Find research datasets worth reusing

opencc-by-4.0Jun 2021View details →

Data for "Variation in Upper Plate Crustal and Lithospheric Mantle Structure in the Greater and Lesser Antilles from Ambient Noise Tomography"

This is the phase velocity information and the shear wave model for the g-cubed paper: "Variation in Upper Plate Crustal and Lithospheric Mantle Structure in the Greater and Lesser Antilles from Ambient Noise Tomography"

opencc-by-4.0Sep 2021View details →

Processed data and models in support of manuscript "Deciphering the state of the lower crust and upper mantle with multi-physics inversion"

Data and model files in original format used in the manuscript  "Deciphering the state of the lower crust and upper mantle with multi-physics inversion". These files are accompanied by a set of python scripts to reproduce several of the figures in the Manuscript. Please refer to the Manuscript and the included files for further information on data origin and how to use the scripts. A link will be added upon acceptance.

opencc-by-4.0Apr 2022View details →

Dataset for "WUS256: An Adjoint Waveform Tomography Model of the Crust and Upper Mantle of the Western United States for Improved Waveform Simulations"

This dataset contains the WUS256 seismic model and auxiliary data used in the creation of the model (Rodgers et al., 2022).  WUS256 is a three-dimensional model of the seismic properties of crust and upper mantle of the western United States.  The WUS256 model is provided in NetCDF format (readable by for example, xarray, Hoyer & Hamman, <a href="https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2021JB022930#jgrb55516-bib-0057">2017</a>) and HDF5 format for viewing with ParaView (Ahrens et al., <a href="https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2021JB022930#jgrb55516-bib-0002">2005</a>) and interaction with Salvus (Afanasiev et al., <a href="https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2021JB022930#jgrb55516-bib-0001">2019</a>). Also included are the earthquake source parameters for the 72 inversion events and 18 validation events in ASCII text format.  Lastly, we include a list of all waveforms used in the creation of WUS256.  This is a simple ASCII file with the event name and receiver name (composed of the network_code and station_code). This effort was support by Lawrence Livermore National Laboratory’s Laboratory Directed Research and Development project 20-ERD-008.  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-833624

opencc-by-nc-nd-4.0Aug 2023View details →

Physical link between effective viscosity and electrical resistivity for dislocation creep in upper mantle and its application in Northwest Xinjiang, China

Cross-section of electrical resistivity extracted from the preferred 3-D resistivity model from Liu (2022) Format: X (Km), Z (Km), rho (ohm-m), T (K) Notes: Temperature(T) extracted from Sun et al., 2022, available at https://doi.org/10.5281/zenodo.6459746            (lat, lon) of the ends of the profile: (,40.71,79.8300), -->, (,46.84,86.0700)

opencc-by-4.0Oct 2024View details →

Lateral Variations in Upper Mantle Discontinuities beneath Northeast China Revealed by Seismic Ambient Noise

<div>Data description:</div> <div> </div> <div>CCdata.zip:</div> <div>Re-sampling Cross-Correlation functions (4Hz) which contain three seismic arrays.</div> <div>CEA contains HL, JL, LN and NM networks. </div> <div>NECESSarray contains YP network. NECsaids contains DB network. </div> <div>All the stations are located east of 122E, between 41N and 46N. </div> <div>The cross-correlations are used to retrieved body-wave reflections from mantle transition zone discontinuities.</div> <div> </div> <div>Syntheticdata.zip:</div> <div>contains four parts: rawdata1d, rawdata2d, stackedwaveform-2d, and compare-1d</div> <div> </div> <div>rawdata1d: </div> <div>raw synthetic waveforms calculated by Qseis (Wang, 1999) after data-processings.</div> <div>H is increased from 0 to 30 km. </div> <div>The distance is 100 km.  </div> <div> </div> <div>rawdata2d: </div> <div>raw synthetic waveforms calculated by SPECFEM2D (Tromp et al., 2008).</div> <div>Three models with depressed d660 (model 1-3) and with a slab on the d660 (model 4).  </div> <div>100 receiver stations (surface), from 305 km to 1295 km in 10 km increments.</div> <div>49 vertical single-force sources (surface), from 320 km to 1280 km in 20 km increments </div> <div> </div> <div>stackedwaveform-2d:</div> <div>The final depth results with different models.</div> <div> </div> <div>compare-1d:</div> <div>The waveforms used to compare the rf and cc.</div> <div> </div> <div>Code:</div> <div>These codes can be used to make the figures of synthetic and NCFs results. </div> <div> </div> <div> </div> <div>NECsaidsDescription.docx:</div> <div>Detailed description about the NECsaids project conducted in northeast China from October, 2010 to September, 2017.</div> <div> </div> <div>station_loc.txt:</div> <div>Coordinate file (station, longitude, latitude) of the stations.</div> <div> </div> <div>Reference</div> <div>Wang, R. (1999). A simple orthonormalization method for stable and efficient computation of Green's functions. Bulletin of the Seismological Society of America, 89(3), 733-741. doi: 10.1785/BSSA0890030733</div> <div>Tromp, J., Komatitsch, D. and Liu, Q. Y. (2008). Spectral-element and adjoint methods in seismology. Commun Comput Phys 3, 1-32.</div>

opencc-by-4.0Aug 2023View details →

Upper-mantle anisotropy in the southeastern margin of the Tibetan Plateau revealed by fullwave SKS splitting intensity tomography

This dataset contains the raw 3-component 100s SKS waveforms, measured splitting intensities and our final inverted anisotropic model for SE Tibet.

opencc-by-4.0Sep 2022View details →

LaMEM source code and input files corresponding to Present‐day upper‐mantle architecture of the Alps: Insights from data‐driven dynamic modelling

This repository contains LaMEM source code and input files for the models presented in Kumar, A., Cacace, M., Scheck-Wenderoth, M., Götze, H.-J., & Kaus, B. J. P. (2022). Present-day upper-mantle architecture of the Alps: Insights from data-driven dynamic modeling. Geophysical Research Letters, 49, e2022GL099476. https://doi. org/10.1029/2022GL099476

opencc-by-4.0Mar 2019View details →

Crustal and upper mantle structure of the Tien Shan orogenic belt from full-wave ambient noise tomography

Empirical Green’s functions, phase delays and shear wave velocity model of Tien Shan

opencc-by-4.0Sep 2021View details →

Data used in: Low Velocity Zones in the Martian Upper Mantle Highlighted by Sound Velocity Measurements

Data used in   Low Velocity Zones in the Martian Upper Mantle Highlighted by Sound Velocity Measurements F. Xu1,&dagger;,&Dagger;,, N. C. Siersch1,&Dagger;, S. Gréaux2, A. Rivoldini3, H. Kuwahara2,4, N. Kondo2, N. Wehr5, N. Menguy1, Y. Kono2, Y. Higo6, A.-C. Plesa7, J. Badro5, D. Antonangeli1 1 Sorbonne Université, Muséum National d‘Histoire Naturelle, UMR CNRS 7590, Institut de Minéralogie, de Physique des Matériaux et de Cosmochimie, IMPMC, Paris, France 2 Geodynamics Research Center, Ehime University, Matsuyama, Japan 3 Royal Observatory of Belgium, Brussels, Belgium 4 Institute for Planetary Materials, Okayama University, Misasa, Tottori, Japan 5 Université de Paris, Institut de physique du globe de Paris, CNRS, Paris, France 6 Japan Synchrotron Radiation Research Institute, SPring-8, Hyogo, Japan 7 DLR Institute of Planetary Research, Berlin, Germany   Corresponding author: Daniele Antonangeli (<a href="mailto:email@address.edu)">daniele.antonangeli@upmc.fr)</a> &dagger; Current address: Department of Earth Sciences, University College London, London, United Kingdom &Dagger; Equal contributing authors

opencc-by-4.0Feb 2023View details →

Frequency-dependent mechanical properties of the Greenland upper mantle calculated using the Very Broadband Rheology calculator

Frequency-dependent mechanical properties of the Greenland upper mantle calculated using the VBRc Frequency-dependent mechanical properties of the upper mantle beneath Greenland inferred using three-dimensional Bayesian inference of mantle thermodynamic state using the Very Broadband Rheology calculator (VBRc). Mechanical properties include the complex modulus, apparent viscosity, maxwell time, and apparent lithosphere thickness. They have been calculated for two constitutive models of anelastic behaviour - master curve fit with pre-melting scaling and extended Burgers with pseudoperiod scaling. These results are described in: Paxman, G.J.G., Lau, H.C.P., Austermann, J., Holtzman, B.K., Havlin. C., (2023), Inference of the Timescale‐Dependent Apparent Viscosity Structure in the Upper Mantle Beneath Greenland, AGU Advances 4(2), doi: 10.1029/2022AV000751. All variables are contained within a single NetCDF file.

opencc-by-4.0Nov 2019View details →

Dataset for Seismic waveform tomography of the Central and Eastern Mediterranean upper mantle

Dataset corresponding to the Seismic waveform tomography of the Central and Eastern Mediterranean upper mantle This dataset belongs to the seismic waveform tomography of the Central and Eastern Mediterranean by Blom, Gokhberg and Fichtner, Solid Earth (Discussions), 2019. Seismic tomography is an inverse problem where the internal elastic structure of the Earth (the upper ~500 km) is determined from seismograms (the vibrations of the Earth as a result of earthquakes, as recorded by seismometers at the Earth's surface). This inverse problem is cast as an optimisation where the misfit between observed and synthetic seismograms is minimised: waveform tomography (often referred to as full waveform inversion or FWI). Synthetic seismograms are produced by simulating the elastic wavefield of earthquakes within the Earth. The optimisation problem is solved by iterative, deterministic, gradient-based inversion. Gradients are computed using the adjoint method, which requires one forward wavefield simulation and one adjoint wavefield simulation per earthquake used in the project. The inversion was carried out over several frequency bands, starting with the longest periods and including a progressively broader frequency band. Within each frequency band, ~10-20 iterations were carried out, totalling to a hundred iterations. Synthetic seismograms and iteration information are stored for a subset of iterations, notably those where human interaction (i.e. the selection of events / data windows) took place. Here, we describe: <ul> <li>The contents of this package</li> <li>How to set up the package such that all the data can be accessed and used, and reproduce the figures.</li> </ul> Contents of this package <ul> <li>Data that was used for the seismic waveform inversion: raw and processed seismograms, station information, earthquake information, as well as the window selection (designating the parts of the data that were actually used at each stage in the inversion) and synthetic seismograms produced during various stages of the inversion. This information is gathered in the LASIF project "EMed_full.complete.tar".</li> <li>Models and misfit development across the iterations, as well as models relating to model testing, as carried out after the inversion. This information is gathered in the tarball "MODEL_FILES.tar". Model files are both given in the ses3d ascii format (text file drho, dvsv, dvsh, dvp and block_x, block_y,  block_z) and in bundled .vtu format. Conversion to .vtu was done using the tools in SCRIPTS. These vtu files can be viewed using Paraview.</li> <li>information on the tools and code that was used to do the inversion: <ul> <li>ses3d: a seismic wave propagation spectral element code in spherical coordinates. This will run both forward and adjoint simulations. This is available publicly through the developers on <a href="https://cos.ethz.ch/software/production/ses3d.html">https://cos.ethz.ch/software/production/ses3d.html</a>. See Gokhberg & Fichtner, 2016.</li> <li>LASIF: a waveform inversion workflow managing package, where we have made small adaptations to make it suitable for our workflow. The original package is available via <a href="http://www.lasif.net">www.lasif.net</a> and on github (see Krischer et al, 2015), the modified version is added to this package as 'LASIF-master.zip'.</li> <li>LASIF_scripts: bespoke scripts in order to interact with the LASIF project and generate different types of analyses and plots that are used in the publication. This is included in the tarball 'LASIF_scripts.tar'</li> <li>SCRIPTS: containing some modified tools that were originally written for ses3d, as well as some additional tools - notably to interact with models converted to the VTK format. This is included in the tarball 'SCRIPTS.tar'</li> <li>A description of the conda environment named lasif_ext (which is used for all the data analysis), in the form of the yml file 'lasif_ext.yml'</li> </ul> </li> <li>An additional LASIF project which is used just to compute sensitivity kernels for different windows within the same trace: 'EMed_window_kernels.tar'. This is used as an example in one of the manuscript figures.</li> </ul> How to set up the data package <ol> <li>Download the entire data package. We will assume it is located in `~/Downloads/`.</li> <li>Get miniconda or anaconda if you don't have it.</li> <li>Install LASIF. This can be done using the instructions from the <a href="http://lasif.net">LASIF website</a>, but with a few adaptations, which are detailed in the lasif_ext.yml file. This amounts to the following: <ol> <li>Add the channel conda-forge to your standard channels</li> <li>Name the environment "lasif_ext"</li> <li>Manually replace the files in the LASIF source directory with those in LASIF-master.zip.</li> <li>Install the specific version of pyqt=4.11.</li> <li>Install the additional packages jupyter, vtk=7.0.0, pandas=0.23.4 (these are the ones that work for me).</li> </ol> </li> <li>Extract the LASIF_scripts.tar to the site-packages directory of your conda environment: <pre><code class="language-bash">tar -xf ~/Downloads/LASIF_scripts.tar -C [/path/to/conda/environments]/lasif_ext/lib/python2.7/site-packages/</code></pre> </li> <li>Make a project directory and extract all needed packages into it: <pre><code class="language-bash"># make project directory mkdir CEMed_project_Blometal cd CEMed_project_Blometal # extract data tarballs into it tar -xf ~/Downloads/EMed_full.complete.tar tar -xf ~/Downloads/EMed_window_kernels.tar tar -xf ~/Downloads/MODEL_FILES.tar # make scripts directory and extract scripts into it mkdir conda_stuff tar -xf ~/Downloads/SCRIPTS.tar -C conda_stuff # make data analysis directory mkdir data_analysis cd data_analysis # extract analysis tools tar -xf ~/Downloads/NPY_FILES.tar tar -xf ~/Downloads/FIGURE_SCRIPTS.tar tar -xf ~/Downloads/figs_png.tar</code></pre> </li> </ol> Now the project should be ready for inspection. The following things can be done, for example: <ul> <li>Reproduce the figures in the manuscript. All scripts for this are located in CEMed_project_Blometal/data_analysis/FIGURE_SCRIPTS/. <pre><code class="language-bash">conda activate lasif_ext cd CEMed_project_Blometal jupyter notebook</code></pre> This should open up a browser tab that shows the directory structure. Navigate to data_analysis/FIGURE_scripts and click on one of the .ipynb files to open it. If you press 'Kernel' > 'Restart kernel and run all' at the top, all cells will be launched automatically. This should work out of the box. </li> <li>Interact with the lasif project. For this, refer to the <a href="http://www.lasif.net">LASIF website</a>. Note that above jupyter notebooks do so extensively, using the lasif communicator.</li> <li>Build additional analysis tools, using the tools supplied in SCRIPTS and LASIF_scripts.</li> </ul> References: <ul> <li> Blom, N., Gokhberg, A., and Fichtner, A.: Seismic waveform tomography of the Central and Eastern Mediterranean upper mantle, Solid Earth Discuss., <a href="https://doi.org/10.5194/se-2019-152">https://doi.org/10.5194/se-2019-152</a>, in review, 2019. </li> <li> Gokhberg, A., Fichtner, A., 2016. Full-waveform inversion on heterogeneous HPC systems. Comp. & Geosci. 89, 260-268. <a href="https://doi.org/10.1016/j.cageo.2015.12.013">https://doi.org/10.1016/j.cageo.2015.12.013</a> </li> <li> Krischer, L., Fichtner, A., Zukauskaitė, S., and Igel, H. (2015), Large‐Scale Seismic Inversion Framework, Seismological Research Letters, 86(4), 1198–1207.<a href="http://dx.doi.org/10.1785/0220140248"> doi:10.1785/0220140248</a> </li> </ul>

opencc-by-4.0Aug 2023View details →

Upper-mantle anisotropy in the southeastern margin of Tibetan Plateau revealed by fullwave SKS splitting intensity tomography

This dataset contains the raw 3-component 100s SKS waveforms, measured splitting intensities and our final inverted anisotropic model for SE Tibet.

opencc-by-4.0Feb 2024View details →

Model for the paper: Cause of enigmatic upper-mantle earthquakes in central Wyoming

We use a large number of high-quality arrival-time data of local and teleseismic events to determine detailed 3-D Vp isotropic and anisotropic tomography of the crust and mantle down to 750 km depth beneath Wyoming and its adjacent areas. For details, see https://doi.org/10.1785/0220230333 This dataset contains the obtained 3-D tomographic models of isotropic P-wave velocity, azimuthal anisotropy and radial anisotropy.

opencc-by-4.0Sep 2023View details →

Data for 'Tomography of upper mantle and transition zone in Southeast Asia'

Two checkerboard results, a synthetic test and a ISC-EHB tomography result using AST method. See the readme.txt file for details.

opencc-by-4.0May 2023View details →

Mantle xenoliths used in "High P-T sound velocities of amphiboles: Implications for low-velocity anomalies in metasomatized upper mantle"

Mineral proportions in hydrous-mineral-bearing mantle xenoliths collected worldwide and their calculated sound velocities in this study.

opencc-by-4.0Aug 2022View details →

Inverted S-wave velocity model for "Anomalous radial anisotropy and its implications for upper mantle dynamics beneath South China from multimode surface wave tomography"

# Instructions for the South China velocity model dataset from multi-mode surface-wave inversion.   1. The detailas can be found at the paper: Tang Q, Sun W, Yoshizawa K, et al. Anomalous radial anisotropy and its implications for upper mantle dynamics beneath South China from multimode surface wave tomography. Journal of Geophysical Research: Solid Earth, 2022, 127(8): e2021JB023485.   2. The relative SV-wave and SH-wave velocity models at different depths (from 0 to 300 km) are stored in the "data" foder. Each file follows the name convention: shear_{SV/SH}.{depth}.dat representing SV or SH velocity at a given depth.   3. In each velocity file, each line have three columns: longitude (deg) latitude (deg) relative_velocity (%)   4. The reference velocity can be found in the two files "SV_velocity" and "SH_velocity", depth and velocity.   5. The relative velocity is calculated from (absolute-reference)/reference*100%. Thus one can have the absolute velocity via absolute = relative * (1+relative/100).