Global Energetics of Solar Flares. XI. Flare Magnitude Predictions of the GOES Class

Abstract

In this study we determine scaling relationships of observed solar flares that can be used to predict upper limits of the GOES-class magnitude of solar flares. The flare prediction scheme is based on the scaling of the slowly-varying potential energy E p (t), which is extrapolated in time over an interval of ∆t ≤ 24 hrs. The observed scaling of the dissipated energy E diss scales with the potential field energy as E diss ∝ E 1.32 p. In addition, the observed scaling relationship of the flare volume, V ∝ E 1.17 diss , the multi-thermal energy, E th ∝ V 0.76 , the flare emission measure EM ∝ E 0.79 th , the EM-weighted temperature T w , and the GOES flux, F 8 (t) ∝ E p (t) 0.92 , allows us then to predict an upper limit of the GOES-class flare magnitude in the extrapolated time window. We find a good correlation (CCC≈ 0.7) between the observed and predicted GOES-class flare magnitudes (in 172 X and M-class events). This is the first algorithm that employs observed scaling laws of physical flare parameters to predict GOES flux upper limits, an important capability that complements previous flare prediction methods based on machine-learning algorithms used in space weather forecasting.

A Comparison of Solar X-Ray Flare Timescales and Peak Temperatures with Associated Coronal Mass Ejections

“…Finally, we emphasize that the data presented here refute simple scaling models between flares and CMEs (e.g., Takahashi et al 2016;Vršnak 2016;Aschwanden 2017Aschwanden , 2020Hu et al 2022) when the models refer to all flares. As seen in Figures 1-3, there are a number of M3 flares with no associated CMEs, even with favorably low Tm values, and a number of major CMEs with the unfavorable high-Tm flares.…”

Survey of Magnetic Field Parameters Associated with Large Solar Flares

“…Aschwanden (2020) predicted the upper limit of the possible GOES class based on the observed scaling of the slowly varying potential energy in the region. The free energy and potential energy show a good positive correlation (see Figure 1 in Aschwanden 2020). In our study, E free can be used to estimate the strongest flare in an AR, which is consistent with the results of Aschwanden (2020).…”

“…Based on the classic Space-Weather HMI AR Patches (SHARP; Bobra et al 2014) descriptors calculated from vector and line-of-sight magnetograms, there have been numerous flare forecasting studies specifically targeted the forecasting of the M/X-class flares (Bobra & Couvidat 2015;Barnes et al 2016;Liu et al 2017;Huang et al 2018;Campi et al 2019;Zheng et al 2023). However, these previous studies are still not capable of providing a substantially better performance than climatological forecasts (Barnes et al 2016;Campi et al 2019), which implies that the most relevant physical parameters that facilitate the prediction of solar flares are still unknown (Aschwanden 2020;Kontogiannis 2023). In this study, we introduce the area of high photospheric magnetic free energy density (HED) as the proxy of AR core region and analyze 11 nonpotential parameters within HED areas of 323 ARs producing C-class and M/X-class flares.…”

What aspects of solar flares can be clarified with mm/submm observations?

“…Significant efforts have been devoted towards identifying precursor signatures of flare events from ground-based and space observations, with varying degrees of success. There are three classes of precursors proposed (Aschwanden, 2020): 1) those involving the presence of specific features in photospheric magnetic structures (such as shear, penumbra type, length of polarity inversion line, etc); 2) those involving some type of magnetic configuration change observed in the photospheric magnetic field (such as helicity injection, new photospheric flux emergence and so on); and 3) direct observation of precursor activity in UV, EUV or X-ray observations, assumed to be related to the main flare itself (e.g. enhanced turbulence, brightenings at many wavelengths, line broadening, jets).…”