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35 results for “Crustal Structure”
Data and results in "Relationship between crustal structure and plate convergence around the Izu collision zone in central Japan"
<p>“allrfstationlist.dat” contains the list of the used seismic stations. The four columns indicate the name, latitude, longitude, and altitude (m) of each station, respectively.</p> <p>“allrfevent.dat” contains the list of the used teleseismic events. From left to right, the 10 columns indicate the year, month (in number), day, hour, minute, and second of the origin time (Japan Standard Time), and the latitude (from –90 to 90), longitude (from –180 to 180), depth of the hypocenter, and magnitude of each event, respectively.</p> <p>“RFmoho.dat” contains the depth distribution of the Moho determined by our RF analysis. The third column indicates the depth (km) of the Moho at the given latitude (the second column) and longitude (the first column)</p> <p>“Tomo_depth_limited.txt” contains the depth distribution of the lower boundary of a layer with a P-wave velocity of 7.5–7.7 km/s in the model by Ishise et al. (2021), which was assumed as the Moho. The third column indicates its depth (km) at the given latitude (the first column) and longitude (the second column)</p> <p>“crustthickness_tomorf.dat” contains the thickness distribution of the crust of the Philippine Sea Plate determined from the geometry of its upper surface estimated by Hirose et al. (2008a, b) and Nakajima et al. (2009) and the Moho depth distribution shown in RFmoho.dat and Tomo_depth_limited.txt. The third column indicates the thickness (km) of the crust at the given latitude (the second column) and longitude (the first column). “RF” and “tomo” in the fourth column indicate the corresponding thickness determined based on the RF analysis and the model by Ishise et al. (2021), respectively.</p>
Dataset for "Adjoint Waveform Tomography for Crustal and Upper Mantle Structure the Middle East and Southwest Asia for Improved Waveform Simulations Using Openly Available Broadband Data"
<p>This dataset contains the MESWA (Middle East and Southwest Asia) seismic model and auxiliary data used in the creation of the model (Rodgers, 2023). MESWA is a three-dimensional model of the seismic properties of crust and upper mantle of the Middle East and Southwest Asia. The MESWA model is provided in NetCDF format (readable by for example, <em>xarray</em>, Hoyer & Hamman, <a href="https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2021JB022930#jgrb55516-bib-0057">2017</a>) and HDF5 format for viewing with <em>ParaView</em> (Ahrens et al., <a href="https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2021JB022930#jgrb55516-bib-0002">2005</a>) and interaction with <em>Salvus</em> (Afanasiev et al., <a href="https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2021JB022930#jgrb55516-bib-0001">2019</a>). </p> <p> </p> <p>Also included are the earthquake source parameters for all 327 Global Centroid Moment Tensor events considered in this study in ASCII text format. Also included are lists of the selected 192 inversion events and 66 validation events in ASCII text format. Lastly, we include a list of all receivers used in the creation and validation of MESWA. This is a simple ASCII file with the event name and receiver name (composed of the network_code and station_code).</p> <p> </p> <p>The following table provides a listing of the files in the dataset:</p> <table> <tbody> <tr> <td> <p><strong>File</strong></p> </td> <td> <p><strong>Description</strong></p> </td> </tr> <tr> <td> <p>MESWA.nc</p> </td> <td> <p>MESWA model in NetCDF format</p> </td> </tr> <tr> <td> <p>MESWA.h5</p> </td> <td> <p>MESWA model in HDF5 format, used by Salvus</p> </td> </tr> <tr> <td> <p>MESWA.xmdf</p> </td> <td> <p>Auxiliary file for MESWA.h5, used to import model into Paraview</p> </td> </tr> <tr> <td> <p>events_project.csv</p> </td> <td> <p>Table of event source parameters for all 327 events considered in the project</p> </td> </tr> <tr> <td> <p>inversion_events_192.csv</p> </td> <td> <p>Table of 192 inversion events </p> <p>(ASCII comma separated value)</p> </td> </tr> <tr> <td> <p>validation_events_66.csv</p> </td> <td> <p>Table of 66 validation events </p> <p>(ASCII comma separated value)</p> </td> </tr> <tr> <td> <p>events_receivers_inversion.csv</p> </td> <td> <p>Table of waveform (event-receiver-channel) data used in the inversion (ASCII comma separated value)</p> </td> </tr> <tr> <td> <p>events_receivers_validation.csv</p> </td> <td> <p>Table of waveform (event-receiver-channel) data used in the validation (ASCII comma separated value)</p> </td> </tr> </tbody> </table> <p> </p> <p> </p> <p><strong>References</strong></p> <p>Afanasiev, M, C Boehm, M van Driel, L Krischer, M Rietmann, DA May, MG Knepley, and A Fichtner (2019). Modular and flexible spectral-element waveform modelling in two and three dimensions, <em>Geophys. J. Int.</em>, 216(3), 1675–1692, doi: 10.1093/gji/ggy469</p> <p> </p> <p>Ahrens, J., Geveci, B., & Law, C. (2005). Paraview: An end-user tool for large data visualization. <em>The Visualization Handbook</em>, 717(8). <a href="https://doi.org/10.1016/b978-012387582-2/50038-1">https://doi.org/10.1016/b978-012387582-2/50038-1</a></p> <p> </p> <p>Hoyer, S., & Hamman, J. (2017). Xarray: N-D labeled arrays and datasets in Python. <em>Journal of Open Research Software</em>, 5(1). <a href="https://doi.org/10.5334/jors.148">https://doi.org/10.5334/jors.148</a></p> <p> </p> <p>Rodgers, A. (2023). Adjoint Waveform Tomography for Crustal and Upper Mantle Structure the Middle East and Southwest Asia for Improved Waveform Simulations Using Openly Available Broadband Data, technical report, LLNL-TR- 851939.</p> <p> </p> <p><strong>Acknowledgements</strong></p> <p>This project was support by Lawrence Livermore National Laboratory’s Laboratory Directed Research and Development project 20-ERD-008 and the National Nuclear Security Administration. This work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344. LLNL-MI-852402</p> <p> </p>
Data for "Variation in Upper Plate Crustal and Lithospheric Mantle Structure in the Greater and Lesser Antilles from Ambient Noise Tomography"
<p>This is the phase velocity information and the shear wave model for the g-cubed paper:</p> <p>"Variation in Upper Plate Crustal and Lithospheric Mantle Structure in the Greater and Lesser Antilles from Ambient Noise Tomography"</p>
Crustal structure of the Volgo-Uralian subcraton revealed by inverse and forward gravity modeling [dataset]
<p>This collection contains data that were used to build a 3D crustal model of the Volgo-Uralian subcraton through inverse and forward gravity modeling.</p> <p>The dataset is subdivided into two folders: (1) Gravity field inversion; (2) Forward gravity modeling. </p>
Dataset presented in the recently submitted AGU manuscript "Constraining the crustal and mantle conductivity structures beneath islands by a joint inversion of multi-source magnetic transfer functions"
<p>Dataset (observed tippers, solar quiet global-to-local transfer functions, and global Q responses) presented in the recently submitted AGU manuscript "Constraining the crustal and mantle conductivity structures beneath islands by a joint inversion of multi-source magnetic transfer functions".</p>
Magnetotelluric data from Santos basin (SE Brazil) and inversion resistivity models exploring basin wedge and deep crustal structure beneath.
<p><strong>Magnetotelluric data</strong></p> <p>Processed data from 90 magnetotelluric broadband stations acquired in are available in Electrical Data Interchange (EDI) and ModEM format.</p> <p>The MMT data were recorded in 2007 by WesternGeco Electromagnetics as part of the National Observatory Rio de Janeiro project funded by Petrobras. The campaign comprised a total of 92 sites from shallow water (about 50 m depth) to deep water (about 1600 m depth). The stations are placed along three NW-SE parallel profiles in the northwest part of Santos basin. The central profile is approximately 160 km long and consists of 56 stations, while the west profile and east profile extend about 55 km each and contain 18 and 16 stations, respectively.</p> <p> </p> <p><strong>Models</strong></p> <p>Inversion models and predicted data are present for two different starting resistivity model testes 10 and 1 Ohm.m. The inversion models were estimated using ModEM - modular system for inversion of electromagnetic geophysical data.</p>
Data and program codes to reproduce the results presented in "Crustal structure beneath Central Kamchatka inferred from ambient noise tomography"
<p>This archive contains the SURF_TOMO code for the surface-wave tomography (<em>Koulakov et al., 2016</em>) and all the necessary files and instructions for reproducing the results presented in the paper “Crustal structure beneath Central Kamchatka inferred from ambient noise tomography” by Igor Egorushkin, Ivan Koulakov, Andrey Jakovlev, Hsin-Hua Huang, Eugeny I. Gordeev, Ilyas Abkadyrov, and Danila Chebrov.</p>
Crustal thicknesses, Moho depths and 3-D density anomaly model for GJI paper: Crustal structure of onshore-offshore Atlantic Canada and environs from constrained 3-D gravity inversion using variable mesh depths by J. Kim Welford
<p>The files are provided as ascii text files in terms of both latitudes/longitudes and eastings/northings. For the 3-D density anomaly model, it is provided with columns of x, y, z, and absolute density. The conversions from latitudes/longitudes to eastings/northings for all of the models and maps in this work are computed with ellipsoid WGS-84 and UTM zone 19 using Generic Mapping Tools.</p>
Rheological structure and lithospheric stress interaction in the Alaska subduction zone gleaned from the 2018 Mw 7.9 oceanic crustal earthquake
<p>This repository contains the observed and modeled first 2-year timeseries of postseismic deformation at GPS sites in the best-fit model associated with the 2018 Mw 7.9 Kodiak, Alaska earthquake (Timeseries.rar), as well as the preferred afterslip on the fault (Afterslip.rar).</p>
Data presented in Crustal structure and anisotropy measured by CHINArray and implications for complicated deformation mechanisms beneath the eastern Tibetan margin
<p>The dataset includes the raw waveforms and receiver functions presented in the paper Crustal structure and anisotropy measured by CHINArray and implications for complicated deformation mechanisms beneath the eastern Tibetan margin, submitted to JGR Solid Earth.</p><p>Contact: Zengsijia@cug.edu.cn</p><p> </p>
Upper Crustal Structure of the Xinfengjiang Reservoir from Ambient Noise Double Beamforming Tomography and Its Implications for Induced Seismicity
<p>The file "CC.tar.gz" contains the linearly stacked ZZ component cross-correlations for all station pairs.</p> <p>The file "Model.tar.gz" contains the 3-D upper crustal model of the Xinfengjiang Reservoir via ambient noise Double-Beamforming tomograpy.</p>
A heterogenous mantle and crustal structure formed during the early differentiation of Mars
<p>Highly siderophile element abundances and Os isotopes of nakhlite and chassignite meteorites demonstrate that they represent a comagmatic suite from Mars. Nakhlites experienced variable assimilation of >2 Ga altered high Re/Os basaltic crust. This basaltic crust is distinct from the ancient crust represented by meteorites Allan Hills 84001, or impact-contaminated Northwest Africa 7034/7533. Nakhlites and chassignites that did not experience crustal assimilation were extracted from a depleted lithospheric mantle distinct from the deep plume source of depleted shergottites. The comagmatic origin for nakhlites and chassignites demonstrates a layered martian interior comprising ancient enriched basaltic crust derived from trace element-rich shallow magma ocean cumulates, a variably metasomatized mantle lithosphere, and a trace element-depleted deep mantle sampled by plume magmatism.</p>
Data from: Crustal structure in central-eastern Greenland from Receiver Functions
<p>Data used in: </p> <p>Helene A. Kraft, Hans Thybo, Lev P. Vinnik, and Sergei Oreshin (2018). Crustal structure in central-eastern Greenland from Receiver Functions, submitted to Journal of Geophysical Research - Solid Earth (Paper #2018JB015919R).</p>
Crustal and upper mantle structure of the Tien Shan orogenic belt from full-wave ambient noise tomography
<p>Empirical Green’s functions, phase delays and shear wave velocity model of Tien Shan</p>
Seismic interpretation of key stratigraphic and structural surfaces, and crustal faults within the Galicia 3-D reflection survey
<p>This repository contains all the seismic interpretations utilized for the analysis in the article "<em>Origin of serpentinization patterns beneath the S-reflector detachment fault in the Galicia margin, offshore Spain</em>". </p> <p>The "<em>Surfaces</em>" file contains the CPS-3 shape files of the major stratigraphic and structural surfaces (seafloor, base of post-rift sedimentary strata, base of pre/syn-rift sedimentary strata, base of crystalline basement, S-reflector detachment fault, Moho). The "<em>Faults</em>" file contains the interpretations of the major crustal faults overlying the S-reflector detachment. The "<em>Data</em>" file contains the spatial boundary of where the S-reflector is the crust-mantle boundary, the P-wave velocities of Schuba et al. (2019) and calculated degree of serpentinization (Schuba et al., submitted) based on Christensen's (2004) 200 MPa/200<sup>o</sup>C serpentinite compilation study. </p> <p>All seismic interpretations were carried out on Petrel<sup>TM</sup> versions 2015 and 2017. The seismic reflection volume that was interpreted can be found at https://doi.org/10.1594/IEDA/500151.</p> <p> </p> <p>References: </p> <ul> <li>Christensen, N.I. (2004). Serpentinites, Peridotites, and Seismology. <em>International Geology Review</em>, <em>46</em>(9), 795-816. https://doi.org/10.2747/0020-6814.46.9.795</li> <li>Schuba, C.N., Schuba, J.P. Gray, G.G., and Davy, R.G., (2019). Interface targeted velocity estimation using machine learning. <em>Geophysical Journal International</em>, <em>218</em>(1), 45-56. https://doi.org/10.1093/gji/ggz142</li> <li>Schuba, C.N., Gray, G.G., Morgan, J.K., Schuba, J.P., and Sawyer, D.S., (submitted). Interface targeted velocity estimation using machine learning. <em>Geochemistry, Geophysics, Geosystems.</em></li> </ul>
Crustal structure of northwestern Iran based on regional seismic tomography
<p>The tomography model presented in the paper "Crustal structure of northwestern Iran based on regional seismic tomography" are obtained using the LOTOS code by Koulakov (2009). Here, we present the full version of the code with initial data and parameters used for calculating P and S velocity models beneath the northwestern Iran. This version of the code is adopted for the Windows OS and contains the entire program listing and the full project structure for Microsoft Visual Studio 2010 and Intel Visual Fortran. Detailed description of the code can be found at <a href="http://www.ivan-art.com/science/LOTOS">www.ivan-art.com/science/LOTOS</a></p> <p>This file includes:</p> <p>1. The full folder with the LOTOS code for the passive-source seismic tomography (Koulakov, 2009, BSSA). </p> <p>2. Folder with the dataset including arrival times of the P and S waves from local seismicity in the area of NW Iran.</p> <p>3. README_NW_IRAN.PDF file with the description of the workflow on how to reproduce the tomography models based on experimental and synthetic data presented in the article. </p> <p>4. Folder SRF_FIGS with figures from the paper created in Surfer-13 that can be used as templates to visualize the results. </p> <p>Koulakov, I., 2009, LOTOS code for local earthquake tomographic inversion: Benchmarks for testing tomographic algorithms: Bulletin of the Seismological Society of America, v. 99, p. 194–214, https://doi.org/10.1785/0120080013.</p>
Velocity models from "Investigation of Martian regional crustal structure near the dichotomy using S1222a surface-wave group velocities"
<p>The isotropic velocity models from joint inversion of Rayleigh- and Love-wave group-velocity measurements of S1222a. The details about these models and the joint inversion are in "Investigation of Martian regional crustal structure near the dichotomy using S1222a surface-wave group velocities" which is submitted to GRL.</p>
The Impact of the Three-Dimensional Structure of a Subduction Zone on Time-dependent Crustal Deformation Measured by HR-GNSS
<p>Companion data set to the paper "<strong>The Impact of the </strong><strong>Three-Dimensional Structure of a Subduction Zone on Time-dependent Crustal Deformation Measured by HR-GNSS.</strong>" The 'GNSS_Stations' folder contains the GNSS stations used for 2011 <strong>M</strong>7.9 Ibaraki, 2011 <strong>M</strong>7.4 Iwate, 2011A <strong>M</strong>7.3 Miyagi and 2003 <strong>M</strong>8.3 Tokachi 2003 earthquakes. The 'Mesh' folder contains the fault geometry mesh files for the Japan Trench, including the GMSH files. The '3D_velocity_model' folder contains the 3D velocity model for the combined West and East domains of the 3D Japan Integrated Velocity Structure Model in a rfile format and the corresponding ifile format. The 'Ruptures' folder contains the projected rupture models for each earthquake on the Japan Trench mesh and the corresponding 100 realizations of the mean rupture models generated using FakeQuakes. If you use these data, please cite the associated publication:</p> <p>Fadugba, ­O. I., Sahakian, V. J., Diego Melgar, D., Rodgers, A. & Shimony, R. (2023). The Impact of the Three-Dimensional Structure of a Subduction Zone on Time-dependent Crustal Deformation Measured by HR-GNSS.</p>
A heterogenous mantle and crustal structure formed during the early differentiation of Mars
Open the record for dataset details and reuse information.
Supplemental Datafiles for the manuscript "Crustal structure of northern Borneo from VDSS: Implications for subduction termination and the tectonic reconstruction of SE Asia"
<p>Processed waveform data (windowed/filtered) from the seismic stations for the Virtual Deep Seismic Sounding (VDSS) study in northern Borneo.</p>
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