Work Description

Title: An analysis of recorded and simulated SH wave reverberations in the upper mantle beneath the USArray Open Access Deposited

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Attribute Value
Methodology
  • The method we use to image the reflecting structure beneath continental US is the common-reflection point (CRP) mapping method. We calculate the reflection point of a seismic wave given the reflection depth and locations of the earthquake and the station. Since the reflection at the source side and the receiver side result in the same wave pulse in seismograms, we first stack all waveforms of one earthquake to obtain the source side reflection, and subtract it. Then we apply the CRP method on remnant waveforms to obtain 3-D reflection structure in the receiver side.
Description
  • We use waveform data from the USArray and spectral-element method synthetics for 3-D seismic models. The recorded waveform data are downloaded from Incorporated Research Institutions for Seismology (IRIS) which is open to everyone. The synthetic waveform data are generated by the SPECMFEM3D_Globe software that was downloaded from the Computational Infrastructure for Geodynamics ( https://geodynamics.org/). This dataset includes the scripts we use to automatically download data from IRIS, the selection of data, and the application of the CRP method. In doing this, we use the TauP toolkit which is free to download ( https://www.seis.sc.edu/taup/) to compute the travel time.
Creator
Depositor
  • meichenl@umich.edu
Contact information
Discipline
Funding agency
  • National Science Foundation (NSF)
Keyword
Resource type
Last modified
  • 11/20/2022
Published
  • 04/07/2022
DOI
  • https://doi.org/10.7302/kcy5-an74
License
To Cite this Work:
Meichen Liu. (2022). An analysis of recorded and simulated SH wave reverberations in the upper mantle beneath the USArray [Data set], University of Michigan - Deep Blue Data. https://doi.org/10.7302/kcy5-an74

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Files (Count: 4; Size: 69.1 KB)

Thumbnailthumbnail-column Title Original Upload Last Modified File Size Access Actions
data_download.py 2022-01-16 2022-01-16 37.6 KB Open Access
stack_onedep.py 2022-01-16 2022-01-16 9.45 KB Open Access
xh_process.py 2022-01-16 2022-01-16 12.1 KB Open Access
xh_readfile_distance_recordsection.py 2022-01-16 2022-01-16 9.93 KB Open Access

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