Global Travel Time Data Set From Adaptive Empirical Wavelet Construction

We present a method for constructing the average waveform shape (hereafter called empirical wavelet) of seismic shear waves on an event-by-event basis for the purpose of constructing a high-quality travel time data set with information about waveform quality and shape. A global data set was assembled from 360 earthquakes between 1994 and 2017. The empirical wavelet approach permits documentation of the degree of similarity of every observed wave with the empirical wavelet. We adapt the empirical wavelet to all pulse widths, thus identifying broadened (e.g., attenuated) pulses. Several measures of goodness of fit of the empirical wavelet to each record are documented, as well as signal-to-noise ratios, permitting users of the data set to employ flexible weighting schemes. We demonstrate the approach on transversely polarized SH waves and build a global travel time data set for the waves S, SS, SSS, Sdiff, ScS, and ScSScS. Onset arrival times of the waves were determined through a correlation scheme with best-fitting empirical wavelets. Over 250,000 travel times were picked, from over 1.4 million records, all of which were human-checked for accuracy via a Portable Document Format (PDF) catalog file making system. Many events were specifically selected to bolster southern hemisphere coverage. Coverage maps show that, while the northern hemisphere is more densely sampled, the southern hemisphere coverage is robust. The travel time data set, empirical wavelets, and all measurement metrics are publicly available and well suited for global tomography, as well as forward modeling experiments.