Statistics – Computation
Scientific paper
Jan 2008
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2008spwea...601001b&link_type=abstract
Space Weather, Volume 6, Issue 1, CiteID S01001
Statistics
Computation
20
Computational Geophysics: Neural Networks, Fuzzy Logic, Machine Learning, Solar Physics, Astrophysics, And Astronomy: Energetic Particles (2114), Space Weather: Forecasting (2722), Space Weather: Space Radiation Environment
Scientific paper
This paper evaluates the performance of an operational proton prediction model currently being used at NOAA's Space Weather Prediction Center. The evaluation is based on proton events that occurred between 1986 and 2004. Parameters for the associated solar events determine a set of necessary conditions, which are used to construct a set of control events. Model output is calculated for these events and performance of the model is evaluated using standard verification measures. For probability forecasts we evaluate the accuracy, reliability, and resolution and display these results using a standard attributes diagram. We identify conditions for which the model is systematically inaccurate. The probability forecasts are also evaluated for categorical forecast performance measures. We find an optimal probability and we calculate the false alarm rate and probability of detection at this probability. We also show results for peak flux and rise time predictions. These findings provide an objective basis for measuring future improvements.
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