Precursors of geomagnetic storms observed by the muon detector network

Details Precursors of geomagnetic storms observed by the muon detector network Precursors of geomagnetic storms observed by the muon detector network

Dec 2000

adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2000jgr...10527457m&link_type=abstract

Journal of Geophysical Research, Volume 105, Issue A12, p. 27457-27468

Physics

Plasma Physics

25

Interplanetary Physics: Cosmic Rays, Interplanetary Physics: Ejecta, Driver Gases, And Magnetic Clouds, Interplanetary Physics: Interplanetary Magnetic Fields, Space Plasma Physics: Charged Particle Motion And Acceleration

Scientific paper

We report the first systematic survey of cosmic ray precursors of geomagnetic storms. Our data set comprises the 14 ``major'' geomagnetic storms (peak Kp>=8-) identified by Gosling et al. [1990] together with 25 large storms (peak Kp>=7-) observed from 1992 through 1998. After eliminating events for which the muon detector network had poor coverage of the sunward interplanetary magnetic field (IMF) direction, we determined that 15 of the remaining 22 events (68%) had identifiable cosmic ray precursors with typical lead times ranging from 6 to 9 hours prior to the storm sudden commencement (SSC). Of the 15 precursors, 10 were of the ``loss cone'' (LC) type which is characterized by an intensity deficit confined to a narrow pitch angle region around the sunward IMF direction. Cosmic rays in the loss cone presumably originate in the cosmic-ray-depleted region downstream of the approaching shock. The remaining five precursors were of the ``enhanced variance'' (EV) type which is characterized by intensity increases or decreases that do not systematically align with the IMF direction. The incidence of precursors increases with storm size; for instance, 89% of storms with peak Kp greater than or equal to 8.0 had precursors. Our results show that the muon detector network can be a useful tool in space weather forecasting. However, new detector(s) installed to fill major gaps in the present network are urgently required for better understanding the nature of precursors and for reliable space weather forecasting.

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