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10 results for “waveform tomography”
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>
Dataset for "WUS256: An Adjoint Waveform Tomography Model of the Crust and Upper Mantle of the Western United States for Improved Waveform Simulations"
<p>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, <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>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).</p> <p>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</p>
Dataset for 'Comparing Adjoint Waveform Tomography Models of California Using Different Starting Models'
<p>This dataset includes the three final models for 'Comparing Adjoint Waveform Tomography Models of California Using Different Starting Models.' Each model is an adjoint waveform tomography model of California and Nevada; the models begin from three separate starting models:</p> <ul> <li>CANV_CS begins with CSEM_NA (Krischer et al., 2018; <a href="https://doi.org/10.1029/2017JB015289">https://doi.org/10.1029/2017JB015289</a>)</li> <li>CANV_SP begins with SPiRaL (Simmons et al., 2021; <a href="https://doi.org/10.1093/gji/ggab277">https://doi.org/10.1093/gji/ggab277</a>)</li> <li>CANV_WUS begins with WUS256 (Rodgers et al., 2022; <a href="https://doi.org/10.1029/2022JB024549">https://doi.org/10.1029/2022JB024549</a>)</li> </ul> <p>The models are provided in both NetCDF format and HDF5 format. Figure generation codes and EventXML files for both the inversion and validation event sets can be found <a href="https://doi.org/10.5281/zenodo.7839070">here</a>.</p> <p> </p> <p><em>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.</em></p>
Dataset for "CANVAS: An adjoint waveform tomography model of California and Nevada"
<p>This dataset includes the model files for the California-Nevada Adjoint Simulations (CANVAS) adjoint waveform tomography model. The model is provided in NetCDF format. The HDF5 file provided is for importing the model into Salvus (Afanasiev et al., 2019; <a href="mondaic.com">mondaic.com</a>) An EventXML file is also provided with information on the events used to calculate the model.</p> <p> </p> <p>Information on the construction of the model can be found in the accompanying publication:</p> <p>Doody, C., Rodgers, A., Afanasiev, M., Boehm, C., Krischer, L., Chiang, A., & Simmons, N. (2023). CANVAS: An adjoint waveform tomography model of California and Nevada. <em>Journal of Geophysical Research: Solid Earth,</em> 128(12). <a href="https://doi.org/10.1029/2023JB027583">https://doi.org/10.1029/2023JB027583</a></p> <p> </p> <p><em>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-856789</em></p>
Three-dimensional crustal channel flows beneath the southeastern Tibetan Plateau revealed by full-waveform ambient noise tomography
<p>This is a new version of Vp and Vs models for paper titled "Three‐Dimensional Crustal Channel Flows Beneath the Southeastern Tibetan Plateau Revealed by Full‐Waveform Ambient Noise Tomography" published in Geophysical Research Letters.</p> <p>Modification history: new Vs model includes from surface downward to 120 km depth.</p> <p>Please ignore the models in version 1 and 2.</p>
Seismicity patterns and multi-scale imaging of Krafla (N-E) Iceland with local earthquake tomography: Raw event waveforms for all events used in the inversion and manual picks for temporary network
<p>This Data and Software were used in the submitted paper "Seismicity patterns and multi-scale imaging at Krafla (N-E Iceland) wih local earthquake tomography" by Glück et al.<br>The data and software provided here are used to compute the velocity models with TomoTV.<br>The raw data (.mseed format) can be visualised with the Python package Pyrocko/Snuffler, which was also used for the arrival time picking.<br>For the temporary network the manual picks are provided along with the code to prepare the manual picks as the input files for a localisation with NonLinLoc by weighting and quality checking the data. This resulting localsitations and the weighted traveltimes are then used for the LET.<br>The same workflow was used for the picks from the permanent network.</p> <p>Data:<br>- Raw data (\WaveformsPermanentStations): 7s waveform snippets of the events listed in the ISOR catalogue on http://lv.isor.is:8080/events/browse/ for the years 2021 and 2022.<br>- Raw data (\WaveformsNodes): 5s waveform snippets of the events listed in the ISOR catalogue on http://lv.isor.is:8080/events/browse/2022 recorded with the temporary network of 98 temporary nodes in June and July 2022.<br>- Pickfile (ManualPicks_100Nodes_Kafla2022.txt): Manual picks of the events listed in the ISOR catalogue for the evenst recorded with the temporary network.<br>- Station file (Station_file.txt): The station file includes the coordinates (Lat, Lon, Elevation) of the permanent stations (StationID starting with K...) and of the temporary nodes (StationID starting with N...).</p> <p>Software (Hyp_format.py):<br>- Weighting: The picks are weighted according to their Signal-to-Noise ratio (described in more detail in Section 2.3 in the main text of the paper)<br>- Writing the inputfile for NonLinLoc (with the selecting the mode option "PorS" in line 118), including all picks, also for those stations where not both phases were picked. The file "endfile.txt" is needed to write the picks to the NonLinLoc input format.<br>- Quality check of the picks: Computing a modified Wadati diagram from the traveltime differences of P and S phases for all the events available (with the selecting the mode option "PandS" in line 118)<br>- Python packages needed: numpy, scipy, matplotlib, pandas, obspy</p>
Waveform Data for paper "Eikonal surface-wave phase-velocity tomography of continental China"
<p>The files uploaded here contain the vertical component records of earthquakes used to measure Rayleigh wave phase velocities in continental China.</p>
Dataset for Seismic waveform tomography of the Central and Eastern Mediterranean upper mantle
<p><strong>Dataset corresponding to the Seismic waveform tomography of the Central and Eastern Mediterranean upper mantle</strong></p> <p>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.</p> <p>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.</p> <p>Here, we describe:</p> <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> <p><strong>Contents of this package</strong></p> <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> <p><strong>How to set up the data package</strong></p> <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> <p>Now the project should be ready for inspection. The following things can be done, for example:</p> <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> <p>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.</p> </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> <p><strong>References:</strong></p> <ul> <li> <p>Blom, N., Gokhberg, A., and Fichtner, A.: <strong>Seismic waveform tomography of the Central and Eastern Mediterranean upper mantle</strong>, 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.</p> </li> <li> <p>Gokhberg, A., Fichtner, A., 2016. <strong>Full-waveform inversion on heterogeneous HPC systems</strong>. 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></p> </li> <li> <p>Krischer, L., Fichtner, A., Zukauskaitė, S., and Igel, H. (2015),<strong> Large‐Scale Seismic Inversion Framework</strong>, Seismological Research Letters, 86(4), 1198–1207.<a href="http://dx.doi.org/10.1785/0220140248"> doi:10.1785/0220140248</a></p> </li> </ul>
Supplementary material "SASSIER22: Full-waveform tomography of the eastern Indonesian region that includes topography, bathymetry and the fluid ocean
<p><strong>Supplementary material “</strong><em>SASSIER22</em><strong>: Full-waveform tomography of the eastern Indonesian region that includes surface topography and the fluid ocean” by Wehner, D., Rawlinson, N., Greenfield, T., Daryono, Miller, M.S., Supendi, P., Lü, ChuanChuan and Widiyantoro, S., for publication in Geochemistry, Geophysics, Geosystems.</strong></p> <p>The material contains: </p> <p>Folder 1 <em>MODELS</em></p> <ul> <li>Absolute values of the starting model for the <em>SASSIER22</em> inversion and both final models (ocean layer — <em>SASSIER22</em> — and ocean load inversion) as NetCDFs and HDF5 files, with the former being readable by e.g. xarray and the latter suitable for viewing with ParaView and interaction with Salvus.</li> </ul> <p>Folder 2 <em>DATA</em></p> <ul> <li>The observed data (filtered and windowed) in MSEED format. Note that this data is provided for reproduction purposes only.</li> </ul> <p>The following additional information is provided in the Zenodo repository of Wehner et al. (2021), which can be found <a href="https://zenodo.org/record/5573139#.YxG4Bi8w1Hd%C2%A0">here</a>.</p> <ul> <li>A Jupyter Notebook (<em>MWE_data_processing.ipynb</em>) that demonstrates the processing steps for the observed waveforms of an event used in the <em>SASSY21</em> inversion (<em>20181229_033914</em>).</li> <li>A Jupyter Notebook (<em>embrace_the_sass.ipynb</em>) with a minimum working example on how to interact with the file formats mentioned above.</li> </ul>
waveform data of the Empirical Green's Functions (EGFs) and earthquakes for the manuscript "Unraveling the Mantle Dynamics in Central Asia with Full Waveform Inversion Tomography"
<p>The dataset uploaded contains the original ASDF files and the SAC files (with '_sac') converted from ASDF</p> <p>For the ASDF files:</p> <p>The ASDF data file could be read through python module pyasdf and obspy after decompressing. </p> <p>The earthquake information could be accessed by the following command</p> <p>import pyasdf</p> <p>ds=pyasdf.ASDFDataSet(ASDFfile, mode='r')</p> <p>event=ds.events[0].preferred_origin()</p> <p>print(event)</p> <p>the waveforms coul dbe accessed through</p> <p>stream=ds.waveforms[net.station].raw_recording</p>
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