TY - JOUR
T1 - Travel Time and Waveform Measurements of Global Multibounce Seismic Waves Using Virtual Station Seismogram Stacks
AU - Lai, Hongyu
AU - Garnero, Edward J.
N1 - Funding Information:
This research was financially supported by funds from NSF EAR-1648817. The detailed comments of two anonymous reviewers greatly helped to improve the manuscript. We thank several seismic data centers that provided seismic data for this study, including IRIS DMC (Incorporated Research Institutions for Seismology, Data Management Center), ORFEUS (Observatories & Research Facilities for European Seismology), NECDC (Northern California Earthquake Data Center), F-net (F-net Broadband Seismograph Network), CNSN (Canadian National Seismic Network). 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 the supplementary information for details. Our final data set is available online (https://doi.org/10.5281/zenodo.3247093).
Funding Information:
This research was financially supported by funds from NSF EAR‐1648817. The detailed comments of two anonymous reviewers greatly helped to improve the manuscript. We thank several seismic data centers that provided seismic data for this study, including IRIS DMC (Incorporated Research Institutions for Seismology, Data Management Center), ORFEUS (Observatories & Research Facilities for European Seismology), NECDC (Northern California Earthquake Data Center), F‐net (F‐net Broadband Seismograph Network), CNSN (Canadian National Seismic Network). 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 the supplementary information for details. Our final data set is available online ( https://doi.org/10.5281/zenodo.3247093 ).
Publisher Copyright:
© 2019. American Geophysical Union. All Rights Reserved.
PY - 2020/1/1
Y1 - 2020/1/1
N2 - We construct geographically localized bin stacks of waveforms, called virtual stations, to enhance signal-to-noise ratios (SNRs) for travel time and waveform measurements of multibounce S and ScS phases (S up to S6 and ScS up to ScS5), as well as direct S, ScS, and Sdiff, on tangential component data. Major arc S and ScS multibounce waves were also measured. Virtual station data are referenced to empirical wavelets constructed from direct S waves for each event. The virtual station approach is useful for low SNR data, bolstering wave path coverage in the southern hemisphere. Goodness of fit measurements between the adapted empirical wavelet and virtual station waveforms are documented, as well as SNRs, allowing for objective definition of travel time measurement quality. From a data set of 360 earthquakes and 8,407 seismographic stations, nearly 4 million records were utilized to construct 248,657 virtual station stacked seismograms, which were compared to best-fitting empirical wavelets. After human inspection of virtual station results, 8,871 travel time measurements were retained from 19 different minor and major arc seismic wave types. Higher multibounce data improve sampling of the southern hemisphere. From 188,003 single seismograms, 3,331 multibounce wave measurements were also made. Comparisons of single seismogram and virtual station stack measurements show a consistent bias: Virtual stack onset times are systematically early due to a broadening effect from stacking records with arrival time differences, which we correct for. The travel time and waveform measurements are publicly available.
AB - We construct geographically localized bin stacks of waveforms, called virtual stations, to enhance signal-to-noise ratios (SNRs) for travel time and waveform measurements of multibounce S and ScS phases (S up to S6 and ScS up to ScS5), as well as direct S, ScS, and Sdiff, on tangential component data. Major arc S and ScS multibounce waves were also measured. Virtual station data are referenced to empirical wavelets constructed from direct S waves for each event. The virtual station approach is useful for low SNR data, bolstering wave path coverage in the southern hemisphere. Goodness of fit measurements between the adapted empirical wavelet and virtual station waveforms are documented, as well as SNRs, allowing for objective definition of travel time measurement quality. From a data set of 360 earthquakes and 8,407 seismographic stations, nearly 4 million records were utilized to construct 248,657 virtual station stacked seismograms, which were compared to best-fitting empirical wavelets. After human inspection of virtual station results, 8,871 travel time measurements were retained from 19 different minor and major arc seismic wave types. Higher multibounce data improve sampling of the southern hemisphere. From 188,003 single seismograms, 3,331 multibounce wave measurements were also made. Comparisons of single seismogram and virtual station stack measurements show a consistent bias: Virtual stack onset times are systematically early due to a broadening effect from stacking records with arrival time differences, which we correct for. The travel time and waveform measurements are publicly available.
KW - S wave data set
KW - major arc phases
KW - multibounce S waves
KW - multibounce ScS waves
KW - slowness stacking
UR - http://www.scopus.com/inward/record.url?scp=85078489771&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85078489771&partnerID=8YFLogxK
U2 - 10.1029/2019GC008679
DO - 10.1029/2019GC008679
M3 - Article
AN - SCOPUS:85078489771
SN - 1525-2027
VL - 21
JO - Geochemistry, Geophysics, Geosystems
JF - Geochemistry, Geophysics, Geosystems
IS - 1
M1 - e2019GC008679
ER -