Predictability of Large Geomagnetic Disturbances Based on Solar Wind Conditions
IEEE Transactions on Plasma Science
We test the ability of a data-derived model of geomagnetic activity, originally optimized to have a high prediction ef£ciency (PE), for its ability to predict only large geomagnetic disturbances. Correlation-based metrics, such as prediction ef£ciency, are often used as a measure of model performance. This metric puts equal weight on prediction of both large and small measurements. However, for space weather purposes, one is often interested in knowing only if a large disturbance event will
... ance event will occur so less emphasis should be placed on small measurements. If only large events are of interest, then a correlation metric is not the best measure of model performance. In this work, we determine how well a data-derived model, originally optimized to have a high prediction ef£ciency, predicts large geomagnetic events. The ratio of the number of correct to false alarm forecasts, RF , is used as an event-predictor metric. It is shown that in the electrojet regions the data-derived model that predicts the north-south component of the ground magnetic £eld Bx has a spatial RF pro£le similar to that of the prediction ef£ciency. Maximal values of RF = 4 are found at 0300 MLT when an event is de£ned as an excursion in the hourly-averaged north-south component of the ground magnetic £eld below −400 nT. Whereas the local time pro£le of P E(Bx) is similar to RF (Bx), the pro£le of P E(|dBx/dt|) differs substantially from RF (|dBx/dt|) in the noon sector. Epoch analysis shows that the poor performance in the noon sector is a result of pre-event levels of |dBx/dt| not being clearly separated from post-event levels.