Statistically predicting Dst without satellite data
© The Society of Geomagnetism and Earth, Planetary and Space Sciences (SGEPSS); The Seismological Society of Japan; The Volcanological Society of Japan; The Geodetic Society of Japan; The Japanese Society for Planetary Sciences; TERRAPUB. 2009
Received: 14 August 2007
Accepted: 23 September 2007
Published: 29 May 2009
In this paper we construct a regression relationship for predicting Dst 1 hour ahead. Our model uses only previous Dst values. This regression is totally unbiased and does not rely on any physical model, except for the fact that Dst somehow contains the information on the recurrent geomagnetic storms. This regression has the prediction efficiency of 0.964, linear correlation with official Dst index of 0.982, and RMS of 4.52 nT. These characteristics are inferior only to our other model, which uses satellite data and provides the prediction efficiency of 0.975, linear correlation with official Dst index of 0.986, and RMS of 3.76 nT. This makes it quite suitable for prediction purposes when satellite data are not available.