Apply ETAS in Earthquake Early Warning – A case study of M6.0 South Napa Earthquake

Earthquake Early Warning (EEW) is a trade-off between time and accuracy. We aim to increase the alerting time without loosing its reliability. This can be achieved by using prior information to classify a pick to be a true or false event, then issue alerts immediately after the first trigger. Since earthquakes cluster in time and location, potential aftershock occurrences can be predicted using the Epidemic-Type Aftershock Sequence Model (ETAS). We show that by applying the prior information provided by ETAS in the Bayesian updating process of EEW, we can significantly improve the alerting time. As an example, the epicenter estimation for the aftershock events from the M6.0 South Napa Earthquake is performed using ETAS to illustrate the accuracy of aftershock prediction. For instance, in an aftershock sequence, the most triggers at the closest stations will turn out to be real earthquake. As a result, during the aftershock sequence of the South Napa earthquake, warnings can be issued after observations of only one or two stations.