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781 results for “'earthquake'”
Geometric Control on Seismic Rupture and Earthquake Sequence along the Yingxiu-Beichuan Fault with Implications for the 2008 Wenchuan Earthquak
<p>A 65000 years seismic sequence is numerical simulated using TriBIE on the unplanar fault plane with variation normal stress. The code is now available in an open-source Git-hub project, <a href="https://github.com/daisy20170101/TriBIE/tree/normal_stress_variation">https://github.com/daisy20170101/TriBIE/tree/normal_stress_variation</a>.</p> <p>The modeling will output the bianary format files of normal stress, fault slip velocity, shear stress, slip during the interseismic loading and coseismic rupture stage, respectively. Since it is impossible to output the data at every time step, especially for the large-scale fault model. Thus, during the interseismic loading, we set a constant time interval to output data and the t-inter-***.dat file will record every time, when the data is outputted. During coseimic rupture, t-cos-**.dat file records time of outputing data. So, the size of t-inter-**.dat and t-cos-**.dat file is the number of outputting steps.The fault plane is discretized into 3,1440 elements and the simulation is carried out by parallel computing on 6 servers with 120 CPUs . Each CPU will dispose data of 262 elements. </p> <p> </p> <p> </p> <p> </p> <p> </p>
Data for: Repeatability of the 20th Century Earthquake Cluster in Mongolia: Paleoseismology along the Tsetserleg Fault (Mongolia)
<p>This dataset is associated to the article "Repeatability of the 20<sup>th</sup> Century Earthquake Cluster in Mongolia: Paleoseismology along the Tsetserleg Fault (Mongolia)" submitted to Journal of Geophysical Research: Solid Earth.</p> <p>It includes the following:</p> <ul> <li>Dataset S1 includes the output of the horizontal offset measurements performed with the LaDiCaOz Matlab GUI.</li> <li>Dataset S2 includes the drone DEMs.</li> </ul>
A Composite Catalog of Damaging Earthquakes for Mainland China
<p>The Mainland China Composite Damaging Earthquake Catalog (MCCDE-CAT) was developed by Li et al. (2021). It contains three databases: Earthquake damage database, Intensity map database, Population exposure database, which for 493 damaging earthquakes that occurred in Mainland China during 1950-2019. Citation: "Y. Li, Z. Zhang, D. Xin, A Composite Catalog of Damaging Earthquakes for Mainland China, Seismol. Res. Lett. 92(6) (2021) 3767-3777. https://doi.org/10.1785/0220210090"</p> <p> </p>
Nicaragua Upper-Plate Earthquake Inversion and Static Stress Change
<p>This data set contains GPS time series and displacements (in tabular form) for the April 10 2014 and Sept 15 & 28 2016 M>5 upper-plate earthquakes in Nicaragua. The data set also contains configuration files for GBIS code, used in determining fault kinematics and Coulomb 3.3, used for calculating static stress change following the earthquakes.</p> <p>A README.txt file is in each folder and details what configuration files do and format of data.</p>
Focal mechanism solutions and relocated earthquake catalog for the Charlevoix Seismic Zone (CSZ)
<p>The relocated catalog for the CSZ (Relocated_earthquakes_CSZ.dat) represent a combination of the catalogs from Yu et al. (2016, BSSA) and Onwuemeka et al. (2018, GRL). The focal mechanism solutions catalog (FMS_CSZ.txt) includes original data combined with the solutions from Mazzotti and Townend (2010, Lithosphere). </p>
Data repository for "3D coseismic surface displacements from historical aerial photographs of the 1987 Edgecumbe earthquake, New Zealand"
<p>This data repository includes supplementary files used in the accompanying manuscript: </p> <p>Delano, J. E, Howell, A., Stahl, T. A., Clark, K. (<em>submitted 2022</em>). 3D coseismic surface displacements from historical aerial photographs of the 1987 Edgecumbe earthquake, New Zealand. Journal of Geophysical Research: Solid Earth.</p> <p>Contents:</p> <ol> <li>Supplementary Text S1, containing additional methods and discussion</li> <li>Supplementary Figures S1-S9</li> <li>Supplementary Tables S1-S6 </li> <li>Raster files (TIFF) of SfM results and differenced DSM</li> <li>Raster files of orthophoto mosaics (pre- and post-earthquake)</li> <li>Shapefiles containing fault trace mapping and displacement locations</li> </ol> <p>See README for individual file descriptions.</p>
HOBITSS earthquake catalog 2014-2015, Hikurangi margin, New Zealand
<p>We include here the full catalog of microearthquake seismicity using the Hikurangi Ocean Bottom Investigation of Tremor and Slow Slip” (HOBITSS) experiment. This catalog is part of a paper submitted to JGR in December 2018. Full catalog details are included in the main manuscript, and the results are considered preliminary until the paper is published</p> <p>Yarce2019_catalog_events.dat file has a more clean up version from the previous one, it states number of P and S phases separately and the total amount of arrivals. It also shows the time in Date Time format in addition to the epoch time format that was already in.</p> <p>[October 10, 2022] We have included the file Yarce2019_catalog_arrivals.csv that contains the arrival data of P and S wave arrivals for the events in the catalog. The last version of the catalog (v3) remained unmodified.</p>
Accelerogram (raw, msd), GLT4 seismic station (Galati, Romania), Vrancea (Romania) earthquake, 2020-04-25 01:04:18 ML=5.0 h=21.6 km
<p>Accelerogram (raw, msd) recorded at GLT4 seismic station (Galati, Romania).</p> <p>Vrancea (Romania) earthquake, 2020-04-25 01:04:18 (local time), ML=5.0, h=21.6 km.</p> <p>Recorded on a GeoSIG GMS-18 instrument.</p>
Regional velocity anomalies and slip distribution of the 2023 Kahramanmaraş, Türkiye Earthquakes
<p>dvp.dat contains columns of longitude, latitude, depth (km), and dVp (%) relative to the 1-D reference model used in https://www.mdpi.com/2076-3263/11/2/91.</p> <p>dvs.dat contains columns of longitude, latitude, depth (km) and dVs (%) relative to the 1-D reference model used in https://www.mdpi.com/2076-3263/11/2/91.</p> <p>slip_model.csv contains columns of subfault node ID, UTM Zone 37 easting (m), UTM Zone 37 northing (m), depth (m), strike (o), dip (o), strike slip (m),dip slip (m) and associated primary fault (i.e. <span>Southern East Anatolian fault (SEAF) and Savrun-Çardak-Sürgü fault (SCSF)). A</span><span> positive strike slip refers to a right-lateral slip and a positive dip slip refers to a normal slip.</span></p>
Earthquake Catalog and Phase-Picks from Gakkel Ridge Deep
<div> <p><span><span>Data Set S1:</span></span><span><span> </span></span><span> </span></p> </div> <div> <p><span><span>This data set </span><span>comprises</span><span> the catalog of manually picked events (CC=1) and new detections</span></span>.</p> <p> </p> <div> <p><span><span>Data Set S2: </span></span><span> </span></p> </div> <div> <p><span><span>Manual picks of the earthquakes that have at least 4 phase readings and are closer than </span><span>40 km</span><span> epicentral distance to one of the four recording stations. </span></span></p> </div> </div>
Data for "Slow Rupture in a Fluid-rich Fault Zone Initiated the 2024 Mw 7.5 Noto Earthquake"
<p><strong>Files for our 3D deformation maps, Back-Projection results, static slip model, and kinematic slip model for the 2024 Mw 7.5 Noto earthquake.</strong></p>
Impact of the 2011 Tohoku earthquake on the species diversity of rocky intertidal sessile assemblages
<p>The impacts of large-scale disturbance events on the species diversity of rocky intertidal sessile assemblages across multiple spatial scales are not well understood. To evaluate the influence of the 2011 Tohoku Earthquake on alpha and beta diversities of rocky intertidal sessile assemblages, we censused sessile assemblages in the mid-shore zone from 2011 to 2019. The census was conducted across 22 study sites on five rocky shores along 30 km of the Sanriku Coast of Japan, which is located 150–160 km north–northwest of the earthquake epicenter. Alpha diversity was measured with three Hill numbers (<em>H</em><sub>0</sub>, <em>H</em><sub>1</sub>, and<em> H</em><sub>2</sub>), which represent the number of equally common species that would exist in a community with the same diversity as the sampled community, with higher values of the subscript indicating more weight placed on abundant species. Beta diversity was measured with two metrics (<em>BD</em><sub>total</sub> at two spatial scales). Values were compared between the years 2011–2019 and the pre-earthquake period (2003–2010). The results show that the Tohoku Earthquake significantly altered the species diversity of intertidal sessile assemblages across multiple spatial scales. All diversity metrics obtained at multiple spatial scales (i.e., alpha diversities: <em>H</em><sub>0</sub>, <em>H</em><sub>1,</sub> and <em>H</em><sub>2</sub>; beta diversities: <em>BD<sub>t</sub></em><sub>otal</sub> at the shore and regional scales) decreased immediately after the earthquake and then increased in subsequent years. Two years after the earthquake, <em>H</em><sub>0</sub> recovered to within the range of pre-earthquake values and <em>H</em><sub>1</sub> and <em>H</em><sub>2</sub> became significantly higher than pre-earthquake values. Most metrics of alpha and beta diversities recovered to pre-earthquake levels after several years, but regional <em>BD</em><sub>total</sub> remained low for a longer period.</p>
Physics-based Simulations of 3D Wave Propagation - Case study deriving from the Le Teil earthquake
<p>This dataset contains 4,000 simulation results of the 3D elastic wave equation in a setting deriving from the Le Teil earthquake (France, 2019). The elastic wave equation governs the propagation of waves in a 3D propagation medium. Two types of data are given in this dataset: a materials dataset and a velocity dataset.</p> <h2>Materials dataset</h2> <p>Each material describes the propagation domain used for one numerical simulation. It is built from non-stationary random fields added to the reference 1D velocity profile and corresponds to the velocity of shear waves. The minimum value is 1500m/s and the maximum is 4500m/s. All materials contain a 1800m-thick bottom layer with a constant velocity of 4500m/s. </p> <p>All materials are 3D arrays of shape 32 x 32 x 32.They correspond to a physical size of 9.6 x 9.6 x 9.6km³. </p> <h3>Practical use</h3> <p>Materials are provided as `.npy` arrays, readable with python: `a = np.load(‘materials0-1999.npy’)`<br>Each file contains 2000 materials. Therefore, `a` is of shape (2000, 32, 32, 32). Indices correspond to the material index, the x coordinate (from West to East), the y coordinate (from South to North), and the z coordinate (from bottom to top). </p> <h2>Velocity dataset</h2> <p>The velocity dataset contains the velocity wavefields simulated at the surface of each propagation domain. They have been generated by solving the 3D elastic wave equation with the high-performance computing code SEM3D based on the Spectral Element Method (https://github.com/sem3d/SEM). To each material described above corresponds one velocity field, obtained by the propagation of waves through this material.</p> <p>Velocity fields were recorded by a grid of 16 x 16 virtual sensors located at the surface of the propagation domain between 150m and 450m (600m between consecutive sensors). Each sensor records the 3-component velocity with a 100Hz sampling between 0s and 20s. </p> <p>Computational details: The computational mesh was designed with elements of size 300m and 7 Gauss-Lobato-Legendre quadrature points. It can accurately represent the propagation of waves up to 5Hz frequency. Waves were generated by a point-wise source placed at the bottom of the domain, inside the constant layer (the position of the source is 4800, 4800, -8400m). The seismic source derives from the Le Teil earthquake [Delouis et al., 2021, doi:10.5802/crgeos.78]. The seismic source is described by a moment tensor with fixed orientation (strike = 48°, dip = 45°, and rake = 88°) and amplitude (moment magnitude M0=2.47 · 10^16 N.m).</p> <h3>Practical use</h3> <p>Results are given in .feather dataframes, readable with pandas library in Python: v = pd.read_feather(‘velocity0-99.feather’). Each dataframe contains 100 simulation results. Each row of the dataframe has the following format: </p> <table> <tbody> <tr> <td>run</td> <td>field</td> <td>x</td> <td>y</td> <td>z</td> <td>0.0</td> <td>0.01</td> <td>0.02</td> <td>...</td> <td>19.98</td> <td>19.99</td> </tr> <tr> <td>12</td> <td>Veloc E</td> <td> <p>150.0</p> </td> <td>770.0</td> <td>-1.0</td> <td>0</td> <td>0</td> <td>0</td> <td>...</td> <td>1.1e-5</td> <td>1.0e-5</td> </tr> <tr> <td>12</td> <td>Veloc N</td> <td> <p>150.0</p> </td> <td>770.0</td> <td>-1.0</td> <td>0</td> <td>0</td> <td>0</td> <td>...</td> <td>3e-6</td> <td>3e-6</td> </tr> <tr> <td>12</td> <td>Veloc Z</td> <td> <p>150.0</p> </td> <td>770.0</td> <td>-1.0</td> <td>0</td> <td>0</td> <td>0</td> <td>...</td> <td>-2.6e-5</td> <td>-2.7e-5</td> </tr> <tr> <td>...</td> <td>...</td> <td>...</td> <td>...</td> <td>...</td> <td>...</td> <td>...</td> <td>...</td> <td>...</td> <td>...</td> <td>...</td> </tr> </tbody> </table> <p>where `run` indicates the index of the material used in this simulation, `field` indicates the component of the velocity field (`Veloc E` for East-West, `Veloc N` for North-South, `Veloc Z` for Vertical). `x`, `y`, `z` are the coordinates of the sensor (in meters). The next 2000 columns contain the velocity field for times 0, 0.01, …, 19.99.</p> <h1>Related work</h1> <p>This dataset was used to fine-tune a Factorized Fourier Neural Operator (F-FNO, Lehmann et al. 2024, doi:10.1016/j.cma.2023.116718) to predict ground motion wavefields from 3D geologies. The code to train the F-FNO is available at https://github.com/lehmannfa/HEMEW3D</p>
AIR-DERSL-Earthquake Feature Set
<p>The dataset covers the data and characteristics of houses damaged by five mega earthquakes. Among them, some of the pre-disaster data was disturbed by clouds and fog, and the file name was stored in the PreCloud file.</p>
Coseismic Surface Ruptures of 20 Strike-Slip Earthquakes Measured from Geodetic Imaging Data
<p>Coseismic surface displacement maps for 20 strike-slip surface rupturing earthquakes measured from radar and optical pixel tracking data. </p> <p>This dataset contains 2D and 3D surface displacement maps, fault traces, total fault-parallel slip measured from the surface displacement maps, a number of strain maps and image IDs used to generate the surface displacement maps </p>
Paleoseismology of the Northern Kongur Shan Extensional System, NE Pamir: Implications for Potential Irregular Earthquake Recurrence
<p>Data and code used in the manuscript submitted to JGR: Solid Earth, including:</p> <p>1. 0.1-m resolution DEM at the Alasai site</p> <p>2. Photomosaics of the lacustrine section and fault exposure</p> <p>3. Dataset on earthquake magnitude and liquefaction distance</p> <p>4. Matlab code for scarp degradation modeling</p> <p>5. Matlab code for Monte Carlo simulation of earthquake cycles</p>
Located Earthquakes Loki's Castle 2019-2020 Deployment
<div>The dataset includes information about the 6977 located events from the 2019-2020 Loki ocean bottom seismometer deplyoment (network code: 8M). The events cover the deplyoment period of 11 months and were recorded by 8 ocean bottom seismometers west of Loki's Castle hydrothermal vent field with a station spacing of 5-6 km. Earthquakes were detected using Lassie, automatically picked using PhaseNet, and partially manually re-picked. Events for location were chosen to have at least 7 P phase picks and were located using NonLinLoc with the EDT_OT inversion scheme. Amplitudes were automatically picked with SEISANs automag function. Local magnitudes were calculated using the hypocentral distance. </div>
Supplementary Data for Progressive Strain Localization with Structural Evolution of Faults and Implications for Earthquake Characteristics
<p>Fault slip measurements from geodetic imaging data (pixel offsets and InSAR) for 16 strike-slip earthquakes. </p> <p>Data columns are: Longitude, Latitude, Fault Slip (meters), 1-sigma uncertainty (meters)</p>
Supplementary Datasets and Movies for the Paper "Mapping finite-fault earthquake slip using spatial correlation between seismicity and point-source Coulomb failure stress change"
<p>Supplementary Datasets and Movies for the Paper <br><strong>Mapping finite-fault earthquake slip using spatial correlation between seismicity and point-source Coulomb failure stress change </strong><br>by Anthony Lomax</p> <p>DOI: <a href="https://doi.org/10.48550/arXiv.2404.05437" target="_blank" rel="noopener">https://doi.org/10.48550/arXiv.2404.05437</a></p> <p> </p> <p><strong>Movie S1 Animation of the 2018, Mw 7.1 Anchorage, Alaska sequence and background seismicity 2014-2022.</strong> Relocated seismicity shown for: 2014 – 2018 mainshock (light blue), 2018 mainshock – 1 month after mainshock (green), 1 month after mainshock through 2022 (light orange); large black dot indicates the Mw 7.1 mainshock hypocenter. See figure caption in main paper for more details.</p> <p><strong>Movie S2 Animation of seismicity-stress, 3D finite-faulting potential slip results the 2018 Mw 7.1 Anchorage, Alaska earthquake sequence.</strong> The high-potential portion of the seismicity-stress finite-faulting field is shown in red for west-dipping reciever faults inferred from the first 1 day of aftershocks (blue dots) after the 2018 mainshock (large black dot). See figure caption in main paper for more details.</p> <p> </p> <p><strong>CSV (.csv) and NLL-Hypocenter (.hyp) format catalogs of NLL-SSST-coherence relocations used in this study:</strong></p> <p>Parkfield_2022_NLL-SSST-coherence_20231201A.csv<br>Parkfield_2022_NLL-SSST-coherence_20231201A.hyp</p> <p>AntelopeValley_2021_NLL-SSST-coherence_20231223A.csv<br>AntelopeValley_2021_NLL-SSST-coherence_20231223A.hyp</p> <p>Anchorage_2018_NLL-SSST-coherence_20231125A.csv<br>Anchorage_2018_NLL-SSST-coherence_20231125A.hyp</p> <p> </p>
Rectangular and Triangular Slip Models of the 2021 M7.4 Maduo (China) Earthquake
<p>This repo contains</p> <ol> <li>MAT data of the Triangular Slip Model of the 2021 M7.4 Maduo (China) Earthquake;</li> <li>The corresponding MATLAB script to visualize the MAT data.</li> </ol>
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
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DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.