Neural network prediction of relativistic electrons at geosynchronous orbit during the storm recovery phase: effects of recurring substorms

• Main Authors: M. Fukata, S. Taguchi, T. Okuzawa, T. Obara
• Format: Article
• Language: English
• Published: Copernicus Publications 2002-07-01
• Series: Annales Geophysicae
• Online Access: https://www.ann-geophys.net/20/947/2002/angeo-20-947-2002.pdf
• ISSN: 0992-7689; 1432-0576

During the recovery phase of geomagnetic storms, the flux of relativistic (&gt;2 MeV) electrons at geosynchronous orbits is enhanced. This enhancement reaches a level that can cause devastating damage to instruments on satellites. To predict these temporal variations, we have developed neural network models that predict the flux for the period 1–12 h ahead. The electron-flux data obtained during storms, from the Space Environment Monitor on board a Geostationary Meteorological Satellite, were used to construct the model. Various combinations of the input parameters <i>AL, <font face="Symbol"><b>S</b></font>AL, Dst </i>and <i><font face="Symbol"><b>S</b></font>Dst</i> were tested (where <i><font face="Symbol"><b>S</b></font></i> denotes the summation from the time of the minimum <i>Dst</i>). It was found that the model, including <i><font face="Symbol"><b>S</b></font>AL</i> as one of the input parameters, can provide some measure of relativistic electron-flux prediction at geosynchronous orbit during the recovery phase. We suggest from this result that the relativistic electron-flux enhancement during the recovery phase is associated with recurring substorms after <i>Dst</i> minimum and their accumulation effect.<br><br><b>Key words. </b>Magnetospheric physics (energetic particles, trapped; magnetospheric configuration and dynamics; storms and substorms)