AUTOMATED SOLAR FLARE STATISTICS IN SOFT X-RAYS OVER 37 YEARS OF GOES OBSERVATIONS: THE INVARIANCE OF SELF-ORGANIZED CRITICALITY DURING THREE SOLAR CYCLES

We analyzed the soft X-ray light curves from the Geostationary Operational Environmental Satellites over the last 37 years (1975-2011) and measured with an automated flare detection algorithm over 300,000 solar flare events (amounting to Almost-Equal-To 5 times higher sensitivity than the NOAA flare catalog). We find a power-law slope of {alpha}{sub F} = 1.98 {+-} 0.11 for the (background-subtracted) soft X-ray peak fluxes that is invariant through three solar cycles and agrees with the theoretical prediction {alpha}{sub F} = 2.0 of the fractal-diffusive self-organized criticality (FD-SOC) model. For the soft X-ray flare rise times, we find a power-law slope of {alpha}{sub T} = 2.02 {+-} 0.04 during solar cycle minima years, which is also consistent with the prediction {alpha}{sub T} = 2.0 of the FD-SOC model. During solar cycle maxima years, the power-law slope is steeper in the range of {alpha}{sub T} Almost-Equal-To 2.0-5.0, which can be modeled by a solar-cycle-dependent flare pile-up bias effect. These results corroborate the FD-SOC model, which predicts a power-law slope of {alpha}{sub E} = 1.5 for flare energies and thus rules out significant nanoflare heating. While the FD-SOC model predicts the probability distribution functions of spatio-temporal scaling laws of nonlinear energy dissipation processes, additionalmore » physical models are needed to derive the scaling laws between the geometric SOC parameters and the observed emissivity in different wavelength regimes, as we derive here for soft X-ray emission. The FD-SOC model also yields statistical probabilities for solar flare forecasting.« less