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106 results for “tsunami”
Near-field tsunami forecasting along the Cascadia subduction zone using rapid GNSS source models
<p>Data pertaining to the submitted work <em>Near-field tsunami forecasting along the Cascadia subduction zone using rapid GNSS source model</em> (2020) by Williamson et al. Specifically, the dataset includes (1) synthetic, generated GNSS waveforms for 1300 Cascadia rupture scenarios and (2) model outputs for every tested rapid earthquake characterization.</p>
Modeled maximum tsunami height along the south coast of Java
<p>Modeled maximum tsunami height along the south coast of Java.</p> <p>Please refer to:</p> <p>Widiyantoro, S., Gunawan, E., Muhari, A., Rawlinson, N., Mori, J., Hanifa, N.R., Susilo, S., Supendi, P., Shiddiqi, H.A., Nugraha, A. D., Putra, H. E. (2020). Seismic gaps south of Java, Indonesia: Implications for megathrust earthquakes and tsunamis, Scientific Reports (submitted).</p>
Tsunami Efficiency due to Very Slow Earthquakes
<p>Data sets of run-ups ds01</p> <p>Data set for calculated law for Tsunami Efficiency</p> <p>Tsunami Efficiency for different types of rupture </p>
Lituya Bay 1958 Tsunami – pre-event bathymetry reconstruction and 3D-numerical modelling utilizing the CFD software Flow-3D
<p>Simulation video, Model code, STL.File of the solid bodies</p>
2009 South Pacific Tsunami Simulation
<p>Videos showing simulation of the 2009 South Pacific Tsunami propagating to Samoa and South East Upolu. This simulation used a source based on original work from Lay et al. 2010 and Hossen et al. 2017.</p> <p>These videos are part of a publication on tsunami runup:</p> <p> </p>
Dataset for the paper "Wedge Plasticity and a Minimalist Dynamic Rupture Model for the 2011 Mw 9.1 Tohoku-Oki Earthquake and Tsunami" in Tectonophysics
<p>This dataset contains the Fortran source codes and input files to reproduce the results in the paper "Wedge Plasticity and a Minimalist Dynamic Rupture Model for the 2011 Mw 9.1 Tohoku-Oki Earthquake and Tsunami". Sample Matlab scripts are included to visualize the results. Model results, such as final fault slip, rupture times, stress changes on fault, final surface displacements, and moment density tensors in the wedge associated with inelastic deformation, are also included as ascii files. See readme for more details.</p>
Tsunami simulations
<p>6 simulations for Senseiver experiments on tsunami waves. The files starting with "agg" we used as testing data, the files starting with "unseen" are test data. The files ending with "_as" may be used for experiments with artifical sensors. The files ending with "_145" indicate tsunami simulations from 0 - 2 hours, and ending with "_289" indicate tsunami simulations from 2 - 4 hours.</p>
Processed dataset used for developing tsunami inundation emulators(Part-II Test Dataset)
<div> <div>This dataset is related to the main Zenodo repository: https://doi.org/10.5281/zenodo.13738078</div> <br> <div>This dataset contains some of the processed datasets covering testing datasets covering tsunami inputs and outputs (for parameters of offshore waveforms, local deformation fields and inundation depths) used in the evaluation of machine learning emulator discussed in the preprint article - "Towards Using Machine Learning Emulation for Probabilistic Inundation Mapping: Multiple Earthquake Sources and Near-field Effect with project repo - https://github.com/naveenragur/ML4SicilyTsunami/tree/ptha_emulators.</div> <br> <div>The post-processed (numpy) files for the two test locations of Catania(CT) and Siracusa(SR) are provided in compressed gzip files(.gz) typically stored in data/processed:</div> <strong>-test_dZ.tar.gz</strong> (local deformation files)</div> <div><strong>-test_d.tar.gz </strong>(inundation depth files)</div> <div><strong>-test_t.tar.gz</strong> (offshore waveform files)</div> <p>The filename follow nomenclature as below</p> <p><strong>d_CT_0.dat, dZ_CT_0.dat, dflat_CT_0.dat, dZflat_CT_0.dat, t_CT_0.dat,lat_lon_idx_CT_892.npy</strong> where the file names represent <strong>{parameter}_{site}_{size}</strong></p> <ol> <li>The first var represent parameter of the file. <ul> <li>d - 2 dimensional file for inundation depth (<strong>events </strong>x <strong>m </strong>x <strong>n</strong>)</li> <li>dZ - 2 dimensional file for local deformation( <strong>events </strong>x <strong>m</strong> x <strong>n</strong>)</li> <li>dflat - 1 dimensional flat file for inundation ( <strong>events </strong>x <strong>locations</strong>)</li> <li>dZflat - 1 dimensional flat file for local deformation( <strong>events </strong>x <strong>locations</strong>)</li> <li>t - 3 dimension offshore waveform for (<strong>events </strong>x <strong>gauges </strong>x <strong>timesteps</strong>)</li> <li>lat_lon_idx - index file for matching lat long coordinate with location indices(<strong>locations x lat x lon</strong>)</li> </ul> </li> <li>The second var represents site of the file. <ul> <li>CT - Catania</li> <li>SR - Siracusa</li> </ul> </li> <li>The third var represents number of events in the file or the selection size. <ul> <li>0,1,2,3 - represent the approx 50000 test events divided into 4 splits</li> </ul> </li> </ol> <div>More information on the attached readme, see project structure and code is available at:</div> <div><strong>https://github.com/naveenragur/ML4SicilyTsunami/tree/ptha_emulators</strong></div>
Processed dataset used for developing tsunami inundation emulators(Part-I Training Dataset and Model Weights)
<p>This dataset contains some of the processed training datasets covering tsunami inputs and outputs parameters (for offshore waveforms, local deformation fields and inundation depths used in developing a machine learning emulator discussed in the preprint article -<strong> Towards Using Machine Learning Emulation for Probabilistic Inundation Mapping: Multiple Earthquake Sources and Near-field Effects</strong> with project repo - <a href="https://github.com/naveenragur/ML4SicilyTsunami/tree/ptha_emulators.">https://github.com/naveenragur/ML4SicilyTsunami/tree/ptha_emulators.</a></p> <p>####Code####</p> <p>Source code from the above github project : <strong>ML4SicilyTsunami-NPJ2024.tar.gz</strong></p> <p>The post-processed numpy dat files for the two test location of <strong>Catania(CT) and Siracusa(SR)</strong> are provided for each variable retrieved from data/processed folder of the project as compressed gzip files(.gz):</p> <p>####Model Checkpoints#### <br>ML Model checkpoints from all training experiments.<br><strong>- outSR.tar.gz (Siracusa)</strong><br><strong>- outCT.tar.gz (Catania)</strong></p> <p>####Training Datasets####<br><strong>- t.tar.gz: </strong>Offshore waveforms for gauge sites in a 3D numpy file<br><strong>- dZ.tar.gz: </strong>Local deformation fields in 2D numpy files or reduced 1D flat files on flooded grids<br><strong>- d.tar.gz: </strong>Maximum inundation depth in 2D numpy files or reduced 1D flat files</p> <p>####Flood Mask####<br>- Identifies floodable and non-floodable areas in the domain.<br><strong> - zero_mask_SR_961.npy.gz</strong><br><strong> - zero_mask_CT_892.npy.gz</strong></p> <p>####Flood Indices####<br>Links between 2D and 1D numpy files:<br>- Indices connecting 2D (events x m x n) numpy files to flattened 1D (events x m) numpy files:<br><strong> - zero_indices_SR_961.npy.gz</strong><br><strong> - zero_indices_CT_892.npy.gz</strong><br>- Indices connecting latitude-longitude coordinates to 1D (events x m) numpy files:<br><strong> - lat_lon_idx_CT_892.npy.gz</strong><br><strong> - lat_lon_idx_SR_961.npy.gz</strong></p> <p>The filenames follow nomenclature representing <strong>{parameter}_{site}_{size}</strong></p> <ol> <li>The first var represents the parameter of the file. <ul> <li>d - 2 dimensional file for inundation depth (<strong>events </strong>x <strong>m </strong>x <strong>n</strong>)</li> <li>dZ - 2 dimensional file for local deformation( <strong>events </strong>x <strong>m</strong> x <strong>n</strong>)</li> <li>dflat - 1 dimensional flat file for inundation ( <strong>events </strong>x <strong>locations</strong>)</li> <li>dZflat - 1 dimensional flat file for local deformation( <strong>events </strong>x <strong>locations</strong>)</li> <li>t - 3 dimension offshore waveform for (<strong>events </strong>x <strong>gauges </strong>x <strong>timesteps</strong>)</li> <li>lat_lon_idx - index file for matching lat long coordinate with location indices(<strong>locations x lat x lon</strong>)</li> </ul> </li> <li>The second var represents site of the file. <ul> <li>CT - Catania</li> <li>SR - Siracusa</li> </ul> </li> <li>The third var represents number of events in the file or the selection size.<br> <ul> <li>892 - represents the training events for the file, of 4 different sizes for Catania and Siracusa each</li> </ul> </li> </ol> <div>More information on the attached readme.</div>
A deglacial hazard cascade exemplified by the landslide, tsunami and outburst flood at Elliot Creek, Southern Coast Mountains, British Columbia, Canada
<p>We describe and model the evolution of a recent landslide and outburst flood in the southern Coast Mountains, British Columbia, Canada. About 18 Mm<sup>3</sup> of rock descended 1000 m from a steep valley wall and traveled across the toe of a glacier before entering a 0.6 km<sup>2</sup> glacier lake and producing a >100-m high wave. Water overtopped the lake outlet and scoured a 10-km long channel before depositing debris on a 2 km<sup>2</sup> fan below the lake outlet. Floodwater, organic detritus, and fine sediment entered a fjord where it produced a 70-km long turbidity current and altered turbidity, water temperature, and water chemistry for weeks. The outburst flood destroyed forest and culturally significant salmon spawning and rearing habitat. Physically based models of the landslide, the displacement wave, and the flood provide real-time simulations of the event and can improve understanding of similar hazard cascades and the risk they pose.</p>
Experimental modelling of tsunamis generated by pyroclastic density currents: the effects of particle size distribution on wave generation
<p><strong>Data set for experimental videos modelling the entrance of a fluidised granular flow into the water.</strong></p> <p>The data set includes:</p> <ul> <li>a MATLAB script to calculated theoretical volume and density of a non-fluidised mixture.</li> <li>Properties of the fluidised granular flows on the fluidising ramp: volume, density, thickness, flow and impact Froude numbers, kinetic energy of the fluidised flows.</li> <li>Properties of the surface elevation: surface elevation at x = 1.6m away from the shoreline, velocity of the leading wave, maximum/minimum amplitudes, potential energy of the generated waves and the energy transfer between the flow and the water column.</li> <li>Properties of the underwater gravity current - displacement, velocity and thickness of the underwater velocity current.</li> <li>a MATLAB script to visualise the surface elevation.</li> </ul>
Data Set for Sandanbata et al. (2022: JGR-Solid Earth) entitled "Sub-decadal Volcanic Tsunamis Due to Submarine Trapdoor Faulting at Sumisu Caldera in the Izu-Bonin Arc"
<p><strong>Descriptions</strong></p> <p>This dataset contains supplementary materials for the following research article:</p> <ul> <li>Sandanbata, O., Watada, S., Satake, K., Kanamori, H., Rivera, L., & Zhan, Z. (2022). Sub-decadal volcanic tsunamis due to submarine trapdoor faulting at Sumisu caldera in the Izu–Bonin Arc. <em>Journal of Geophysical Research: Solid Earth</em>, 127, e2022JB024213. <a href="https://doi.org/10.1029/2022JB024213">https://doi.org/10.1029/2022JB024213</a></li> </ul> <p>We construct earthquake source models for the 2015 earthquake at Sumisu caldera in the Izu-Bonin Arc. Four source models, presented in Figures 4a, S8a, S9a, and S14a, are contained in this dataset. </p>
FIGURA 5 in Nou registre de blocs de tsunamis a la costa rocosa de Binidalí (S de Menorca, illes Balears)
FIGURA 5. Ubicació dels blocs de la zona d'estudi sobre un model en 3-D (LIDAR PNOA 2014, www.cnig.es) i representació dels valors màxims de Transport Figure. Location of the boulders of the study area on a 3-D model (LIDAR PNOA 2014, www.cnig.es) and representation of the maximum values of Transport Figure.
Supplementary movies of the dynamic rupture and tsunami models published in Ulrich et al. (2019)
<p>Supplementary movies of the dynamic rupture and tsunami models published in Ulrich et al. (2019)</p> <p>movie_Sulawesi_SR-cp.mov: Absolute slip rate (m/s) across the fault network during the earthquake. Author: Thomas Ulrich</p> <p>movie_Sulawesi_wavefield-cp.mov: Absolute slip rate (m/s) and wavefield (absolute particle velocity in m/s) across the fault network during the earthquake. Author: Thomas Ulrich</p> <p>SulawesiTanioka.mp4: Sea surface height (m) predicted by the tsunami scenario. Author: Stefan Vater</p> <p>reference: Ulrich, T., Vater, S., Madden, E. H., Behrens, J., van Dinther, Y., van Zelst, I., Fielding, E. J., Liang, C. & Gabriel, A. A. (2019). Coupled, Physics-based Modeling Reveals Earthquake Displacements are Critical to the 2018 Palu, Sulawesi Tsunami. doi: 10.31223/osf.io/3bwqa.</p>
FIGURA 8 in Nou registre de blocs de tsunamis a la costa rocosa de Binidalí (S de Menorca, illes Balears)
FIGURA 8. Representació gràfica de les columnes d'aigua o sobreelevacions necessàries (Run-up) per al desplaçament de blocs sota diferents escenaris:Rpt: arrabassament amb tsunamis,Rps:arrabassament amb temporals,Rdt:arrossegament amb tsunamis i Rdt:arrossegament amb temporal. Graphical representation of the water columns or necessary lifs (Run-up) for the movement of blocks under different scenarios:Rpt:plugging with tsunamis, Rps:plugging with storms,Rdt:dragging with tsunamis i Rdt:dragging with storms.
FIGURA 4 in Nou registre de blocs de tsunamis a la costa rocosa de Binidalí (S de Menorca, illes Balears)
FIGURA 4. Valors del Transport Figure (Scheffers & Kelletat,2003). Transport Figure values (Scheffers & Kelletat,2003).
FIGURA 7 in Nou registre de blocs de tsunamis a la costa rocosa de Binidalí (S de Menorca, illes Balears)
FIGURA 7. Relació entre la distància dels blocs al penya-segat en metres i el seu pes en tones. Relationship between the distance to the cliff of the boulders in meters and their weight in metric Tons.
FIGURA 3 in Nou registre de blocs de tsunamis a la costa rocosa de Binidalí (S de Menorca, illes Balears)
FIGURA 3. Anàlisi del temps de desplaçament pel tsunami del 21 de maig de 2003 (costa nord d'Algèria) i pel tsunami de la costa de Ligúria de 1887,amb contorns d'intervals de 10 minuts.Font:Heidarzadeh et al.(2019). Analysis of the travel time for the tsunami of May 21,2003 (North coast of Algeria) and for the tsunami of the Ligurian coast of 1887,contours of 10-minute intervals.Source:Heidarzadeh et al. (2019).
FIGURA 1 in Nou registre de blocs de tsunamis a la costa rocosa de Binidalí (S de Menorca, illes Balears)
FIGURA 1. Ubicació de la zona d'estudi, Binidalí, sud de Menorca, illes Balears. Al centre i a la esquerra,la rosa d'onatge d'aquest sector de la costa (www.puertos.es). Location of the study area in the south of Menorca, Balearic Islands. At centre-lef,the wave rose of this coastal sector (www.puertos. es).
FIGURA 6 in Nou registre de blocs de tsunamis a la costa rocosa de Binidalí (S de Menorca, illes Balears)
FIGURA 6. Relació entre l'alçada dels blocs sobre el nivell de la mar en metres i el seu pes en tones. Relationship between the height of the boulders in meters and their weight in metric Tons.
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International Brain Laboratory public data
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OpenNeuro
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