Solar particle event dose and dose rate distributions: Parameterization of dose-time profiles using Bayesian inference and Markov Chain Monte Carlo methods

Galactic Cosmic Rays and Solar Particle Events are the dominant interplanetary radiation sources outside the Earth's geomagnetic field. Large Solar Particle Events may present an acute health hazard to crews of deep space, exploratory missions. Previous investigations to predict dose and dose rate-time profiles of Solar Particle Events have assumed a Weibull growth curve and have employed least squares regression techniques to perform model parameter inference. The work reported here is the first to utilize Bayesian inference techniques and Markov Chain Monte Carlo methods to sample parameter distributions for dose and dose rate-time profiles. Representative Solar Particle Events which span the observed range of asymptotic dose to astronauts are modeled using long-term growth models which include (1) a Weibull growth curve, (2) a Gompertz growth curve, and (3) a logistic growth curve.