Statistical Prediction of Solar Particle Event Frequency based on the Measurements of Recent Solar Cycles for Acute Radiation Risk Analysis

Details Statistical Prediction of Solar Particle Event Frequency based on the Measurements of Recent Solar Cycles for Acute Radiation Risk Analysis Statistical Prediction of Solar Particle Event Frequency based on the Measurements of Recent Solar Cycles for Acute Radiation Risk Analysis

Dec 2009

adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2009agufmsa43a1621k&link_type=abstract

American Geophysical Union, Fall Meeting 2009, abstract #SA43A-1621

Computer Science

Performance

[7924] Space Weather / Forecasting, [7938] Space Weather / Impacts On Humans, [7959] Space Weather / Models, [7984] Space Weather / Space Radiation Environment

Scientific paper

Large solar particle events (SPEs) present significant acute radiation risks to the crew members during extra-vehicular activities (EVAs) or in lightly shielded space vehicles for space missions beyond the protection of the Earth’s magnetic field. Acute radiation sickness (ARS) can impair performance and result in failure of the mission. Improved forecasting capability and/or early-warning systems and proper shielding solutions are required to stay within NASA’s short-term dose limits. Exactly how to make use of observations of SPEs for predicting occurrence and size is a great challenge, because SPE occurrences themselves are random in nature even though the expected frequency of SPEs is strongly influenced by the time position within the solar activity cycle. Therefore, we developed a probabilistic model approach, where a cumulative expected occurrence curve of SPEs for a typical solar cycle was formed from a non-homogeneous Poisson process model fitted to a database of proton fluence measurements of SPEs that occurred during the past 5 solar cycles (19 -23) and those of large SPEs identified from impulsive nitrate enhancements in polar ice. From the fitted model, the expected frequency of SPEs was estimated at any given proton fluence threshold (ΦE) with energy (E) >30 MeV during a defined space mission period. Corresponding ΦE (E=30, 60, and 100 MeV) fluence distributions were simulated with a random draw from a gamma distribution, and applied for SPE ARS risk analysis for a specific mission period. It has been found that the accurate prediction of deep-seated organ doses was more precisely predicted at high energies, Φ100, than at lower energies such as Φ30 or Φ60, because of the high penetration depth of high energy protons. Estimates of ARS are then described for 90th and 95th percentile events for several mission lengths and for several likely organ dose-rates. The ability to accurately measure high energy protons (50-300 MeV) in real-time is shown to be a crucial issue for crew protection.

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