Riometer based Neural Network Prediction of Kp

The Canadian Geospace Observatory Riometer Array is a network of 11 wide-beam riometers deployed across Central and Northern Canada. The geographic coverage of the network affords a near continent scale view of high energy (>30keV) electron precipitation at a very course spatial resolution. In this paper we present the first results from a neural network based analysis of riometer data. Trained on decades of riometer data, the neural network is tuned to predict a simple index of global geomagnetic activity (Kp) based solely on the information provided by the high energy electron precipitation over Canada. We present results from various configurations of training and discuss the applicability of this technique for short term prediction of geomagnetic activity.