Statistics – Computation
Scientific paper
Oct 2008
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2008geoji.175..185b&link_type=abstract
Geophysical Journal International, Volume 175, Issue 1, pp. 185-201.
Statistics
Computation
4
Computational Seismology
Scientific paper
We present a multiple event location technique that is able to produce minimally biased (location accuracy of 5 km or better) events from a cluster of earthquakes, without relying on prior ground truth information or dense local seismograph networks. In the hybrid hypocentroidal decomposition and reciprocal cluster analysis (HDC-RCA) method, HDC determines accurate relative locations in an event cluster (but a biased hypocentroid) using regional and/or teleseismic data. RCA uses local phases and invokes the reciprocity principle by relocating the local station network centroid with the events fixed (by HDC) as fictitious stations. Since the location of the local station network centroid is exactly known, the mislocation vector between the true and relocated centroids represents the offset with which the entire event cluster must be shifted to obtain unbiased absolute locations. We have developed applicability criteria to help determine under what conditions HDC-RCA is able to determine minimally-biased locations in an event cluster. The performance of the HDC-RCA method is validated on several event clusters containing previously determined ground truth events and applied to clusters for which ground truth events were not previously determined. Events promoted to GT5 level are provided in an electronic supplement.
Bergman Eric
Bondár István
Engdahl Eric Robert
Kohl Ben
Kung Yu-Long
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