Global Ground Truth Data Set with Waveform and Arrival Data

Abstract : We present the final results of our three-year research project to produce a high-confidence global GT5 data set. During the course of this project we have developed, tested, and validated the hybrid HDC-RCA (Hypocentroidal Decomposition and Reciprocal Cluster Analysis) methodology to produce new GT5 or better event locations from event clusters. The HDC algorithm uses regional and teleseismic data to estimate precise relative event locations with respect to the cluster centroid. The RCA algorithm uses local data to precisely locate the cluster centroid. We have demonstrated that the HDC-RCA multiple event location methodology is able to produce high-confidence GT5 (epicenter and depth) or better event locations using only a few local stations, without reliance on independent GT information. A posteriori assessment procedures and a priori applicability criteria have been developed and tested to assure the quality and high-confidence of the resulting GT5 events. We have developed a novel, adaptive approach to waveform cross-correlation for improved differential arrival time measurements. The method finds the optimal time-bandwidth product to perform waveform cross-correlation, thus maximizing the similarity between waveforms for a wide range of seismic phases. Correlations are accepted or rejected based on their significance level derived from the estimated time-bandwidth product. We have further developed an error model to estimate the a priori uncertainties in differential time measurements in order to facilitate their inclusion with bulletin arrival time picks in the HDC algorithm. We demonstrated differential times contribute to significant improvements in resolving the relative event locations in the HDC analysis and validated the cross-correlation differential time measurement model.