The Virtual Seismologist (VS) method: a Bayesian approach to seismic early warning
Abstract
The Virtual Seismologist (VS) method is a Bayesian approach to seismic early warning applicable to regions with distributed seismic hazard. It is modeled on ``back of the envelope'' methods of human seismologists for examining waveform data, in particular, in the use of the shapes of the ground motion envelopes and the relative frequency content of the observed ground motions to distinguish between small and large events. What differentiates the VS method from other proposed paradigms for seismic early warning is its capacity to assimilate different types of information that may be useful in arriving at quick and reliable estimates of magnitude and location. In addition to the observed ground motion amplitudes, the VS method uses prior information such as previously observed seismicity, the state of health of the seismic network, and station-specific amplification factors. These types of information are useful in resolving the trade-offs between magnitude and location when such trade-offs cannot be resolved by the limited available observations at the start of the earthquake rupture. We apply the VS method to various earthquake scenarios.
- Publication:
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AGU Fall Meeting Abstracts
- Pub Date:
- December 2004
- Bibcode:
- 2004AGUFM.S21A0253C
- Keywords:
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- 7223 Seismic hazard assessment and prediction;
- 7299 General or miscellaneous;
- 7212 Earthquake ground motions and engineering;
- 7215 Earthquake parameters