On‐Demand Custom Broadband Synthetic Seismograms

Krischer, Lion; Hutko, A. R.; Driel, Martin van; Stähler, Simon C.; Bahavar, M.; Trabant, Chad; Nissen‐Meyer, Tarje

doi:10.1785/0220160210

Cited by 51 publications

(45 citation statements)

References 31 publications

(25 reference statements)

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“…We request the vertical components of the synthetic global broadband seismogram for the iasp91_2s model from the IRIS Syngine Data Service (Krischer et al, 2017) powered by the spectral-element program AxiSEM (Nissen-Meyer et al, 2014) and the Python packages Obspy and Instaseis (Van Driel et al, 2015). A mask is applied to the full waveforms ( Fig.…”

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confidence: 99%

Observation and explanation of spurious seismic signals emerging in teleseismic noise correlations

Li¹,

Boué²,

Campillo³

2019

Preprint

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Abstract. Deep body waves have been reconstructed from seismic noise correlations in recent studies. Authors prospect their great potentials in deep-Earth imaging. In addition to the expected physical seismic phases, some spurious arrivals having no correspondence in earthquake seismograms are observed from the noise correlations. The origins of the noise-derived body waves have not been well understood. Traditionally, the reconstruction of seismic phases from inter-receiver noise correlations is attributed to the interference between waves from noise sources in the stationary-phase regions. The interfering waves emanating from a stationary-phase location have a common ray path from the source to the first receiver. The correlation operator cancels the common path and extracts a signal corresponding to the inter-receiver ray path. In this study, with seismic noise records from two networks at teleseismic distance, we show that noise-derived spurious seismic signals without correspondence in real seismograms can arise from the interference between waves without common ray path or common slowness. These noise-derived signals cannot be explained by the traditional stationary-phase arguments. Numerical experiments reproduce the observed spurious signals. These signals still emerge for uniformly distributed noise sources, and thus are not caused by localized sources. We interpret the presence of the spurious signals with a less restrictive condition of quasi-stationary phase: providing the time delays between interfering waves from spatially distributed noise sources are close enough, the stack of correlation functions over the distributed sources can still be constructive as an effect of finite frequencies, and thereby noise-derived signals emerge from the source averaging.

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confidence: 99%

Observation and explanation of spurious seismic signals emerging in teleseismic noise correlations

Li¹,

Boué²,

Campillo³

2019

Preprint

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“…speeding up data retrieval by parallelization and bulk requests 7. demonstrate obspyDMT's plotting capabilities as we go 8. apply instrument corrections to waveform data 9. retrieve synthetic seismograms from Syngine (Synthetics Engine) web service (Krischer et al, 2017), to match observed seismograms.…”

Section: Guided Tour Of Use Casesmentioning

confidence: 99%

“…waveforms from a new IRIS web service: Syngine (Krischer et al, 2017) and (2) providing required metadata for calculating synthetic waveforms using external tools.…”

Section: Requesting Synthetic Seismogramsmentioning

confidence: 99%

ObspyDMT: a Python toolbox for retrieving and processing large seismological data sets

Hosseini

Sigloch

2017

Solid Earth

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Abstract. We present obspyDMT, a free, open-source software toolbox for the query, retrieval, processing and management of seismological data sets, including very large, heterogeneous and/or dynamically growing ones. ObspyDMT simplifies and speeds up user interaction with data centers, in more versatile ways than existing tools. The user is shielded from the complexities of interacting with different data centers and data exchange protocols and is provided with powerful diagnostic and plotting tools to check the retrieved data and metadata. While primarily a productivity tool for research seismologists and observatories, easy-to-use syntax and plotting functionality also make obspyDMT an effective teaching aid. Written in the Python programming language, it can be used as a stand-alone command-line tool (requiring no knowledge of Python) or can be integrated as a module with other Python codes. It facilitates data archiving, preprocessing, instrument correction and quality control -routine but nontrivial tasks that can consume much user time. We describe obspyDMT's functionality, design and technical implementation, accompanied by an overview of its use cases. As an example of a typical problem encountered in seismogram preprocessing, we show how to check for inconsistencies in response files of two example stations. We also demonstrate the fully automated request, remote computation and retrieval of synthetic seismograms from the Synthetics Engine (Syngine) web service of the Data Management Center (DMC) at the Incorporated Research Institutions for Seismology (IRIS).

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“…ObsPy (Beyreuther et al, 2010;Megies et al, 2011;Krischer et al, 2015) is currently running and tested on Linux (32 and 64 bit), Windows (32 and 64 bit) and Mac OS X. Please refer to the ObsPy web page for complete notes regarding ObsPy installation on different platforms.…”

Section: Appendix A: Directory Structurementioning

confidence: 99%

“…obspyDMT is part of the ObsPy ecosystem (Beyreuther et al, 2010;Megies et al, 2011;Krischer et al, 2015), an open-source community project that develops Python software for seismological observatories under the GNU Lesser General Public License, hosted by the Ludwig-Maximilians-Universität Munich. ObspyDMT uses many of ObsPy's utility functions, as well as functions from Python's numpy, scipy and matplotlib libraries (Hunter, 2007), combining them into a more specialized piece of software.…”

Section: Introductionmentioning

confidence: 99%

Reply to Riccardo Zaccarelli's comments (RC2)

Hosseini¹

2017

Preprint

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We present obspyDMT, a free, open-source software toolbox for the query, retrieval, processing and management of seismological data sets, including very large, heterogeneous and/or dynamically growing ones. ObspyDMT simplifies and speeds up user interaction with data centers, in more versatile ways than existing tools. The user is shielded from the complexities of interacting with different data centers and data exchange protocols and is provided with powerful diagnostic and plotting tools to check the retrieved data and metadata. While primarily a productivity tool for research seismologists and observatories, easy-to-use syntax and plotting functionality also make obspyDMT an effective teaching aid. Written in the Python programming language, it can be used as a stand-alone command-line tool (requiring no knowledge of Python) or can be integrated as a module with other Python codes. It facilitates data archiving, preprocessing, instrument correction and quality control -routine but nontrivial tasks that can consume much user time. We describe obspyDMT's functionality, design and technical implementation, accompanied by an overview of its use cases. As an example of a typical problem encountered in seismogram preprocessing, we show how to check for inconsistencies in response files of two example stations. We also demonstrate the fully automated request, remote computation and retrieval of synthetic seismograms from the Synthetics Engine (Syngine) web service of the Data Management Center (DMC) at the Incorporated Research Institutions for Seismology (IRIS). Published by Copernicus Publications on behalf of the European Geosciences Union. Interface Data source URL FDSN BGR http://eida.bgr.de EMSC http://www.seismicportal.eu ETH http://eida.ethz.ch GEONET http://service.geonet.org.nz GFZ http://geofon.gfz-potsdam.de INGV http://webservices.rm.ingv.it IPGP http://eida.ipgp.fr IRIS http://service.iris.edu ISC http://isc-mirror.iris.washington.edu KOERI

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On‐Demand Custom Broadband Synthetic Seismograms

Cited by 51 publications

References 31 publications

Observation and explanation of spurious seismic signals emerging in teleseismic noise correlations

Observation and explanation of spurious seismic signals emerging in teleseismic noise correlations

ObspyDMT: a Python toolbox for retrieving and processing large seismological data sets

Reply to Riccardo Zaccarelli's comments (RC2)

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