The development of a solar proton event prediction model

Details The development of a solar proton event prediction model The development of a solar proton event prediction model

Jun 2004

adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2004phdt........16p&link_type=abstract

Ph.D dissertation, 2004. 150 pages; England: University of Southampton (United Kingdom); 2004. Publication Number: AAT C820404.

Computer Science

Solar Proton Event, Forecasting, Magnetosphere, Radiation Hazards, Spacecraft Hazard

Scientific paper

Solar Proton Events (SPEs) pose a significant radiation hazard to spacecraft within and beyond the magnetosphere, but currently there is no capability to predict these events more than 24 hours before they occur. This thesis develops a classification approach for the prediction of SPEs with a 48-hour lead time, and addresses the fact that very little work has been done on examining SPE forecasting methods with longer lead times than current flare-association techniques allow. Development of the technique has been based on a uniform dataset that covers 3 solar cycles and more than 30 decades of continuous spacecraft observations, and has used solar x-ray fluxes and solar radio fluxes as predictor variables.
By comparing times of SPE occurrence to times at which the solar proton flux was at a background level it has been shown that SPEs are associated with increased levels of solar x-ray flux and solar radio flux, and that these increases are, on average, significant up to 5 days prior to SPE occurrence. Using these variables as inputs neural models have generated 65% success rates for SPE prediction with a 48-hour lead time, extending the lead time of existing models by a day or more. A neural model has been coded to operate in real-time and represents the only autonomous SPE forecast model with a 48-hour lead time that does not require human supervision. Assessing the model over a 12-month operational period showed it to have superior SPE detection capability to the current 2-day forecast operated by the Space Environment Centre.
Success of the classification technique was limited by the fact that solar x- ray flares were found to exhibit similar precursors to SPEs, although this meant that the model could in fact be used to forecast flares to a greater success than SPEs. Additional findings showed that the correction of radio flux observations for centre-to-limb dependence may offer the potential for more accurate forecasting ability on a timescale of days.

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