Articles | Volume 23, issue 9
Ann. Geophys., 23, 2969–2974, 2005
https://doi.org/10.5194/angeo-23-2969-2005

Special issue: 1st European Space Weather Week (ESWW)

Ann. Geophys., 23, 2969–2974, 2005
https://doi.org/10.5194/angeo-23-2969-2005

  22 Nov 2005

22 Nov 2005

A logistic regression model for predicting the occurrence of intense geomagnetic storms

N. Srivastava 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.