the (triple) spatial resolution of the telescope (Abramenko et al 2001).…”

“…The authors also argued that flare-quiet ARs may exhibit high day-to-day variations of the power index while the power index of flare-productive ARs remains stable at relatively high level days before and days after flare events. Mandage & McAteer (2016) concluded that the power index can be employed to forecast flares several days in advance.…”

The Sun’s Magnetic Power Spectra over Two Solar Cycles. I. Calibration between SDO/HMI and SOHO/MDI Magnetograms

“…Their spectra span from l = 1 to l ∼ 100 to understand the solar cycle and large-scale dynamo (Karak et al 2014;Charbonneau 2020). Most of the rest of the studies of magnetic power spectra concentrate on the analysis of local magnetograms of ARs, for the relationship between flare productivity and the magnetic power index (Abramenko et al 2002;Abramenko & Yurchyshyn 2010;Mandage & McAteer 2016) or the variation of magnetic power spectra during AR flux emergence (Kutsenko et al 2019).…”