Abstract
The prediction of solar energetic particle (SEP) events may help to improve the mitigation of adverse effects on humans and technology in space. UMASEP (University of Málaga Solar particle Event Predictor) is an empirical model scheme that predicts SEP events. This scheme is based on a dual-model approach. The first model predicts well-connected events by using an improved lag-correlation algorithm for analyzing soft X-ray (SXR) and differential proton fluxes to estimate empirically the Sun–Earth magnetic connectivity. The second model predicts poorly connected events by analyzing the evolution of differential proton fluxes. This study presents the evaluation of UMASEP-10 version 2, a tool based on the aforementioned scheme for predicting all >10 MeV SEP events, including those without associated flare. The evaluation of this tool is presented in terms of the probability of detection (POD), false alarm ratio (FAR) and average warning time (AWT). The best performance was achieved for the solar cycle 24 (i.e., 2008–2019), obtaining a POD of 91.1% (41/45), a FAR of 12.8% (6/47) and an AWT of 2 h 46 min. These results show that UMASEP-10 version 2 obtains a high POD and low FAR mainly because it is able to detect true Sun–Earth magnetic connections.
Subject
General Physics and Astronomy
Cited by
5 articles.
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