Neural networks and predictions of solar-terrestrial effects

Abstract

Neural networks for predictions of solar-terrestrial effects, such as geomagnetic induced currents (GICs), are presented. The following assumptions are made: the geomagnetic activity is mainly controlled by the southward B z -component of the solar wind. There are three major solar causes of the southward B z -components, namely the solar sector boundaries (SSB), the coronal mass ejections (CME) and the coronal holes (CH). The mean GIC size has an exponential relation to the geomagnetic activity index K p . The neural networks were trained with solar input data from various U.S. data bases: SSB-data from CSSA, Stanford, California, CME-data and solar wind-data from NOAA/SEL, Boulder, Colorado and finally CH-data from SacPeak/AFGL.