Initial test of a Bayesian approach to solar flare prediction

Abstract

A test of a new Bayesian approach to solar flare prediction (Wheatland 2004a) is presented. The approach uses the past history of flaring together with phenomenological rules of flare statistics to make a prediction for the probability of occurrence of a large flare within an interval of time, or to refine an initial prediction (which may incorporate other information). The test of the method is based on data from the Geostationary Observational Environmental Satellites (GOES), and involves whole-Sun prediction of soft X-ray flares for 1976-2003. The results show that the method somewhat over-predicts the probability of all events above a moderate size, but performs well in predicting large events.

arXiv comment4 pages, 2 figures, Astronomical Society of Australia meeting in Brisbane, July 2004; revised version

References in corpus (2)

• Bayesian Blocks, A New Method to Analyze Structure in Photon Counting Data
• A Bayesian Approach to Solar Flare Prediction

Cited by in corpus (7)

• A Statistical Solar Flare Forecast Method
• Are Solar Active Regions with Major Flares More Fractal, Multifractal, or Turbulent than Others?
• Non-neutralized electric currents in solar active regions and flare productivity
• Strong Gravitational Lens Inversion: A Bayesian Approach
• Testing and Improving a Set of Morphological Predictors of Flaring Activity
• Lower-than-expected flare temperatures for TRAPPIST-1
• Kappa-Maxwellian electrons and Bi-Maxwellian protons in a two-fluid model for fast solar wind