A Bayesian Approach to Solar Flare Prediction

A number of methods of flare prediction rely on classification of physicalcharacteristics of an active region, in particular optical classification ofsunspots, and historical rates of flaring for a given classification. Howeverthese methods largely ignore the number of flares the active region has alreadyproduced, in particular the number of small events. The past history ofoccurrence of flares (of all sizes) is an important indicator to future flareproduction. We present a Bayesian approach to flare prediction, which uses theflaring record of an active region together with phenomenological rules offlare statistics to refine an initial prediction for the occurrence of a bigflare during a subsequent period of time. The initial prediction is assumed tocome from one of the extant methods of flare prediction. The theory of themethod is outlined, and simulations are presented to show how the refinementstep of the method works in practice.Comment: 17 pages, 3 figure