Long-Period Long-Duration Events Detected by the IRIS Community Wavefield Demonstration Experiment in Oklahoma: Tremor or Train Signals?
Abstract
In this study, we apply a recently developed local similarity method to detect long‐period long‐duration (LPLD) seismic events using 1‐month continuous waveforms recorded by a nodal array from the Incorporated Research Institutions for Seismology (IRIS) community wavefield experiment in Oklahoma. The local similarity method detects seismic events by correlating waveforms at each station with its neighboring stations. Using this method, we visually identify 21 potential tremor‐like LPLD events lasting more than 300 s during the 1‐month period. However, with beamforming analysis, we find that the source locations and waveform characteristics of these events are consistent with train‐generated seismic signals from the nearby Union Pacific railway. Additional evidence includes amplitude decay away from the railway track, and similarities in frequency–time contents with other confirmed train‐generated seismic signals. This case study highlights the need of dense‐array observations to distinguish between natural and anthropogenic LPLD seismic signals.
Additional Information
© 2018 Seismological Society of America. Published Online 1 August 2018. Data and Resources: Seismic data used in this study are collected by the Incorporated Research Institutions for Seismology (IRIS) community wavefield experiment in Oklahoma and are open to public in the IRIS Data Management Center (DMC; http://ds.iris.edu/mda/YW?timewindow=2016-2016, last accessed June 2018). The authors appreciate Incorporated Research Institutions for Seismology (IRIS) for deployment of the IRIS community wavefield experiment in Oklahoma and making the data available to public. The authors thank Heather Deshon and Mike Brudzinski for pointing out potential train‐generated tremor‐like signals at the 2017 Eastern Section of Seismological Society of America Annual Meeting in Norman, Oklahoma. The authors appreciate Editor Brandon Schmandt, Abhijit Ghosh, and two anonymous reviewers for their constructive suggestions to improve this article. This article has benefitted from the valuable advice and help from Kevin Chao in Northwestern University, U.S.A., and Wei‐fang Sun in National Dong Hwa University, Taiwan. C. Li and Z. Peng are supported by National Science Foundation (NSF) Grants EAR‐1551022 and EAR‐1818611.Attached Files
Supplemental Material - srl-2018081_esupp.zip
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Additional details
- Eprint ID
- 88491
- Resolver ID
- CaltechAUTHORS:20180802-083040921
- NSF
- EAR‐1551022
- NSF
- EAR‐1818611
- Created
-
2018-08-02Created from EPrint's datestamp field
- Updated
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2021-11-16Created from EPrint's last_modified field
- Caltech groups
- Seismological Laboratory