As an example, we apply the GrowClust method to two prominent, recent sequences in western Nevada: the Spanish Springs and Sheldon earthquake swarms. Additionally, GrowClust outputs robust location error estimates that are useful in interpreting the reliability and resolution of relocation results. Requiring no explicit matrix inversion, the method is computationally efficient and capable of handling large data sets, and naturally applies greater weight to more similar event pairs. The GrowClust method uses input differential travel times, cross-correlation values, and reference starting locations, and applies a hybrid, hierarchical clustering algorithm to simultaneously group and relocate events within similar event clusters. Here we describe GrowClust, a relative event relocation algorithm that can provide reliable relocation results for earthquake sequences over a wide range of spatial and temporal scales. Techniques based on waveform cross-correlation can significantly improve the precision of the relative locations of event pairs observed at a set of common stations. Accurate earthquake locations are essential for providing reliable hazard assessments, understanding the physical mechanisms driving extended earthquake sequences, and interpreting fault structure.
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