Suppressing Coda Events with a Bayesian Model of Global Scale Seismology

Large seismic events often trigger a wave train of slow decaying energy known as the coda that can mislead signal detectors into forming coda detections that appear to look like regular phase detections. These coda detections can confuse event formation algorithms into building false events known as coda events. Naive solutions to this problem by dropping any detection that looks like a coda detection can have the negative consequence of missing real events. We propose to address this issue by extending an existing Bayesian approach, NET-VISA that has been designed to build event bulletins using a generative model of global-scale seismology. Our extensions significantly boost the existing work by reducing the total number of false events by nearly half and virtually eliminating coda events without changing the number of real events.