AbstractWe have constructed operational models for forecasting the geomagnetic storm index (Dst) two hours in advance from six parameters: the velocity and density of the solar wind, the magnitude of the interplanetary magnetic field (IMF), and the x, y, and z components of the IMF. Our models use an Elman-type neural network, and we forecast space weather by using real-time solar-wind data from the Advanced Composition Explorer spacecraft.The models have worked well since April of 1998 and the Dst values forecast using them have been made available to the public at http://www.crl.go.jp/uk/uk223/service/nnw/index.html. From February to October 1998 there were 11 storms with minimum Dst values below −80 nT, and for ten the difference between the forecast minimum Dst and the Dst calculated from data measured by ground stations was less than 23%.For the storm starting on 19 October, however, the difference was 40% because of the weak correlation between the ACE environment and the earth's environment during this event.The Dst depends on the orientation of the IMF relative to the solar magnetospheric x-y plane and seems to be relatively large when the y component of the IMF is positive and perhaps also when the x component is positive.
Operational models for forecasting Dst
Advances in Space Research ; 31 , 4 ; 829-834
2002-01-01
6 pages
Article (Journal)
Electronic Resource
English
Operational Models for Forecasting Dst
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