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REGIONAL LOCATION AND IDENTIFICATION USING SPARSE STATIONS

By Brian Savage, Ying Tan, Lupei Zhu and Don Helmberger

Abstract

Locating events in Southern California is quite simple since we have about 500 stations, with a large fraction broadband (TriNet). We locate and identify within minutes. Thus, we have an opportunity to test hybrid methods against the full array estimate. Here we report on three projects addressing these issues; (1) locating events using one calibrated station with waveform data plus a few other stations with travel-time and polarity information, (2) particularly complex sub-regions where the depth phases such as pPn and sPn prove ineffective, and (3) calibrating paths using a combination of sparse regional waveforms and radar. In previous efforts (last years report) we presented results using waveforms from one-station (PAS) and a few polarities from the array (3 to 5). The model employed a grid-search over mechanism (strike, dip and rake) with the depth fixed. Along most paths the method proved effective when comparing against the entire network. Here we present results of letting the depth vary as well so that the single station must use pPn and sPn and the ratio of body waves to surface waves to fix the depth. Only about half the paths still work, but in those situations, the location is greatly improved over just travel-time fitting because of the whole seismogram matching procedure. Our method uses an adaptive grid search over location with calibrated Pnl and surface wave time shifts

Year: 2011
OAI identifier: oai:CiteSeerX.psu:10.1.1.199.2780
Provided by: CiteSeerX
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