Bayesian prediction of geomagnetic storms: Wind data, 1996-2010

The feature‐based Bayesian method previously developed by Chen et al. (1996, 1997) to predict the occurrence, severity, and duration of large geomagnetic storms has been run on a daily basis on the Wind/Magnetic Fields Investigation (MFI) data from January 1996 until March 2010. The algorithm uses as input real‐time solar wind magnetic field data obtained at the L1 Lagrange point, and the output is the probability prediction of the magnetic field structure of the upstream solar wind that has yet to arrive, and its geoeffectiveness, where geoeffectiveness is measured by the traditional Dst index. The performance characteristics of the method are evaluated using a four‐level contingency table: nonstorm disturbances (−80 nT