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781 results for “Earthquake”
Data and Models for "Probabilistic Imaging of Tsunamigenic Seafloor Deformation During the 2011 Tohoku-oki Earthquake"
<p><strong>Directory "waveform_data"</strong> includes 13 tsunami time series data from different instruments: TM1, TM2, KPG1, KPG2, GB801, GB802, GB803, GB804, GB806, GB807, D21401, D21413, and D21418. Each data file (*.dat) has two columns for (1) the time since earthquake initiation (min) and (2) ocean surface or seafloor displacement amplitude (m).</p> <p><strong>Directory “kin_models”</strong> includes the following:</p> <p>1. Seafloor Mesh Geometry</p> <ul> <li>The entire seafloor mesh consists of two separate parts (422 and 136 nodes each; 558 in total) due to the need to resolve potential discontinuity at the trench. The files “*Pt{1,2}-SM2.PointCoord.txt” consists of six columns for the ID, longitude (deg), latitude (deg), East (km), North (km) and depth (km) of the nodes in each triangular mesh. The E/N coordinates are calculated in UTM projection system, relative to an arbitrary reference point.</li> <li>The files “*.ClipPath.txt” includes the ID/lon/lat of mesh boundary nodes, which can be used for plotting.</li> <li>Visualization of the mesh parts are provided in PDF files.</li> <li>The file “*Total-SM2.PointCoord.txt” excludes boundary nodes and contains seafloor locations (504 nodes) that are directly used in tsunami arrival time calculations.</li> </ul> <p>2. Posterior Mean Models</p> <ul> <li>Ensemble-averaged models of seafloor displacements and uncertainty estimates, with no spatial averaging (“0R” in the file name) or with one-ring spatial averaging (“1R”). These models are shown in Figures 5 and 6 of <em>Jiang and Simons</em> (2016). The data files “posterior_mean_{0,1}R.txt” have three columns for (1) vertical seafloor displacement (m), (2) one-sigma standard deviation of displacement (m), and (3) corresponding resolution length (km). The model values (558 rows) correspond to nodes in files “*Pt{1,2}-SM2.PointCoord.txt” concatenated in sequential order.</li> <li>Tsunami arrival times (in sec) are calculated from the posterior mean values of propagation speeds, with zero sec at the earthquake epicenter. The coordinates (508 nodes) are included in geometry file “*Total-SM2.PointCoord.txt.”</li> </ul> <p><strong>Directory “kin_ensemble”</strong> includes the entire posterior model ensemble (98304 samples) in HDF5 format. Using a Linux command <em>h5dump</em> will show the following information about the contained datasets, with their names and dimensions. The main datasets are: (1) Covariance (1008×1008); (2) Data Log-likelihood (98304×1); (3) Posterior Log-likelihood (98304×1); and (4) Sample Set (98304×1008). Each model has 1008 parameters (504 for displacement and 504 for propagation speeds). The source coordinates (504 nodes) are included in geometry file "*Total-SM2-Parameter.PointCoord.txt."</p> <p><strong>Note:</strong> three different geometries files above are used for (1) posterior mean displacements (558 nodes), (2) arrival time calculation (508 nodes), and (3) source inversion models (504 nodes). </p>
Earthquake Response of Reinforced Concrete Frames with Infill and Active External Confinement: Tests and Dataset
<p>One option to retrofit reinforced concrete (RC) frames is the construction of infill walls. Many studies have shown that infill increases lateral strength and stiffness but tends to reduce drift capacity relative to bare frames. Fewer studies have quantified reductions in drift demand attributed to infills prior to failure. This report summarizes experiments designed to compare drift demands of frames with and without infill. Included data comes from two theses completed at Purdue University which focused on the dynamic response of one-third scale, non-ductile RC frames to uniaxial simulated earthquake ground motions. Tests were conducted on bare frames, frames with masonry infill walls, and frames with timber infill walls. In 11 of 14 test series, active confinement was applied to columns using external post-tensioned reinforcement</p> <p> </p> <p>This dataset summarizes two experimental programs that studied the dynamic, in-plane response of one-third scale RC frames with full-height infills and active external column confinement. Theses summarized were written by Monical (2021) and Kerby (2022), and included data from 254 in-plane dynamic tests of non-ductile RC frames with various seismic retrofits.</p>
InSAR stack of the 2019 Ridgecrest, California earthquake sequence from Sentinel-1 descending track 71 processed with ASF HyP3
<p>A stack of unwrapped interferograms on Owens Valley, California for the <a href="https://earthquake.usgs.gov/earthquakes/eventpage/ci38457511/executive">2019 Ridgecrest earthquake sequence</a>.</p> <p>Sensor: Sentinel-1 descending track 71</p> <p>Time: 2019.06.10 - 2019.08.15, 7 acquisitions, 11 interferograms</p> <p>Processor: <a href="https://hyp3-docs.asf.alaska.edu/guides/insar_product_guide/">ASF HyP3</a> (GAMMA)</p> <p>Tropospheric delay estimated from ERA-5 using PyAPS is attached.</p> <p>This is an input dataset for the time series analysis with <a href="https://github.com/insarlab/MintPy">MintPy</a>.</p>
Earthquake Connection Indicator (ECI) table for the locations of the cult of Poseidon with earthquake-related epithets in the ancient Aegean Sea region
<p>The rationale behind this table is to categorize the spatial attachment of the evidence of the earthquake-related epithets of Poseidon to earthquake proxies in the region of the ancient Aegean Sea.</p> <h2>Attributes</h2> <h3><strong>Location</strong></h3> <p>States the location of a findspot of the evidence of an earthquake-related epithet of Poseidon.</p> <h3><strong>Epithet</strong></h3> <p>Identifies a specific earthquake-related epithet of Poseidon at a particular location.</p> <h3><strong>Earthquake_connection_indicator</strong></h3> <p>Each location of the cult of Poseidon with an earthquake-related epithet is attributed with a number from 1 to 3 based on its spatial ties to earthquake proxies. Earthquake proxies consist of active fault lines (Ganas, A., I. A. Oikonomou, and C. Tsimi. 2013. ‘NOAfaults: A Digital Database for Active Faults in Greece’. Bulletin of the Geological Society of Greece 47 (2): 518–30. https://doi.org/10.12681/bgsg.11079), and locations of ancient earthquake reports (Guidoboni, Emanuela, Graziano Ferrari, Gabriele Tarabusi, Giulia Sgattoni, Alberto Comastri, Dante Mariotti, Cecilia Ciuccarelli, Maria Giovanna Bianchi, and Gianluca Valensise. 2019. ‘CFTI5Med, the New Release of the Catalogue of Strong Earthquakes in Italy and in the Mediterranean Area’. Scientific Data 6 (1). https://doi.org/10.1038/s41597-019-0091-9; National Geophysical Data Center. 1972. ‘Global Significant Earthquake Database’. NOAA National Centers for Environmental Information. https://doi.org/10.7289/V5TD9V7K).</p> <p>ECI 1: A location with an attested cult of Poseidon with an earthquake-related epithet located more than 5 kilometers from the nearest active fault or an ancient earthquake report.</p> <p>ECI 2: A location with an attested cult of Poseidon with an earthquake-related epithet located within a 5-kilometer radius from an active fault line.</p> <p>ECI 3: A location with an attested cult of Poseidon with an earthquake-related epithet located either a) within a 5-kilometer radius from an active fault line with an ancient earthquake report anywhere along the particular fault; or b) within a 5-kilometer radius from an ancient earthquake report itself.</p> <h3><strong>Lat</strong></h3> <p>Latitude</p> <h3><strong>Long</strong></h3> <p>Longitude</p> <h3><strong>DB MAP testimony #</strong></h3> <p>ID number of a testimony of Poseidon with an earthquake-related epithet based on Bonnet C. (dir.), ERC Mapping Ancient Polytheisms 741182 (DB MAP), Toulouse 2017-2023: <a href="https://base-map-polytheisms.huma-num.fr/">https://base-map-polytheisms.huma-num.fr</a>. DOI: <a href="https://doi.org/10.34847/nkl.1e19sne6">https://doi.org/10.34847/nkl.1e19sne6.</a></p> <h3><strong>PHI ID</strong></h3> <p>IDs of inscriptions mentioning Poseidon with an earthquake-related epithet from the Searchable Greek Inscriptions (PHI, https://inscriptions.packhum.org/) as listed in the Greek Inscriptions in Space and Time dataset (GIST, Kaše, Vojtěch, Petra Heřmánková, and Adéla Sobotková. 2023. ‘GIST’. Zenodo. https://doi.org/10.5281/zenodo.10139110.). To search the ID at PHI, put the number at the end of the URL in the following format https://epigraphy.packhum.org/text/32602.</p> <h3><strong>Thely</strong></h3> <p>Indicates whether the evidence is listed in the book Thély, Ludovic. 2016. Les Grecs face aux catastrophes naturelles: savoirs, histoire, mémoire. Bibliothèque des Écoles françaises d’Athènes et de Rome : BEFAR. Athènes, Paris: École française ; diffusion De Boccard.</p>
Earthquake rupture front tracked by polarization azimuths: Codes and extra material
<p>Set of matlab codes to calculate the rupture front position and migration speed every second starting from a set of SAC files.</p> <p>delays_turkey_event.m needs as input SAC files and returns a set of figures displaying the rupture front position and migrations speed. It needs some ad-hoc functions that are contained in this repository. </p> <p>list_of_accelerometers.txt contains the list of instruments processed in the code. </p> <p>turkey_section.py plots the seismic section of a subset of instruments located on or close the East Anatolian Fault line slipped during the Mw 7.8 2023 Kahramanmaraş earthquake.</p> <p>For all details, see Palo and Zollo, Small-scale segmented fault rupture along the East Anatolian Fault during the 2023 Kahramanmaraş earthquake, <em>Commun Earth Environ, 2024. </em>Uploaded files .fig correspond to the source figures of the graphs included in this paper. </p> <p> </p>
Map of Co-Seismic Landslides for the M 7.8 Kaikoura, New Zealand Earthquake
<p>Prepared by the Research Group on Earthquake Geology in Greece (http://eqgeogr.weebly.com/)</p> <p>Version 2 (updated)</p> <p>With the release of new Sentinel-2 images, and other available resources for the M7.8 Kaikoura earthquake, we present an update of the Map of Co-Seismic Landslides and Surfaces Ruptures (As of 27/11/2016). Landslides were mapped using Sentinel-2 satellite images from Copernicus, European Space Agency, dated November and December 2016. Images were visually compared with previous last available S2A images without cloud cover (13 September and 26 October) and landslides and large slope failures were manually mapped. Areas covered by cloud are omitted and shown on map. 5875 landslide sites are shown in the map. A small number of landslides could have been mis-identified due to insufficient resolution of the images, small gaps of cloud cover or for other reasons. Also, re-activated landslides on the central mountainous area were unabled to identify due to imagery restrictions (medium resolution, relief shadows etc). Some local gaps in Sentinel imagery still exist due to cloud cover, but we believe the current map is very close to the major distribution of mass movement effects. Surface ruptures were mapped using Sentinel-2 imagery and approximate position from photos of the post-earthquake aerial surveys of Environment Canterbury Regional Council (http://ecan.govt.nz)</p> <p>KML file contains7355 landslide spots.</p>
Differential Interferogram of the September 16 2018 Mw 5.3 earthquake Lake Muir, Perth, Australia
<p>A moderate earthquake of Mw 5.3 (M<sub>L</sub> 5.7) occured on September 16 2018 near the Lake Muir region, Perth, SW Australia. Despite Australia being in a mostly stable continental interior, moderate or strong shallow crustral earthquakes occured the past years. Due to shallow faulting and low relief/semi-arid conditions in most regions of Australia, even moderate events lead to surficial deformation in form of mapped surface ruptures or deformation identified by radar satellites (InSAR).</p> <p>The Sep.16 earthquake produced a distinctive surficial deformation pattern, identified in an interferometric pair of Sentinel-1 Copernicus radar images (Descending orbit, September 14 - September 26). Sentinel-1 TOPS Interferogram and Line-of-Sight (LOS) displacement were produced using SNAP and DIAPASON tools in the <a href="https://geohazards-tep.eo.esa.int">Geohazards Exploitation Platform</a>. Color fringes on interferogram represent each a ~2.8cm displacement. Displacement (unwrapped) grid files are also provided.</p> <p>InSAR analysis show co-seismic rupture along a NNE-SSW reverse fault plane, consistent with published moment tensors (USGS). LOS profiles show a 5-15cm displacement across a fault rupture that propagated to the surface. Hundreds of metres of fractures and surface ruptures were reported by local farmers' accounts and photographs to the ABC South West Australia news agency.</p>
Surface deformation of the Mw 6.4 and Mw 7.1 Ridgecrest earthquakes measured from subpixel correlation of Copernicus Sentinel-2 optical images
<p>Surface deformation of the Mw 6.4 and Mw 7.1 Ridgecrest earthquakes measured from subpixel correlation of Copernicus Sentinel-2 optical images </p>
Data for the seismological studies on the 2017 MW5.5 Pohang earthquake
<p><strong># written by J.-U. Woo</strong><br> Data includes [1] cut seismogram provided from the Korea Meteorological Administration (KMA), Korea Institute of Geoscience and Mineral Resources (KIGAM), and Korea Hydro & Nuclear Power (KHNP), [2] an example of waveform cross-correlation, [3] phase arrival times, [4] cross-correlation measurements, and [5-7] three earthquake catalogs (1-3).</p> <p><strong>Suggested citation:</strong><br> <strong>1</strong>. J.‐U. Woo, M. Kim, D.‐H. Sheen, T.‐S. Kang, J. Rhie, F. Grigoli, W.L. Ellsworth, D. Giardini, 2019, An In‐Depth Seismological Analysis Revealing a Causal Link Between the 2017 M<sub>W</sub> 5.5 Pohang Earthquake and EGS Project, JGR solid earth, doi:10.1029/2019JB018368.</p> <p><strong>Further suggested citations:</strong></p> <p><strong>2</strong>. W.L. Ellsworth, D. Giardini, J. Townend, S. Ge, and T. Shimamoto, 2019, Triggering of the Pohang, Korea, Earthquake (Mw 5.5) by Enhanced Geothermal System Stimulation. Seismological Research Letters, 90(5), 1844-1858.</p> <p><strong>3</strong>. K.-K. Lee, W.L. Ellsworth, D. Giardini, J. Townend, S. Ge, T. Shimamoto, I.-W. Yeo, T.-S. Kang, J. Rhie, D.-H. Sheen, C. Chang, J.-U. Woo, C. Langenbruch, 2019, Managing injection-induced seismic risks. Science, 364(6442), 730-732.</p> <p><strong>4</strong>. C. Langenbruch, W. L. Ellsworth, J.-U. Woo and D. J. Wald, 2020, Value at Induced Risk: Injection-induced seismic risk from low-probability, high-impact events. Geophysical Research Letters, 47, e2019GL085878. http://doi.org/10.1029/2019GL085878.</p> <p><strong>Descriptions:</strong><br> [1] Cut seismogram ("wf_cut.gz"): Each sac file is named as "(station name).(event ID of catalog1).(component; E/N/Z).sac".<br> - Zero-padding may be applied to some waveforms.<br> [2] An example of waveform cross-correlation ("wf_cc.gz"): See the README.txt in "wf_cc.gz" for details<br> [3] Phase arrival times ("phphase.txt"):<br> - First column: event ID of catalog1<br> - Second column: station name<br> - Third column: yyyymmddHHMMDD (year, month, day of month, hour, minute)<br> - Fourth and fifth columns: P-wave arrivals in second (N/A: non available)<br> - Sixth and seventh columns: S-wave arrivals in second (N/A: non available)<br> [4] Waveform cross-correlation data ("phcc.txt"):<br> - First column: event 1 ID<br> - Second column: event 2 ID<br> - Third column: station name<br> - Fourth column: arrival time difference between event 1 and event2. The arrival time differences should be added to the arrivals of the event 2 to make maximum cross-correlation coefficients. See the details in [2].<br> - Fifth column: waveform cross-correlation coefficient after alignment<br> - Sixth column: two letters for component (E/N/Z) & phase(P/S), repectively<br> [5] Earthquake catalog 1 ("catalog1.txt") for initial locations<br> [6] Earthquake catalog 2 ("catalog2.txt") for final locations<br> [7] Earthquake catalog 3 ("catalog3.txt") regarding to the determined focal mechanisms</p>
Supplementary Datasets for the Paper "A new view of seismicity under Mt. Etna volcano, Italy, 2014-2023 from multi-scale high-precision earthquake relocations"
<p>Supplementary Datasets for the Paper <br><strong>Mapping finite-fault earthquake slip with spatial correlation between seismicity and point-source Coulomb failure stress change </strong><br>by Anthony Lomax, Tiziana Tuvè, Elisabetta Giampiccolo, Ornella Cocina<br>DOI: <a href="https://doi.org/10.48550/arXiv.2404.05437" target="_blank" rel="noopener">https://doi.org/xxxx</a></p> <p><strong>20240724A_Etna_Seismicity_2014-2023_INGV-OE_NLL-SC.csv</strong> is the catalog of NLL-SC relocations presented in the paper in CSV (.csv) format.</p> <p><strong>File_S1_catalog_config_run.zip</strong> includes the relocated NLL-SC catalog in CSV (.csv) and NLL-Hypocenter (.hyp) formats, along with pick data, configuration and other files used to run the NLL-SC relocations presented in the paper.</p>
Local Earthquake Tomography of the Alpine Region from 24 Years of Data - DELIVERABLES
<h1><strong>Local Earthquake Tomography of the Alpine Region from 24 Years of Data</strong></h1> <p>M. Bagagli(1), I. Molinari(2), T. Diehl(3), E. Kissling(4)</p> <p><em>(1) Dipartimento Scienze della Terra, Università di Pisa, 56126 Pisa, Italy</em><br><em>(2) Istituto Nazionale di Geofisica e Vulcanologia, Sezione di Bologna, 40127 Bologna, Italy</em><br><em>(3) Swiss Seismological Service, ETH Zurich, 8006 Zürich, Switzerland</em><br><em>(4) Institute of Geophysics, Department of Earth Sciences, ETH Zürich, 8006 Zürich, Switzerland</em></p> <p>mail-to: matteo.bagagli@dst.unipi.it<br>date: 08.11.2024<br>version: 1.0</p> <p>-----------------------------------------------------------------------------------------------------</p> <p>This repository contains the all the deliverables of the aforementioned manuscript.<br>The folder is organized into subfolders for the relative tasks.</p> <p>- Min1D_StatDelays<br>- 3Dtomo<br>- EMSC_Catalog_May2007_Dec2015<br>- tomo2plt_scripts<br>- inventories</p> <p>For additional details, we refer the reader to the main manuscript and its supplementary materials.</p>
HR-GNSS data used in Neuro-Fuzzy Kinematic Finite-Fault Inversion: 2. Application to the Mw6.2, 24/August/2016, Amatrice Earthquake
<p>Here are the high-rate GNSS data we used to infer the low-frequency components of seismic source radiation within the M 6.2, 24/August/2016, Amatrice Earthquake. In particular, the traces are used to constrain frequencies between 0.03-0.06 Hz. This data has been used to evaluate the performance of the method, in a train/test split procedure, described in the manuscript. We upload data here to comply with AGU Fair data policy (https://www.agu.org/Publish-with-AGU/Publish/Author-Resources/Policies/Data-policy)</p> <p>Please find the pre-print of the manuscript from the ESSOAR (<a href="https://doi.org/10.1002/essoar.10504341.1">https://doi.org/10.1002/essoar.10504341.1</a>).</p> <p>Notice that the complete set of data are reposited on INGV FTP server: ftp://gpsfree.gm.ingv.it/amatrice2016/</p> <p>The data is originally processed by Avallone et al. (2016), and the detailed analysis procedure has been explained there. In the case where you used this data, please cite the original articles: </p> <p>Avallone, A., Latorre, D., Serpelloni, E., Cavaliere, A., Herrero, A., Cecere, G., ... & Selvaggi, G. (2016). Coseismic displacement waveforms for the 2016 August 24 Mw 6.0 Amatrice earthquake (central Italy) carried out from High-Rate GPS data. Annals of Geophysics, 59. (<a href="https://doi.org/10.4401/ag-7275">https://doi.org/10.4401/ag-7275</a>)</p> <p>Avallone, A., Selvaggi, G., D'Anastasio, E., D'Agostino, N., Pietrantonio, G., Riguzzi, F., ... & Zarrilli, L. (2010). The RING network: improvement of a GPS velocity field in the central Mediterranean. Annals of Geophysics, 53(2), 39-54. (<a href="https://doi.org/10.4401/ag-4549">https://doi.org/10.4401/ag-4549</a>)</p> <p> </p>
Mainshock+aftershock forecasts from Regional Earthquake Likelihood Models (RELM) experiment
<p>Contains mainshock+aftershock forecasts produced by various members of the working group for the development of Regional Earthquake Likelihood Models. These forecasts were obtained from the Collaboratory of the Study of Earthquake Predictability (CSEP) testing center hosted by the Southern California Earthquake Center at the University of Southern California.</p> <p>Forecasts are described by the following publications</p> <ol> <li>Helmstetter et al. (2007) with aftershocks</li> <li>Kagan et al. (2007)</li> <li>Shen et al. (2007)</li> <li>Bird & Liu (2007)</li> <li>Ebel et al. (2007) with aftershocks</li> </ol> <p>Forecasts are stored in tab separated value files with the following fields (the first row of data is shown as an example):</p> <pre>LON_0 LON_1 LAT_0 LAT_1 DEPTH_0 DEPTH_1 MAG_0 MAG_1 RATE FLAG -125.4 -125.3 40.1 40.2 0.0 30.0 4.95 5.05 5.8499099999999998e-04 1 </pre> <p>References</p> <p>Bird, P., and Z. Liu (2007). Seismic Hazard Inferred from Tectonics: California, Seismological Research Letters 78 37-48.</p> <p>Ebel, J. E., D. W. Chambers, A. L. Kafka, and J. A. Baglivo (2007). Non-Poissonian Earthquake Clustering and the Hidden Markov Model as Bases for Earthquake Forecasting in California, Seismological Research Letters 78 57-65.</p> <p>Helmstetter, A., Y. Y. Kagan, and D. D. Jackson (2007). High-resolution Time-independent Grid-based Forecast for M >= 5 Earthquakes in California, Seismological Research Letters 78 78-86.</p> <p>Kagan, Y. Y., D. D. Jackson, and Y. Rong (2007). A Testable Five-Year Forecast of Moderate and Large Earthquakes in Southern California Based on Smoothed Seismicity, Seismological Research Letters 78 94-98.</p> <p>Shen, Z.-K., D. D. Jackson, and Y. Y. Kagan (2007). Implications of Geodetic Strain Rate for Future Earthquakes, with a Five-Year Forecast of M5 Earthquakes in Southern California, Seismological Research Letters 78 116-120</p> <p> </p>
The Interseismic Seismicity of the East Anatolian Fault Between 2007-2012 and Aftershock Locations of the 2020 Mw6.8 Sivrice Earthquake
<p>The two files include the seismicity along the Eastern Anatolian Fault In Turkey between 2007 and 2012 and the Aftershocks of the January 24, 2020 Mw6.8 Sivrice (Elazığ) earthquake.</p>
ICP Displacement Fields from the 2016 Mw 7.8 Kaikōura Earthquake over the Papatea Fault, New Zealand
<p>Three-dimensional displacement fields produced over the Papatea Fault, South Island, New Zealand following the 2016 Mw 7.8 Kaikōura earthquake. The dataset was generated from pre- and post-event aerial image point clouds using a windowed implementation of the iterative closest point algorithm.</p> <p>Creation Date: 8/28/2021</p> <p>Authors: Colin Bloom (University of Canterbury, Christchurch, New Zealand), Tim Stahl (University of Canterbury), and Andy Howell (University of Canterbury/GNS Science, Lower Hutt, New Zealand)</p> <p>Projection: New Zealand Transverse Mercator</p> <p>Scale: 25 m/pixel</p> <p>Notes: There are three displacement directions, east, north, and vertical. Positive values represent east, north, and up in the vertical direction respectively in relation to the pre-event surface. Displacement values are in meters. Extremely high or low data values likely represent noise in the dataset.</p>
InSAR interferences and slip model related to the 2021 Maduo earthquake in Qinghai province, China
<p>The dataset includes the SAR unwrapped interferograms, and the slip model related to the 2021 Maduo earthquake on western Maduo County, Qinghai Province of China.</p> <p>SAR images:</p> <p>Sensor: Sentinel-1 A/B ascending and descending tracks interferograms, including the T099A, T026A, T172A, T106D, T004D and T033D.</p> <p>Time: 2021.05.13 - 2019.05.27, 6 radar phases images and 2 range offset images.</p> <p>Processing software: GAMMA</p> <p>Topographic data from the Shuttle Radar Topography Mission (SRTM) with a resolution of 1 arcsec were used to align the images and remove the topographic phase.</p> <p>First‐order tropospheric delays were mitigated by using the Generic Atmospheric Correction Online Service (GACOS)</p> <p>Silp Models:</p> <p>The model is generated through triangular dislocation inversion.</p> <p>The slip models is composed of two files:</p> <p> Main rupture: Slip_Maduo_Main.gmt</p> <p> Tip rupture: Slip_Maduo_Tip.gmt</p> <p>Format: GMT</p>
Catalog of Repeating Earthquakes for Northern California, 1984-2014
<p>This catalog includes 27,675 repeating earthquakes grouped in 7,713 sequences in northern California for the years 1984-2014. The repeating earthquakes were identified by a comprehensive analysis of waveform similarity, relative event location, and relative size of all earthquakes recorded by the Northern California Seismic Network (NCSN). Details can be found in:</p> <p>Waldhauser, F., & Schaff, D. P. (2021). A comprehensive search for repeating earthquakes in northern California: Implications for fault creep, slip rates, slip partitioning, and transient stress. Journal of Geophysical Research: Solid Earth, 126, e2021JB022495. https://doi.org/10.1029/2021JB022495</p> <p> </p>
Mainshock+aftershock M4.95+ seismicity forecasts derived from the Regional Earthquake Likelihood Models (RELM) and the multiplicative hybrid earthquake models developed by Rhoades et al. (2014)
<p>Contains six mainshock+aftershock seismicity forecasts developed by the Working Group of the Regional Earthquake Likelihood Models (RELM) experiment, sixteen multiplicative hybrid forecasts created by Rhoades et al. (2014), and the 2011-2020 M4.95+ ANSS earthquake catalog for California. Six additional forecast files are included to properly conduct the comparative tests implemented in the Collaboratory for the Study of Earthquake Predictability (CSEP) testing centre.</p> <p>Forecasts are stored in tab separated value files with the following fields (the first row of data is shown as an example):</p> <pre>LON_0 LON_1 LAT_0 LAT_1 DEPTH_0 DEPTH_1 MAG_0 MAG_1 RATE FLAG -125.4 -125.3 40.1 40.2 0.0 30.0 4.95 5.05 5.8499099999999998e-04 1 </pre> <p>Forecast are described in detail by the following publications:</p> <p>Bird, P., and Z. Liu (2007). Seismic Hazard Inferred from Tectonics: California. Seismological Research Letters, 78(1):37-48.</p> <p>Ebel, J. E., D. W. Chambers, A. L. Kafka, and J. A. Baglivo (2007). Non-Poissonian Earthquake Clustering and the Hidden Markov Model as Bases for Earthquake Forecasting in California. Seismological Research Letters, 78(1): 57-65.</p> <p>Helmstetter, A., Y. Y. Kagan, and D. D. Jackson (2007). High-resolution Time-independent Grid-based Forecast for M >= 5 Earthquakes in California. Seismological Research Letters, 78(1): 78-86.</p> <p>Holliday, J., Chen, C., Tiampo, K., Rundle, J., Turcotte, D., and Donnellan, A. (2007). A RELM earthquake forecast based on pattern informatics. Seismological Research Letters, 78(1):87–93.</p> <p>Kagan, Y. Y., D. D. Jackson, and Y. Rong (2007). A Testable Five-Year Forecast of Moderate and Large Earthquakes in Southern California Based on Smoothed Seismicity. Seismological Research Letters, 78(1): 94-98.</p> <p>Rhoades, D.A., Gerstenberger, M.C., Christophersen, A., Zechar, J.D., Schorlemmer, D., Werner, M.J. and Jordan, T.H., 2014. Regional earthquake likelihood models II: Information gains of multiplicative hybrids. Bulletin of the Seismological Society of America, 104(6):3072-3083.</p> <p>Shen, Z.-K., D. D. Jackson, and Y. Y. Kagan (2007). Implications of Geodetic Strain Rate for Future Earthquakes, with a Five-Year Forecast of M5 Earthquakes in Southern California. Seismological Research Letters, 78(1):116-120.</p> <p>Ward, S. (2007). Methods for evaluating earthquake potential and likelihood in and around California. Seismological Research Letters, 78(1):121–133.</p> <p>Wiemer, S. and Schorlemmer, D. (2007). ALM: An asperity-based likelihood model for California. Seismological Research Letters, 78(1):134–140.</p>
Morphotectonic indices and earthquake dataset of Batui Thrust Segment, Banggai, Indonesia
<p>To measure the tectonic activity of a region, morphotectonic, a quantitave measurement of landscapes are carried out. Combination between geological, geomorphology, and earthquake data approach are powerful source to determine process that make up mountainous landscape. The combined data are applied to Pagimana and adjacent area, Banggai, Indonesia by dividing into eight watersheds and aim the Batui Thurst as main objective. The data comprised of 8.5m vertical resolution Digital Elevation Model (DEM) and earthquakes catalog were downloaded from the open-source database and extracted using composited GIS software. We use seven morphometry indices consist of Mountain Front Sinousity (Smf), Drainage Basin: Asymmetry Factor (AF) and Transverse Topographic Symmetry (T), Hypsometric Integral (HI), Channel Sinuosity (S), Ratio of Valley Floor Width to Valley Height (Vf), Stream Length-Gradient Index (SL), and Basin Elongation Ratio (Re) and embed them on eight watersheds which taken by remote sensing. Weighing indices and watersheds matrix also calculated to define correlation between each watershed on each index. Fieldwork also carried out to ensure the presence of Batui Thrust and other related structural geology which have been developed on the Pagimana. This dataset is potentially can be used for geologist, geophysicist and geomorpher to get new insight on the forming of East Arm of Sulawesi landscape and the Banggai-Sula Microcontinent development. Beside, the urban planner and risk assessor can be easily analyze the dataset to avoid and minimize effect of the potential earthquake hazard in the future.</p>
Data to reproduce the results: Statistical power of spatial earthquake forecast tests
<p>We provide data needed to reproduce the figures from the publication titled "Statistical power of spatial earthquake forecast tests".</p>
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Allen Brain Atlas
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OpenNeuro
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