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Ann. Geophys., 23, 2969-2974, 2005
www.ann-geophys.net/23/2969/2005/
© European Geosciences Union 2005
A logistic regression model for predicting the occurrence of intense geomagnetic storms
N. Srivastava
Udaipur Solar Observatory, Physical Research Laboratory, P.O. Box 198, Udaipur, India
Abstract. A logistic regression model is
implemented for predicting the occurrence of intense/super-intense
geomagnetic storms. A binary dependent variable, indicating the
occurrence of intense/super-intense geomagnetic storms, is
regressed against a series of independent model variables that
define a number of solar and interplanetary properties of
geo-effective CMEs. The model parameters (regression coefficients)
are estimated from a training data set which was extracted from a dataset
of 64 geo-effective CMEs observed during 1996-2002. The trained
model is validated by predicting the occurrence of geomagnetic
storms from a validation dataset, also extracted from the same
data set of 64 geo-effective CMEs, recorded during 1996-2002, but
not used for training the model. The model predicts 78% of the
geomagnetic storms from the validation data set. In addition, the
model predicts 85% of the geomagnetic storms from the training
data set. These results indicate that logistic regression models
can be effectively used for predicting the occurrence of intense
geomagnetic storms from a set of solar and interplanetary factors.
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