Improvements in short-term forecasting of geomagnetic activity

We have improved our space weather forecasting algorithms to now predict Dst and AE in addition to Kp for up to 6 h of forecast times. These predictions can be accessed in real time at http://mms.rice.edu/realtime/forecast.html. In addition, in the event of an ongoing or imminent activity, e-mail "alerts" based on key discriminator levels have been going out to our subscribers since October 2003. The neural network-based algorithms utilize ACE data to generate full 1, 3, and 6 h ahead predictions of these indices from the Boyle index, an empirical approximation that estimates the Earth's polar cap potential using solar wind parameters. Our models yield correlation coefficients of over 0.88, 0.86, and 0.83 for 1 h predictions of Kp, Dst, and AE, respectively, and 0.86, 0.84, and 0.80 when predicting the same but 3 h ahead. Our 6 h ahead predictions, however, have slightly higher uncertainties. Furthermore, the paper also tests other solar wind functions-the Newell driver, the Borovsky control function, and adding solar wind pressure term to the Boyle index-for their ability to predict geomagnetic activity.