TERRAPUB Earth, Planets and Space

Earth Planets Space, Vol. 61 (No. 5), pp. 621-624, 2009


Statistically predicting Dst without satellite data

A. S. Parnowski

Space Research Institute NASU & NSAU, 40 prosp. Akad. Glushkova, Kyiv-187, 03680 MSP, Ukraine

(Received August 14, 2007; Revised September 16, 2007; Accepted September 23, 2007; Online published May 29, 2009)

Abstract: 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.
Key words: Space weather, statistical model, Dst prediction.

Corresponding author E-mail: dyx@ikd.kiev.ua

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