TY - JOUR
T1 - Global Travel Time Data Set From Adaptive Empirical Wavelet Construction
AU - Lai, Hongyu
AU - Garnero, Edward J.
AU - Grand, Stephen P.
AU - Porritt, Robert W.
AU - Becker, Thorsten W.
N1 - Funding Information:
This research was financially supported by funds from National Science Foundation (NSF) EAR-1648817. We thank several seismic data centers that provided seismic data for this study, including Incorporated Research Institutions for Seismology, Data Management Center (IRIS DMC), Observatories & Research Facilities for European Seismology (ORFEUS), Northern California Earthquake Data Center (NECDC), F-net Broadband Seismograph Network (F-net), and Canadian National Seismic Network (CNSN). We also thank EarthScope program for the freely available USArray data, which provided large numbers of high-quality seismic data. Moreover, we thank the principle investigators, individuals, and organizations that deployed the seismic networks used in this study. A total number of 308 network codes was used in this study, which correspond to nearly 1,600 unique network deployments from various organizations and groups. We have compiled a list of detailed information of each individual network used in this study, including the network name, network operator, network country, network website if available, network deployment country, and digital object identifier if available. Please refer to Supporting Information S1 for details. Our final data set is available online (https://zenodo.org/record/1241248; doi:10.5281/zenodo.1299902). We thank Christine Houser and an anonymous reviewer for exceptionally thoughtful reviews, which helped to improve the manuscript.
Funding Information:
This research was financially supported by funds from National Science Foundation (NSF) EAR‐1648817. We thank several seismic data centers that provided seismic data for this study, including Incorporated Research Institutions for Seismology, Data Management Center (IRIS DMC), Observatories & Research Facilities for European Seismology (ORFEUS), Northern California Earthquake Data Center (NECDC), F‐net Broadband Seismograph Network (F‐net), and Canadian National Seismic Network (CNSN). We also thank EarthScope program for the freely available USArray data, which provided large numbers of high‐quality seismic data. Moreover, we thank the principle investigators, individuals, and organizations that deployed the seismic networks used in this study. A total number of 308 network codes was used in this study, which correspond to nearly 1,600 unique network deployments from various organizations and groups. We have compiled a list of detailed information of each individual network used in this study, including the network name, network operator, network country, network website if available, network deployment country, and digital object identifier if available. Please refer to Supporting Information S1 for details. Our final data set is available online (https://zenodo.org/record/1241248; doi:10.5281/zenodo.1299902). We thank Christine Houser and an anonymous reviewer for exceptionally thoughtful reviews, which helped to improve the manuscript.
Publisher Copyright:
©2019. American Geophysical Union. All Rights Reserved.
PY - 2019/5
Y1 - 2019/5
N2 - 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.
AB - 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.
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U2 - 10.1029/2018GC007905
DO - 10.1029/2018GC007905
M3 - Article
AN - SCOPUS:85065392635
SN - 1525-2027
VL - 20
SP - 2175
EP - 2198
JO - Geochemistry, Geophysics, Geosystems
JF - Geochemistry, Geophysics, Geosystems
IS - 5
ER -