Predicting solar wind structures and their geoeffectiveness

摘要: This paper describes a feature-based pattern-recognition technique that utilizes real-time solar wind measurements to identify and predict the occurrence of structures can cause geomagnetic storms. The is based on knowledge storms are caused by events with certain identifiable features, two most important ones being (1) extended periods (2) large amplitudes southward interplanetary magnetic field (Bz < 0). Using measured properties available at current time t profiles north-south component, Bz(t) , east–west estimated for has yet arrive, where future time. On basis Bz By occurrence, onset time, duration, severity impending predicted. It shown durations exceeding predetermined threshold be predicted accurately. Successful predictions made after examining initial ∼20% geoeffective (i.e., storm-causing) structure. For long-duration such as clouds advance prediction from several hours in excess 10 hours. tested using 5 months historical data. We develop procedure extend capability incorporating additional features. Reduction potential “false alarms” “misses” resulting extensions discussed.