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662 results for “Seismicity”
USGSG16AP00094: Developing a seismic velocity model of the central valley, northern California: model SSJD2016
<p>Seismic velocity model SSJD2016 uses earthquake travel-time, ambient noise group velocity and gravity data to update Thurber NC2009, for northern California.</p>
Development and impact analysis of ground motion datasets for potential strong-to-great seismic scenarios in Chinese mainland
<p>地震动情景数据对于评估地震灾害损失至关重要,并且是协作式多学科地震风险分析和区域灾害预防的基础要素。这项研究根据地震灾害分区数据确定了 50 个潜在的地震成因位置,并得到了地质和地震学证据的支持。根据潜在的损坏程度选择了四个震级(Mw 6.5、Mw 7.0、Mw 7.5 和 Mw 8.0),最终建立了 200 个地震情景。该数据集包括峰值地面加速度 (PGA)、峰值地面速度 (PGV) 和地震强度,是使用之前在应急响应中验证的强大 GMPE 生成的。这为灾害预防、减灾和城市规划提供了有用的支持,使其适用于许多分析需求。</p> <p><strong><em>注意: </em> 这是对高风险地震断层地震情景的模拟,旨在帮助决策者采取主动措施来减轻潜在地震的影响。它还为相关研究人员提供了一组可用的数据资源。请不要使用这些数据来生成或传播错误信息!</strong></p>
E-Supplement to the Relocation of the Seismicity in Central Asia using the Global RSTT model
<p><span>The e-Supplement contains the Ground Truth event list in the Central Asia region, as well as the relocated event bulletin in ISF2.0 format.</span></p>
Non-Poissonian Forecast and Hazard source files - New Zealand National Seismic Hazard Model 2022
<h3>This repository contains:</h3><ul><li>The forecast's files for the Distributed Seismicity Model of the NZNSHM2022, as well as figures, and the Paraview files to explore them in the software interactively. (https://www.paraview.org/)</li><li>The Openquake source files (https://github.com/gem/oq-engine) to run the NZ-NSHM2022 model using the non-Poisson forecasts as single branches.</li></ul><h3>Installation instructions</h3><p>For reproducibility, this package should install OpenQuake (https://github.com/gem/oq-engine) in its version v3.16.4. However, Openquake should remain backward compatible for the Negative Binomial formulation in the future. To install the version 3.16.4, a virtual environment can be created used Anaconda/Miniconda/Micromamba (the latter is recommended, see installation instructions https://mamba.readthedocs.io/en/latest/installation.html) by using:</p><blockquote><p><i>conda env create -f environment.yml</i></p></blockquote><p>This environment should already contain the Openquake version. If the Openquake software should be installed manually into an environment created by the user:</p><blockquote><p><i>source activate {user_env}</i></p><p><i>git clone https://github.com/gem/oq-engine --depth=1 --branch=v3.16.4</i></p><p><i>cd oq-engine</i></p><p>pip install -e .</p></blockquote><p>For additional information, please see the README.md file, or visit <a href="https://github.com/pabloitu/nz_nshm2022_nonpoisson">https://github.com/pabloitu/nz_nshm2022_nonpoisson</a></p>
Temporal Seismic Velocity Changes Associated with the Mw 6.1, May 2008 Ölfus Doublet, South Iceland: a Joint Interpretation from dv/v and GPS. Cubuk-Sabuncu-etal-Dataset
<p>The dataset for the article "Temporal Seismic Velocity Changes Associated with the Mw 6.1, May 2008 Ölfus Doublet, South Iceland: a Joint Interpretation from dv/v and GPS" by Cubuk-Sabuncu et al. is provided.</p> <p>The weather dataset is now included in version 2.</p>
Seismic profiles, migration velocities and tomographic inversion results of the deep reflection profiles in the central South China
<h1><strong>Overview</strong></h1> <p>The following set of data and scripts are meant to accompany the paper:</p> <p>Jiang, W. B., Wang, Q., Zhang, Y.Q., Dong, S.W., Ruan, Y.Q., Cui, J.J., Kuang, Z.Y., Paleoproterozoic collision to Mesozoic crustal reworking in central South China: evidence from borehole data and seismic crustal structure, Submitted to JGR: Solid Earth</p> <p>The data and scripts are intended to reproduce seismic profiles, migration velocities, and tomographic inversion results shown in the paper.</p> <p>The repository contains five directories:</p> <p><strong>./01_Seismic_Profiles/</strong> -> Four seismic profiles shown in the manuscript. (1) psdm_line01.sgy (Figure 7a); (2) psdm_line02.sgy (Figure 7b); (3) SCB_PSDM.segy (Figure 9); (4) SCB_PSTM.segy (Figure S5a).</p> <p><strong>./02_Tomographic_Data_Velocity/</strong> -> picked_traveltimes.tt, picked traveltime for the normal shots (Figure 6a). The file contains location of shots and receivers, picked traveltimes; Tomo_inv.mdl, P-wave velocity model derived from first-arrival traveltime tomography (Figure 8a); Tomo_Fx1_Fz1_ray.mdl, Ray density distribution calculated using the Vp model (Figure 8b); traveltime_data_FILE_FORMAT.pdf, this pdf file describes the format of *.tt file; mdl_data_FILE_FORMAT.pdf, this pdf file describes the format of *.mdl file.</p> <p><strong>./03_Migration_Velocity_Models/ </strong>-> Migration velocity models to produce prestack time migration profile and prestack depth migration profile. VEL_RMS.mdl, RMS velocity field used in prestack time migration (Figure S4a); VEL_INTERVAL.mdl, Interval velocity field used in prestack depth migration (Figure S4b).</p> <p><strong>./04_Bouguer_Gravity_Anomaly/ </strong>-> gravity_data.grv, the Bouguer gravity anomaly data used in 2-D gravity modelling; gravity_data_FILE_FORMAT.pdf, this pdf file describes the format of *.grv file.</p> <p><strong>./05_Scripts/</strong> -> Matlab scripts to reproduce seismic profiles, migration velocities, and tomography inversion results shown in the paper. </p>
A legacy of submarine slope failure in seismic reflection data along the active Hikurangi Margin, Aotearoa New Zealand
<p><span>We present a database that documents mass transport deposits (MTDs) in 32 marine geophysical surveys, encompassing >38,000 line-km of 2D seismic profiles. We map and characterise 737 MTDs, showing variations in size, location and style of failure, which we attribute to changes in geomorphic setting from north to south. MTDs in the northern Hikurangi margin, characterised by a high taper wedge and seamount subduction, show a broad range in size, with the highest proportion of MTDs displaying blocky or intact internal architecture. The central margin, characterised by lower wedge taper, hosts the most MTDs (51%), albeit with the thinnest (on average) and clustering within interridge basins. The southern Hikurangi margin hosts widespread submarine canyons and the largest (on average) MTDs, based on area and thickness. We demonstrate the importance of seismic archives in providing new insights into MTD preservation and discuss the bias between seafloor geomorphology and subseafloor seismic data in quantifying MTD occurrence. Our findings support the interrogation of the varied and complex causes of submarine landslides along active margins generally, as well as regions prone to cascading geohazards and landslide-induced tsunami. </span></p>
Sediment thickness of the USA from seismic receiver functions
<p>Data relating to the results of "Sediment thickness of the contiguous United States from seismic receiver functions" (submitted).</p> <p> </p> <p>Summary dataset of sediment thicknesses measured at seismic stations across the USA. Original reciever functions obtained from the IRIS EARS database. The data is provided in two formats, simple txt and geojson. Both files contain the same data. For each station, the receiver function delay time (in seconds) and two estimates of sediment thickness (in kilometres) are given.</p> <p>UPDATE v2: The addition of further stations from the BK network in California's Central Valley</p>
Seismic source location with a match field processing approach during the RESOLVE dense seismic array experiment on the Glacier d'Argentiere
<p>This deposit contains the data set we used in our paper ‘<em>Dynamic imaging of glacier structures at high-resolution using source localization with a dense seismic array</em>’. The paper is in review for GRL and a preprint can be found here: <a href="http://dx.doi.org/10.1002/essoar.10507953.1">10.1002/essoar.10507953.1</a>.</p> <p>The dataset present here contains 34 files named ‘<strong>beam_15423_jd***.h5</strong>’. These files correspond to the output of the matched field processing for each day. They are in .h5 format and we provide a matlab code (<strong>read_MFP_data.m</strong>) to read these files. These files can be read with any other language since they are in . h5.</p> <p>In linux you can use <strong>h5dump –A filename.h5</strong> and you can see the content of each files.</p> <p> </p> <p>More information on how the MFP process is conducted can be found in on the <a href="https://lecoinal.gricad-pages.univ-grenoble-alpes.fr/resolve/">website </a>dedicated to this aspect or on our paper. The whole procedure and associated codes is provided on the <a href="http://lecoinal.gricad-pages.univ-grenoble-alpes.fr/resolve/">lecoinal.gricad-pages.univ-grenoble-alpes.fr/resolve/</a>.</p> <p>We also deliver with this deposit one day of seismic data <strong><a href="https://zenodo.org/api/files/873ccbe8-814d-4202-90ae-e115aab1942d/ZO_2018_121.h5?versionId=c59d2014-a6e1-43c5-96a6-91ee9a6b89ce">ZO_2018_121.h5 </a></strong>that can be used to test our MFP process. The data corresponds to the signal measured for 24 hours at each of the 98 sensors with a sampling rate of 500 Hz. More information on these seimsic signals can be found on our <a href="https://lecoinal.gricad-pages.univ-grenoble-alpes.fr/resolve/">website </a>and the whole seimsic dataset can be found here <a href="https://seismology.resif.fr/networks/#/ZO__2018">https://seismology.resif.fr/networks/#/ZO__2018</a>. Detailed for downloading the dataset should be search on our website.</p> <p> </p> <p>Other dataset linked to this project are:</p> <ul> <li>Nanni, Ugo, Gimbert, Florent, Roux, Phillipe, & Lecointre, Albanne. (2020). DATA of "Resolving the 2D temporal evolution of subglacial water flow with dense seismic array observations." [Data set]. Zenodo. <a href="https://doi.org/10.5281/zenodo.4024660">https://doi.org/10.5281/zenodo.4024660 </a></li> <li>Nanni, Gimbert, Roux, Helmstetter, Garambois, Lecointre, Walpersdorf, Jourdain, Langlais, Laarman, Lindner, Sergenat, Vincent, & Walter. (2020). DATA of the RESOLVE Project (https://resolve.osug.fr/) [Data set]. In Seismological Research Letters (Version v0). Zenodo. <a href="https://doi.org/10.5281/zenodo.3971815">https://doi.org/10.5281/zenodo.3971815 </a></li> </ul> <p>This dataset is also linked to two other study:</p> <p><em>Observing the subglacial hydrology network and its dynamics with a dense seismic array: </em></p> <p><a href="https://doi.org/10.1073/pnas.2023757118">https://doi.org/10.1073/pnas.2023757118</a></p> <p><em>A Multi‐Physics Experiment with a Temporary Dense Seismic Array on the Argentière Glacier, French Alps: The RESOLVE Project</em></p> <p><a href="https://doi.org/10.1785/0220200280">https://doi.org/10.1785/0220200280</a></p> <p> </p> <p> </p> <p> </p> <p> </p> <p>Do not hesitate to contact us if you would like to try this approach an another dataset.</p>
Remnants of the amalgamation of the East and West Cathaysia blocks revealed by a short-period dense seismic array
<p>This is the data used to support relevant research, including the data of the teleseismic receiver function with the Gaussian factor of 10.0, which can be used to facilitate further relevant research.</p>
Reproducing nonlinear seismic response from in-situ soil dynamic parameters: application to the Delaney Park Downhole Array, Alaska
<p>The zip file named 'seismic data at DPDA.zip' contains all the seismic data used in our study.</p> <p>The DEEPSOIL file named 'ground response analysis at DPDA.dp' contains the numerical models used in our study.</p>
Two global ensemble M5.95+ seismicity models obtained from the combination of interseismic strain rates and earthquake-catalogue data
<p>Contains two global earthquake-rate forecasts developed by Bayona et al. (2021) to be prospectively evaluated by the Collaboratory for the Study of Earthquake Predictability (CSEP). The Tectonic Earthquake Activity Model (TEAM) is a geodetic-based model using Version 2.1 of the Global Strain Rate Map (GSRM2.1; Kreemer et al., 2014), while the World Hybrid Earthquake Estimates based on Likelihood scores (WHEEL) is a model obtained from a multiplicative log-linear combination of TEAM with the Smoothed Seismicity (KJSS) model of Kagan and Jackson (2011).</p> <p>Earthquake densities are expressed as number of M5.95+ events per unit 0.1<sup>o</sup> cell per year. The forecasts are stored in tab separated value files, with the following fields (the first row of data is shown as an example):</p> <table> <tbody> <tr> <td><sub>lon_min</sub></td> <td><sub>lon_max</sub></td> <td><sub>lat_min</sub></td> <td><sub>lat_max</sub></td> <td><sub>depth_min</sub></td> <td><sub>depth_max</sub></td> <td><sub>5.95</sub></td> <td><sub>6.05</sub></td> <td>...</td> </tr> <tr> <td><sub>-180.0</sub></td> <td><sub>-179.9</sub></td> <td><sub>-90.0</sub></td> <td><sub>-89.9</sub></td> <td><sub>0.0</sub></td> <td><sub>70.0</sub></td> <td><sub>4.95e-11</sub></td> <td><sub>3.97e-11</sub></td> <td>...</td> </tr> </tbody> </table> <p>Data and forecasts are described in detail in the following publications:</p> <p>Bayona, J.A., Savran, W., Strader, A., Hainzl, S., Cotton, F. and Schorlemmer, D., 2021. Two global ensemble seismicity models obtained from the combination of interseismic strain measurements and earthquake-catalogue information. <em>Geophysical Journal International</em>, <em>224</em>(3), pp.1945-1955.</p> <p>Kreemer, C., Blewitt, G. and Klein, E.C., 2014. A geodetic plate motion and Global Strain Rate Model. <em>Geochemistry, Geophysics, Geosystems</em>, <em>15</em>(10), pp.3849-3889.</p> <p>Kagan, Y.Y. and Jackson, D.D., 2011. Global earthquake forecasts. <em>Geophysical Journal International</em>, <em>184</em>(2), pp.759-776.</p>
A temporary broadband seismic array in the largest desert of China: TASTE
<p>This includes the dataset of our manuscript submitted to Seismological Research Letters entitled with <em>A temporary broadband seismic array in the largest desert of China: TASTE</em></p>
Earthquakes analyzed through the Environmental Seismic Intensity (ESI) scale
<p>The spreadsheet includes information on over 150 earthquakes that have been analyzed using the Environmental Seismic Intensity scale.</p>
Data to reproduce: "The Seismic Signature of California's Largest Earthquakes, Droughts, and Floods"
<p>Data to reproduce "The Seismic Signature of California's Largest Earthquakes, Droughts, and Floods", submitted to JGR: Solid Earth.</p>
Millstätter See seismic and core data for the publication "High-resolution calibration of seismically-induced lacustrine deposits with historical earthquake data in the Eastern Alps (Carinthia, Austria)"
<p>This dataset comprises the core data and the 3.5 kHz seismic data of Millstätter See, a lake in the Eastern European Alps, Austria. Together with a bathymetric dataset (10.5281/zenodo.5875923) and a core/seismic dataset from Wörthersee (10.5281/zenodo.5875576), this is the basis for the publication Daxer et al. "High-resolution calibration of seismically-induced lacustrine deposits with historical earthquake data in the Eastern Alps (Carinthia, Austria)".</p> <p>28 core sections (individual short cores or sections of long cores - see <em>MillstaetterSee_core_data.xlsx</em> for information) were analysed with a multi-sensor core logger (MSCL) and photographed with a smartcube camera image scanner and an ITRAX core scanner. The generated data are available in the folders <em>MSCL.zip</em> and <em>Photos.zip</em>. Some core sections were also analysed with a Malvern Mastersizer 3000 and/or CT scanning. The generated data are provided in the folders <em>Grain Size.zip </em>and<em> CT data MI17-04.zip </em>(as .dcm files).</p> <p>The seismic profiles are provided as .SGY files (<em>Seismic Pinger Data.zip</em>).</p>
Woerthersee seismic and core data for the publication "High-resolution calibration of seismically-induced lacustrine deposits with historical earthquake data in the Eastern Alps (Carinthia, Austria)"
<p>This dataset comprises the core data and the 3.5 kHz seismic data of Wörthersee, a lake in the Eastern European Alps, Austria. Together with a dataset from Millstättersee (core and seismic data: 10.5281/zenodo.5875911; bathymetric data: 10.5281/zenodo.5875923), this is the basis for the publication Daxer et al. "High-resolution calibration of seismically-induced lacustrine deposits with historical earthquake data in the Eastern Alps (Carinthia, Austria)".</p> <p>24 short cores were analysed with a multi-sensor core logger (MSCL) and photographed with a smartcube camera image scanner and an ITRAX core scanner. The generated data are available in the folders <em>MSCL.zip</em> and <em>Photos.zip</em>. Some core sections were also analysed with a Malvern Mastersizer 3000. The generated grain-size data are provided in the folder <em>Grain Size.zip</em>.</p> <p>The seismic profiles are provided as .SGY files (<em>Seismic Pinger Data.zip</em>).</p>
Archive of the analysis results of the microtremor data obtained from a seismic array with a radius of 0.58 m distributed to the participants of the blind prediction experiments for the ESG6 symposium
<p>This is a supplemental material of the paper "Array-size dependency of the upper limit wavelength normalized by array radius for the standard spatial autocorrelation method" by Ikuo Cho, published in Earth, Planets and Space. It consists of the analysis results of the microtremor data observed using a seismic array with a radius of 0.58 m, which were distributed to the participants of the blind prediction experiments in ESG6. It involves all analysis results and script files to draw Figure 1 of the paper. See the "Availability of data and materials" section of the paper to download the original observed data and analysis code. See the main text of the paper for the details of the analysis.</p>
Logs and QC information for the northern Borneo Orogeny Seismic Survey seismic network
<p>Instrument log files (mass positions + GPS offset/syncs and system information) for the northern Borneo Orogeny Seismic Survey (nBOSS) seismic network, which operated 2018–2020.<br> <br> FDSN network code: YC (<a href="https://doi.org/10.7914/SN/YC_2018">https://doi.org/10.7914/SN/YC_2018</a>).</p>
Earthquake Catalogue for: Illuminating the pre-, co-, and post-seismic phases of the 2016 M7.8 Kaikoura earthquake with 10 years of seismicity
<p><strong>0.2: Correction</strong></p> <p>This version corrects the original dataset which had some incorrect focal mechanisms. These mechanisms had incorrect rakes as a result of an error in the uncertainty calculation algorithm. The remainder of the catalogue is unchanged.</p> <p><strong>Code:</strong></p> <p>If you are looking for the code used for this project this is here: <a href="https://zenodo.org/record/5047794#.Y22Mvn5By-Y">https://zenodo.org/record/5047794#.Y22Mvn5By-Y</a> - the link in the paper appears to be wrong as of 11/11/2022.</p> <p><strong>Description</strong></p> <p>Earthquake catalogue generated around the rupture area of the 2016 M7.8 Kaikoura earthquake. For a full description see the associated paper submitted to JGR 2021.</p> <p>The catalogue is here in two forms:</p> <ol> <li>A QuakeML file with all picks, magnitudes, and locations included. This is quite a large file. When reading using ObsPy this will take a long time to read (>10 minutes), and expand in memory to > 8GB.</li> <li>A CSV file with the preferred origin and magnitude information for all events. Relocated events can be identified because they have a station count of 0: GrowClust does not return the number of stations used, whereas NonLinLoc (used for absolute locations) does.</li> </ol>
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