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SEC proton prediction model: verification and analysis
1National Oceanic and Atmospheric Administration, Space Environmental Center, Boulder, CO 80303-3328, USA.
Radiation Measurements
|September 7, 2001
Summary
This study refines a long-standing model for predicting solar energetic particle (SEP) events. Improvements enhance the accuracy of proton event probability, peak flux, and rise time predictions, aiding space weather forecasting.
Area of Science:
- Space Physics
- Solar Physics
- Space Weather
Background:
- A model has guided solar energetic particle (SEP) event prediction at NOAA since the 1970s.
- Accurate prediction of SEPs is crucial for space weather forecasting and mitigating risks to technology and astronauts.
Purpose of the Study:
- To describe the existing NOAA SEP prediction model, including its algorithms for proton event probability, peak flux, and rise time.
- To analyze the model's performance against observational data and identify areas for improvement.
- To implement and evaluate modifications to enhance prediction accuracy.
Main Methods:
- Description of algorithms for proton event probability, peak flux, and rise time.
- Comparison of model predictions with historical observational data.
- Analysis of model performance using root-mean-square (rms) error for flux and rise time.
- Implementation of algorithm modifications based on historical data analysis.
- Derivation of conditional climatology for proton event occurrence based on flare characteristics.
Main Results:
- The current model shows limited ability to distinguish between flares associated with proton events and those that are not.
- Peak flux predictions exhibit significant scatter, with an rms error close to an order of magnitude.
- Rise time predictions also show considerable scatter, with an rms error of approximately 28 hours.
- Implemented algorithm modifications reduced the rms error in log10 flux prediction by 21% and rise time by 31%.
- Improved probability predictions were achieved by incorporating conditional climatology.
Conclusions:
- The refined model demonstrates enhanced accuracy in predicting key characteristics of solar energetic particle events.
- The updated algorithms offer a more reliable tool for space weather forecasting.
- Further improvements in predicting proton event probability, peak flux, and rise time are achievable through model refinement.
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