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372 results for “Waveforms”
WaveMAP analysis of extracellular waveforms from monkey premotor cortex during decision-making
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SKS waveform data of WAVESArray in NE China
<p>This file is SAC waveform data of 20 s before and 40 s after SKS phase. It is only used for scientific research.</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>
ECLAIR superbolt waveforms
<p>The database contains 375 electric field waveforms recorded by CEA during the ECLAIR campaign from October 2012 to June 2013 which are caused by superbolt flashes.</p> <p>Each waveform is written in an ASCII file which name is the triggering date of the flash.</p> <p>Inside each file, there is four header lines followed by the data:</p> <blockquote> <p>Triggering time (UTC): 2012-12-10 11:33:35.325</p> <p>Column 1: Relative time to the triggering time (ms)</p> <p>Column 2: Electric field (V/m)</p> <p>=======================================</p> <p>-5.00001 0.00001</p> <p>...</p> </blockquote> <p> </p>
Waveform Data F08_EV_PLC_Data_V2.csv
<p>Raw waveform data. A 2 sec recording of mains voltage with EMI superimposed including a switching frequency of PV inverter (at frequency around 20 kHz) and emission of the PLC system (in the frequency range 35-90 kHz). Version 2 is Double precision.</p>
SKS waveforms
<p>This file contains data for SKS-phase splitting analysis. A total of 18 SKS waveforms in horizontal components are included.</p>
Cascadia FakeQuakes waveform data and scenario plots
<p>Supplementary data for the paper "Kinematic Rupture Scenarios and Synthetic Displacement Data: An Example Application to the Cascadia Subduction Zone<strong>" </strong>by D.Melgar, RJ Leveque, DS Dreger and RM Allen in the Journal of Geophysical Research. Cascadia.zip contains the waveforms, rupture descriptions and scenario plots. File formats are explained in fakequakes_readme.pdf</p>
FIGURE 33. A single waveform plot showing a in A revision of the Ewartia oldfieldi (Distant) species complex (Hemiptera: Cicadidae: Cicadettinae) with five new species from eastern and northern Australia
FIGURE 33. A single waveform plot showing a breakdown of two phrases of the complex mode of the calling song of Ewartia oldfieldi (Distant). This illustrates the various components that were measured for the purposes of the Non-metric Multidimensional Scaling Analysis.
Broadband waveforms for teleseismic receiver functions in the northwestern part of South America
<p>This dataset provides a comprehensive collection of teleseismic events occurring within an epicentral distance range spanning 30° to 130°, featuring a minimum magnitude threshold of Mw > 4.5. Data from 98 triaxial broadband seismological stations affiliated with three distinct seismological networks: the Colombian Geological Survey (RSNC), IRIS-PASSCAL Consortium/USGS, and Volcanological Observatories are incorporated in this dataset. These recordings span the period from 1999 to 2021. The raw waveforms are updated, these were trimmed several seconds before and after the P-wave arrival.</p><p>The dataset is systematically arranged in chronological order based on teleseismic events and is presented in the SAC format. Geospatial information pertaining to each event is encapsulated within the header file.</p>
Original waveform of TanluArray portable seismic network in the Tanlu fault zone and surrounding areas
<p>The waveform in this folder was recorded by the National Institute of Natural Hazards (NINH) (cut by catalog from 2019 and 2021). Waveform data were intercepted from the 10s before and 10s after the theoretical arrival-time of Pn. It is only used for scientific research.</p>
High-quality teleseismic waveform records of nodal seismometers in the northern Sumatra, Indonesia
<p>This dataset includes three-component teleseismic records (M≥5.5) used for receiver function calculation, waveform analysis, and imaging in Feng et al. (submitted to JGR: Solid Earth). The data are collected from the mobile seismic nodal array jointly deployed by Earth Observatory of Singapore, Singapore and Universitas Syiah Kuala, Indonesia during January 2020 to July 2021 (Lythgoe et al., 2022, https://doi.org/10.1029/2022eo220140). Please check out the readme document for detailed information.</p>
A CMOS-compatible oscillation-based VO2 Ising machine solver: Waveforms and code
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Dataset of flow rate, water temperature, radon concentration, and seismic waveforms from a hot spring system
<p>Flow rate, water temperature, radon concentration, meteorological data, and seismic waveforms in a hot spring system that used for investigating the groundwater radon changes and hydrological responses induced by large earthquakes. </p>
Current and voltage waveforms captured from a three-phase 20 kV feeder
<p>Waveforms have been captured from a incoming 20 kV feeder in the VTT MIKES building in Espoo, Finland. The file contains information of the measurement setup and data sample points recorded at approximately 6.5 kHz and 13 kHz sample rates. 64 and 32 consecutive have been respectively captured using a frequency locking sample clock. The signals can be programmed to a arbitrary function generator to produce continuous currents and voltages. Spectral content is shown based on fast Fourier transform.</p>
Imaging the northeast lobe of the Sudbury Structure through 2D and 2.5D visco-acoustic full-waveform inversion
<p>Seismic reflection profile LN182 - Northeast lobe of the Sudbury Structure. The LN182 transect comprises over 1,300 receivers (single wireless vertical-component 5-Hz geophones) and over 1,500 vibroseis sources. A linear upsweep of 5-120 Hz was generated by four vibroseis trucks forming the vibroseis source system. </p>
Global canopy top height estimates from GEDI LIDAR waveforms for 2019
<p>Canopy top height (RH98) is estimated from GEDI L1B waveforms globally between 51.6° N & S. The map is based on the first four months of L1B Version 1 data (April-July 2019). The sparse footprint level predictions are averaged at 0.5 degree resolution (approx. 55 km raster cells at the equator) to obtain a dense map. We refer to the original research article below for further information, especially on how the predictions were filtered before the aggregation.</p> <p>The footprint level RH98 predictions are stored in hdf5 files corresponding to the orbit files of the GEDI L1B Version 1 data. The file <a href="https://zenodo.org/api/files/0a9300b5-2dea-4791-a019-319ed6209713/load_pred_RH98_files.py?versionId=6af41185-f13b-44aa-9042-a59efd4abb82">load_pred_RH98_files.py </a>contains more information on how to parse and load the prediction orbit files.</p> <p><strong>GEDI mission website</strong>: <a href="https://gedi.umd.edu/">https://gedi.umd.edu/</a>.</p> <p><strong>Citation: </strong>Use of these data require citation of this dataset and the original research article. These citations are as follows:</p> <p>Lang, N., Kalischek, N., Armston, J., Schindler, K., Dubayah, R., & Wegner, J. D. (2022). Global canopy height regression and uncertainty estimation from GEDI LIDAR waveforms with deep ensembles. <em>Remote Sensing of Environment</em>, <em>268</em>, 112760.</p> <p>Lang, Nico, Kalischek, Nikolai, Armston, John, Schindler, Konrad, Dubayah, Ralph, & Wegner, Jan Dirk. (2021). Global canopy top height estimates from GEDI LIDAR waveforms for 2019 (1.1) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.5704852</p> <p> </p>
Convolutional-neural-network-based reflection-waveform inversion (major revision)
<p>This dataset is used to plot the synthetic results shown in paper: "Convolutional-neural-network-based reflection-waveform inversion"</p>
Original waveform of HAVESArray portable seismic network in Hainan Island and surrounding areas
<p>The waveform in this folder was recorded by the National Institute of Natural Hazards (NINH) (cut by catalog from 2018 and 2020). Waveform data were intercepted from the 20s before and 20s after the theoretical arrival-time of Pn. It is only used for scientific research.</p>
Waveform data for the manuscript "Varying Shear Wave Splitting Parameters Suggest Interaction between Lithosphere and Asthenosphere in Arxan-Chaihe Volcanic Field, NE China"
<p>The folder contains the seismic waveform data (in SAC format) used for shear wave splitting measurements in this study, which has been filtered with corner frequencies of 0.02–1.00 Hz. </p>
A lower mantle slab below the East Asia margin constrained by seismic waveform complexity
<p>This dataset consists of two parts: the waveforms of four events and the calculated MPD data for three of them. The waveforms for each event are recorded at the stations along the 2D profile. While the MPD data contains all the stations from the China National Seismic Network. </p>
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