Find research datasets worth reusing

opencc-by-4.0Jun 2020View details →

Gravity modeling of the Alpine lithosphere affected by magmatism based on seismic tomography

The Southern Alpine regions have been affected by several magmatic and volcanic events between the Paleozoic and the Tertiary. This activity has undoubtedly had an important effect on the density distribution and structural setting at lithosphere scale. Combining the information from gravity field and a high-resolution seismic tomography has been carried out a new 3D lithosphere density model of the Alpine region.

opencc-by-4.0Sep 2019View details →

DETOX seismic tomography models

----------------------- DETOX tomography models ----------------------- This folder contains three tomography models, DETOX-P1, DETOX-P2 and DETOX-P3, in the following formats:  - NetCDF (dirname: grid_nc4) - VTK (dirname: vtk) - xyz-value (dirname: txt_tetrahedron) - JPEG for GPLATES, only high-velocities (dirname: GPLATES) The directories are organized as follow:   DETOX-P1 ├── GPLATES ├── grid_nc4 ├── txt_tetrahedron └── vtk DETOX-P2 ├── GPLATES ├── grid_nc4 ├── txt_tetrahedron └── vtk DETOX-P3 ├── GPLATES ├── grid_nc4 ├── txt_tetrahedron └── vtk --------------------- Citation: * Kasra Hosseini, Karin Sigloch, Maria Tsekhmistrenko, Afsaneh Zaheri, Tarje Nissen-Meyer, Heiner Igel, Global mantle structure from multifrequency tomography using P, PP and P-diffracted waves, Geophysical Journal International, Volume 220, Issue 1, January 2020, Pages 96–141, https://doi.org/10.1093/gji/ggz394

opencc-by-4.0Jan 2021View details →

Lithospheric architecture of the Paranapanema Block and adjacent nuclei using multiple-frequency P-wave seismic tomography

We provide: the tomographic model for dephts 68 to 768 km as text files, where the first column is the longitude, the second is the latitude and the third if the velocity perturbation; the proposed limits for the Paranapanema Block, Luiz Alves Craton and Rio Apa Craton as a csv file (Figure 12 of the paper), where the first column is the name of the feature, the second is the longitude and the third is the latitude; and the abstract for the paper "Lithospheric architecture of the Paranapanema Block and adjacent nuclei using multiple-frequency P-wave seismic tomography".

opencc-by-4.0Sep 2024View details →

Time-lapse electrical resistivity tomography and seismic reflection imaging of a shallow ground-water aquifer (0-50 m): Mississippi River levee seepage across the Duncan Point bar, Baton Rouge, Louisiana, U.S.A.

The electrical resisitivity raw data files are slightly processed to remove bad data points but can be inverted using tomographic inversion code.  The seismic data were assembled in Seismic Unix format, a shortened version of the SEG-Y format (Society of Exploration Geophysicists Exchange Format-Y https: //seg. org/Publications/SEG-Technical-Standards), that has the 3200-byte EBCDIC and 400-byte tape header removed. The data uploaded online (<a href="https://zenodo.org/records/14776025">https://zenodo.org/records/14776025</a>) is a CMP brute-stacked seismic section.   During data collection, shotpoint location changed proceeding along a 136-degree azimuth (south-easterly direction), and spaced every 1 m. A total of 48, horizontal-component 28-Hz nominal geophones were placed every one meter and shotpoints were located half-way between geophones. Geophones remained fixed at their locations throughout the survey and so the CMP spacing is nominally 0.5-m but fold varies linearly from a value of 1 from either side of the survey to a central maximum of 24.  The seismic source consisted of a partially buried 20-lb steel I-beam struck repeatedly on either side three times by an 8-lb sledge hammer.  Data of the same striking polarity were added in-phase in the field.  Data with opposing polarity at each shotpoint location were subtracted later to enhance SH-wave data and suppress converted SH-to-P waves. Seismic processing is minimal and consists of standard surface-wave muting, elimination of bad seismic traces, normal moveout, bandpass filtering (between 12 Hz and 50 Hz) and preliminary stacking with trace mixing every 3 CMPs.  The data were stacked with a single velocity throughout that ranged from 80 m/s (Vs) at 0.2 s, to 100 m/s at 0.35 s and reached 180 m/s at 0.5 s of two-way traveltime.

opencc-by-4.0Jul 2020View details →

Local seismic tomography of the eastern Anatolia region

The tomography model presented in the paper "Local seismic tomography of the eastern Anatolia region" 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 eastern Anatolia. 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>

opencc-by-4.0Aug 2020View details →

Local seismic tomography of the Middle Tien Shan region

The tomography model presented in the paper "Studying the depth structure of the Kyrgyz Tien Shan by using the seismic tomography and magnetotelluric sounding methods" 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 Kyrgyz Tien Shan. 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>

opencc-by-4.0Jan 2021View details →

Seismic datasets in "Conjugate fault deformation revealed by aftershocks of the 2013 Mw6.6 Lushan earthquake and seismic anisotropy tomography"

The Lushan seismic dataset used in the manuscript entitled 'Conjugate fault deformation revealed by aftershocks of the 2013 Mw6.6 Lushan earthquake and seismic anisotropy tomography ' submitted to Geophysical Research Letters.

opencc-by-4.0Nov 2022View details →

Dataset and LOTOS program code to reproduce the main results of seismic tomography for West Aegean region (Turkey)

This file contains the data to reproduce the results presented in the article: Petrov I., Bushenkova N., Gulten, P., (2023). Intracontinental extension settings in the structure of the Aegean region (Turkey): local seismic tomography study., Journal of Geodynamics.This file includes:1. The full version of the LOTOS code for the seismic tomography (Koulakov, 2009);2. Folder with the dataset including arrival times of the P and S waves and the location of network  from local seismicity in Aegean region of Tukey and it`s surroundings;3. README.PDF file with the description of how to reproduce the tomography models and datatests based on data presented in the article. 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.

opencc-by-4.0Apr 2024View details →

Upper Crustal Structure of the Xinfengjiang Reservoir from Ambient Noise Double Beamforming Tomography and Its Implications for Induced Seismicity

The file "CC.tar.gz" contains the linearly stacked ZZ component cross-correlations for all station pairs. The file "Model.tar.gz" contains the 3-D upper crustal model of the Xinfengjiang Reservoir via ambient noise Double-Beamforming tomograpy.

opencc-by-4.0Sep 2024View details →

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

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. The data and software provided here are used to compute the velocity models with TomoTV. The raw data (.mseed format) can be visualised with the Python package Pyrocko/Snuffler, which was also used for the arrival time picking. 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. The same workflow was used for the picks from the permanent network. Data: - 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. - 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. - Pickfile (ManualPicks_100Nodes_Kafla2022.txt): Manual picks of the events listed in the ISOR catalogue for the evenst recorded with the temporary network. - 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...). Software (Hyp_format.py): -  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) -  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. -  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) -  Python packages needed: numpy, scipy, matplotlib, pandas, obspy

opencc-by-4.0Apr 2022View details →

Data and program codes to reproduce the results of seismic tomography for Okmok

This file contains the files to reproduce the results presented in the article: Kasatkina, E., Koulakov I., Grapenthin, R., Izbekov, P., Larsen, J., Al Alifi, N., and Qaysi, S.I. (2022). Multiple shallow magma sources beneath the Okmok caldera as inferred from local earthquake tomography, Journal of Geophysical Research, Solid Earth. This file includes: 1. The full folder with the LOTOS code for the passive-source seismic tomography (Koulakov, 2009, BSSA).  2. Folder with the dataset including arrival times of the P and S waves from local seismicity in the area of the Okmok Caldera in Aleutian Islands. 3. README_OKMOK.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.  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.

opencc-by-4.0Sep 2022View details →

Data and program codes to reproduce the results of local earthquake seismic tomography for Tenerife Island

This file contains the files to reproduce the results presented in the article: Local earthquake seismic tomography reveals the link between the crustal structure and volcanism in Tenerife (Canary Islands) by Ivan Koulakov, Luca D'Auria, Janire Prudencio, Iván Cabrera-Pérez, Nemesio M. Pérez, Jesús M. Ibáñez, Journal of Geophysical Research, Solid Earth. This file includes: 1. The full folder with the LOTOS code for the passive-source seismic tomography (Koulakov, 2009, BSSA).  2. Folder with the dataset including arrival times of the P and S waves from local seismicity in the area of the Tenerife Island, Canary Archipelago. 3. README_TENERIFE.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.  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.

opencc-by-nd-4.0Dec 2017View details →

FIGURE 2 in Breathing of the Nevado del Ruiz volcano reservoir, Colombia, inferred from repeated seismic tomography

FIGURE 2: Ancestral biogeographic reconstruction of tropical, temperate and cosmopolitan occurrence of oribatid mites as reconstructed with ancestral character state mapping in Mesquite 3.10 using parsimony algorithms. See text for details. The tree is based on the BI phylogeny of the 18S rRNA and partial 28S rDNA (see Fig. 1).

opencc-by-4.0Oct 2024View details →

Crustal structure of northwestern Iran based on regional seismic tomography

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> This file includes: 1. The full folder with the LOTOS code for the passive-source seismic tomography (Koulakov, 2009, BSSA).  2. Folder with the dataset including arrival times of the P and S waves from local seismicity in the area of NW Iran. 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.  4. Folder SRF_FIGS with figures from the paper created in Surfer-13 that can be used as templates to visualize the results.  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.

opencc-by-4.0Aug 2021View details →

Seismic radial and azimuthal anisotropy tomography beneath Greenland and surrounding regions

Dear readers, These four files contain P-wave velocity model beneath Greenland and surrounding regions obtained by regional anisotropy tomography (Toyokuni & Zhao, 2021, ESS).  P-wave radial anisotropy (RAN) model RAN_DV0.DAT: Isotropic component (DV0) of RAN tomography -FORMAT: Latitude(deg), Longitude(deg), Depth(km), dVp0(%) RAN_AI.DAT: Anisotropic component RAN tomography -FORMAT: Longitude(deg), Latitude(deg), Depth(km), alpha(%) P-wave azimuthal anisotropy (AAN) model AAN_DV0.DAT: Isotropic component (DV0) of AAN tomography -FORMAT: Latitude(deg), Longitude(deg), Depth(km), dVp0(%) AAN_AI.DAT: Anisotropic component AAN tomography -FORMAT: Longitude(deg), Latitude(deg), Depth(km), FVD(deg), beta(%) We note that the tomography was conducted in the transformed coordinates. The details of the coordinate transformation are described in the above paper. We also note that the fast velocity direction (FVD) of the AAN model is in the transformed coordinates. Please contact us if you want any program to convert it back to the geographical coordinates. We hope it is useful to you. Kind wishes, Genti Toyokuni & Dapeng Zhao Tohoku University, Japan E-mail: toyokuni@tohoku.ac.jp Reference: Toyokuni, G. & Zhao, D. (2021). P wave tomography for 3-D radial and azimuthal anisotropy beneath Greenland and surrounding regions. Earth and Space Science, under review.

opencc-by-4.0Jul 2022View details →

Data files for 'Tan et al., (2022). Seismogenesis of the 2021 Mw 7.1 earthquake sequence near the northeastern Japan revealed by double-difference seismic tomography'

catalog.dat : the selected earthquake phase data (originated from Hi-net, https://www.hinet.bosai.go.jp/?LANG=en) station.dat : the seismic station coordinates MOD : the initial velocity models (including the grid nodes, Vp & Vp/Vs) relocation.dat : the earthquake relocations by the DD tomography Vp_model.dat, Vs_model.dat, VpVs_model.dat : the inverted 3D velocity models by DD tomography (having exactly the same layout as MOD)

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-4.0Mar 2022View details →

Coupled lithospheric deformation in the Qinling Orogen, central China: Insights from seismic reflection and surface-wave tomography

Data of geochronology of intrusive plutons and selected zircon Hf values shown in Figure S1 and the references cited

opencc-by-4.0May 2022View details →

Data and program codes to reproduce the results of seismic tomography for La Palma Island

This file contains the files to reproduce the results presented in the article: Voluminous storage and rapid magma ascent beneath La Palma revealed by seismic tomography by Luca D'Auria, Ivan Koulakov, Janire Prudencio, Iván Cabrera-Pérez, Jesús M. Ibáñez, Jose Barrancos, Rubén García-Hernández, David Martínez van Dorth, Germán D. Padilla, Monika Przeor, Victor Ortega, Pedro Hernández, Nemesio M. Peréz, Scientific Reports. This file includes: 1. The full folder with the LOTOS code for the passive-source seismic tomography (Koulakov, 2009, BSSA).  2. Folder with the dataset including arrival times of the P and S waves from local seismicity in the area of the La Palma Island, Canary Archipelago. 3. README_LA_PALMA.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.  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.