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Probabilistic Solar Particle Flux Forecast Modeling

This study presents a probabilistic model for forecasting solar particle events (SPE) using historical data from the SPE database for the most recent solar cycles (19-23). We develop a non-homogeneous Poisson process model to predict the frequency of SPEs based on measurements of SPE flux. Key findings include a cumulative frequency distribution of recorded SPEs and a non-constant hazard function that captures the propensity of SPE occurrences. Additionally, we simulate distributions for various mission periods, providing a realistic framework for future space mission planning.

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Probabilistic Solar Particle Flux Forecast Modeling

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  1. Probabilistic Solar Particle Flux Forecast Modeling Myung-Hee Y. Kim and Francis A. Cucinotta

  2. SPE Database for the Recent Solar Cycles 19 20 21 22 23

  3. Model-based Prediction of SPE Frequency based on the Measurements of SPE Flux Propensity of SPEs: Hazard Function of Offset b Distribution Density Function 19 20 21 22 23 m=1783rd day Typical Nonspecific Future Cycle

  4. Approaches • Cumulative frequency distribution of recorded SPEs • Model for the realistic application and the dependence • of multipleSPEs: • Non-constant hazard function defined for the best propensity of SPE data in space era • Non-homogenous Poisson process model for SPE frequency in an arbitrary mission period • Cumulative probability of SPE occurrence during a given mission period using fitted Poisson model • 3. Simulation of F30, 60, or 100 distribution for each mission periods by a random draw from Gamma distribution

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