A Bayesian Approach to Solar Flare Prediction

Abstract

A number of methods of flare prediction rely on classification of physical characteristics of an active region, in particular optical classification of sunspots, and historical rates of flaring for a given classification. However these methods largely ignore the number of flares the active region has already produced, in particular the number of small events. The past history of occurrence of flares (of all sizes) is an important indicator to future flare production. We present a Bayesian approach to flare prediction, which uses the flaring record of an active region together with phenomenological rules of flare statistics to refine an initial prediction for the occurrence of a big flare during a subsequent period of time. The initial prediction is assumed to come from one of the extant methods of flare prediction. The theory of the method is outlined, and simulations are presented to show how the refinement step of the method works in practice.

17 pages, 3 figures

References in corpus (1)

• Bayesian Blocks, A New Method to Analyze Structure in Photon Counting Data

Cited by in corpus (37)

• Power-law distributions in empirical data
• An Observational Overview of Solar Flares
• The origin, early evolution and predictability of solar eruptions
• 25 Years of Self-Organized Criticality: Solar and Astrophysics
• A Comparison of Flare Forecasting Methods, I: Results from the "All-Clear" Workshop
• Solar Flare Prediction Model with Three Machine-Learning Algorithms Using Ultraviolet Brightening and Vector Magnetogram
• Deep Flare Net (DeFN) model for solar flare prediction
• Microflares and the Statistics of X-ray Flares
• Flare Prediction Using Photospheric and Coronal Image Data
• A Statistical Solar Flare Forecast Method
• A hybrid supervised/unsupervised machine learning approach to solar flare prediction
• Flares in Open Clusters with K2. II. Pleiades, Hyades, Praesepe, Ruprecht 147, and M67
• Turbulence, Complexity, and Solar Flares
• Prediction of Solar Flares Using Unique Signatures of Magnetic Field Images
• Statistics and Polarization of Type III Radio Bursts Observed in the Inner Heliosphere
• Statistical Modeling of Solar Flare Activity from Empirical Time Series of Soft X-ray Solar Emission
• Radio and X-ray Observations of PSR B0540-69
• On the generation of probabilistic forecasts from deterministic models
• Evidence for departure from a power-law flare size distribution for a small solar active region
• On the Brightness and Waiting-time Distributions of a Type III Radio Storm observed by STEREO/WAVES
• Solar Flare Index Prediction Using SDO/HMI Vector Magnetic Data Products with Statistical and Machine Learning Methods
• Leveraging the Mathematics of Shape for Solar Magnetic Eruption Prediction
• Is the Hemispheric Asymmetry of Monthly Sunspot Area an Irregular Process with Long-Term Memory?
• The Effect of Limited Sample Sizes on the Accuracy of the Estimated Scaling Parameter for Power-Law-Distributed Solar Data
• The Poissonian Origin of Power Laws in Solar Flare Waiting Time Distributions
• Bayesian Analysis of Solar Oscillations
• A search for stellar X-ray sourcesin the Sagittarius and Carina dwarf galaxies - I: X-ray observations
• Chandra observations of the globular cluster M54
• On the possibility to probe the flare productivity of an active region on the early stage of emergence
• Initial test of a Bayesian approach to solar flare prediction
• The association of the Hale Sector Boundary with RHESSI solar flares and active longitudes
• Flare frequency in M dwarfs belonging to Young Moving Groups
• The corona of a fully convective star with a near-polar flare
• Enhancing the detection of low-energy M dwarf flares: Wavelet-based denoising of CHEOPS data
• CaII and H$\alpha$ flaring M dwarfs detected with multi-filter photometry
• Kepler-411 star activity: connection between starspots and superflares
• Solar flare forecasting using morphological properties of sunspot groups