Forecasting of solar particle event doses using Bayesian inference

John S. Neal, Lawence W. Townsend

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

This work reports the use of Bayesian inference methods to make forecasts of dose-time profiles due to solar particle event proton fluxes using dose and dose rate values from early in the evolution of the event. Predicted profiles for absorbed dose in water are presented for the September 24,2001, November 4,2001. and November 22.2001 solar particle events. Dose-time profiles are modeled with nonlinear regression techniques that assume Weibull and Gompertz growth curves. Predictions are implemented by Markov Chain Monte Carlo sampling techniques. Results for the September 24. 2001 event under-predict actual asymptotic dose and suggest a refinement of the categorization methodology. Predictions for the November 2001 events provide good agreement with the actual dosetime profiles. This work provides encouraging results towards the development of a real-time, event-triggered, advanced warning system.

Original languageEnglish
Title of host publication2003 IEEE Aerospace Conference, Proceedings
Pages3451-3464
Number of pages14
DOIs
StatePublished - 2003
Externally publishedYes
Event2003 IEEE Aerospace Conference - Big Sky, MT, United States
Duration: Mar 8 2003Mar 15 2003

Publication series

NameIEEE Aerospace Conference Proceedings
Volume7
ISSN (Print)1095-323X

Conference

Conference2003 IEEE Aerospace Conference
Country/TerritoryUnited States
CityBig Sky, MT
Period03/8/0303/15/03

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