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Solar Energetic Particle Forecasting Algorithms and Associated False Alarms View all abstracts by submitter

Bill Swalwell   Submitted: 2017-11-30 04:49

Solar energetic particle (SEP) events are known to occur following solar flares and coronal mass ejections (CMEs). However some high-energy solar events do not result in SEPs being detected at Earth, and it is these types of event which may be termed "false alarms". We define two simple SEP forecasting algorithms based upon the occurrence of a magnetically well-connected CME with a speed in excess of 1500 km s-1 ("a fast CME") or a well-connected X-class flare and analyse them with respect to historical data sets. We compare the parameters of those solar events which produced an enhancement of >40 MeV protons at Earth ("an SEP event") and the false alarms. We find that an SEP forecasting algorithm based solely upon the occurrence of a well-connected fast CME produces fewer false alarms (28.8%) than one based solely upon a well-connected X-class flare (50.6%). Both algorithms fail to forecast a relatively high percentage of SEP events (53.2% and 50.6% respectively). Our analysis of the historical data sets shows that false alarm X-class flares were either not associated with any CME, or were associated with a CME slower than 500 km s-1; false alarm fast CMEs tended to be associated with flares of class less than M3. A better approach to forecasting would be an algorithm which takes as its base the occurrence of both CMEs and flares. We define a new forecasting algorithm which uses a combination of CME and flare parameters and show that the false alarm ratio is similar to that for the algorithm based upon fast CMEs (29.6%), but the percentage of SEP events not forecast is reduced to 32.4%. Lists of the solar events which gave rise to >40 MeV protons and the false alarms have been derived and are made available to aid further study.

Authors: Swalwell, B., Dalla, S., Walsh, R.
Projects: None

Publication Status: Published in Solar Physics 292:173 (2017)
Last Modified: 2017-11-30 11:56
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