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82 results for “subduction zones”
Melt Focusing Along Permeability Barriers at Subduction Zones and the Location of Volcanic Arcs: Numerical models
<p>The dataset includes 2-D subduction zone models calculated by Comsol Mutiphysics®, slab geometry, subduction parameters, and the prediction results.</p> <p>Each numerical model solves the thermal structure of 31 subduction zones. The 2-D slab geometry of each subduction zone is obtained from the compilations of global subduction geometries based on earthquake catalogs Slab 1.0 and Slab2 (Hayes et al., 2012; 2018). Each slab geometry is imported in the corresponding Comsol model as a text file format. Below the point where the slab depth data is unavailable, the slab interface is simply defined as a straight line with the same dip to the bottom of the computation domain. The subduction parameters used in the models are available in Table 1.</p> <p>Using the calculated thermal structure at 30 Ma, we approximate the locations of the arc as the apices of 5 isotherms at 100°C interval within 800°C – 1200°C. The predicted arc locations from each isotherm are reported in Table 2 as the horizontal distance from the trench. The actual arc location in each model is defined as the point on the surface where the slab interface reaches the subarc slab depth <em>H</em> in Table 1 and reported as the horizontal distance from the trench in Table 2. The slab water loss depth and rate obtained from van Keken et al. (2011) are presented in Table 2. In case of the maximum temperature above the water loss depth is higher than the experimentally-derived melting condition, 800°C, we report the horizontal distance from the trench. The width of the horizontal distance of slab water loss depth is assumed as the expected melting region. </p>
Wave propagation of local earthquakess in a subduction zone
<p>The movie shows wave propagation simulations that we used to model the synthetic seismograms presented in the manuscript "Toward waveform-based characterization of slab & mantle wedge (SAM) earthquakes" by Felix Halpaap, Stéphane Rondenay, Qinya Liu, Florian Millet, Lars Ottemöller. The movie contains four panels, corresponding to four waveform simulations of earthquakes occurring (i, top left) in the mantle wedge, (ii, bottom left) on the subduction interface, (iii, top right) in the slab crust, (iv, bottom right) in the slab mantle. In the movie, the simulation runs are synchronized to show the P-wave arrival at a station vertically above the earthquake at the same time. The counter in the top left corner indicates the simulation time relative to the P-wave arrival at that station. To enhance the visibility of small-amplitude wavefronts, the color intensity of the wavefronts corresponds to a logarithmic scaling of the wavefront amplitudes, with wavefront amplitudes below 0.5 % muted. The amplitudes here correspond to the norm of the displacement vector (i.e., showing particle motion in the horizontal and vertical directions).</p>
Rheological structure and lithospheric stress interaction in the Alaska subduction zone gleaned from the 2018 Mw 7.9 oceanic crustal earthquake
<p>This repository contains the observed and modeled first 2-year timeseries of postseismic deformation at GPS sites in the best-fit model associated with the 2018 Mw 7.9 Kodiak, Alaska earthquake (Timeseries.rar), as well as the preferred afterslip on the fault (Afterslip.rar).</p>
Thermal modeling of subduction zones with prescribed and evolving 2D and 3D slab geometries data
<p>Deforming subduction zone finite element model temperature, velocity, surface and flux field data as reported in the work:</p> <p>N. Sime, C. R. Wilson and P. E. van Keken<br> Thermal modeling of subduction zones with prescribed and evolving 2D and 3D slab geometries.</p>
Data from the article "Past large earthquakes influence future strong ground motion in subduction zones".
<p>Rupture and Ground motion data (version 2) in the central zone of Chile using kinematic seismic simulation data published in https://doi.org/10.1007/s11069-024-06651-9. The rupture process is derived from coupling and geometry data incorporated into the Heterogeneous Energy-Based method (https://doi.org/10.1515/geo-2022-0522).</p> <p>A video summarizing the data and results can be found in: <a href="https://youtu.be/VDIgko7ieEY?si=U_hoXBcO3OlM6XY8">https://youtu.be/VDIgko7ieEY?si=U_hoXBcO3OlM6XY8</a> <br><br>Please note that this is a revised version where the data code has been slightly modified compared to its previous version.</p>
Catalog and moment rate function dataset of shallow VLFE southeast off the Kii Peninsula, in the Nankai subduction zone
<h2>Catalog</h2> <p>"VLFE_catalog_latestUTC" is the catalog file. Estimated origin time (JST), longitude, latitude, seismic moment, duration, seismic moment (half-value width), half-value width, Variance reduction, and estimated origin time (UTC) of each shallow VLFE are listed. </p> <p>"VLFE_catalog_SP_latestUTC" is the catalog file for shallow VLFEs evaluated via a single Küpper wavelet with various durations. </p> <h2>Inversion results</h2> <p>YYYYDDMMHHMM is the directory name of a shallow VLFE that occurred in HH:MM DD MM YYYY (JST). </p> <ul> <li>YYYYDDMMHHMM_VR.dat: spatiotemporal variation of variance reduction in inversion procedure. </li> <li>YYYYDDMMHHMM_param.stfvlf: parameter file for inversion. Station names and their weight in inversion are listed.</li> <li>YYYYDDMMHHMM_solution.png: Image file illustrating inversion result. </li> <li>YYYYDDMMHHMM_stf_optimal.sac: SAC format file for the estimated optimal moment rate function of a shallow VLFE. </li> <li>YYYYDDMMHHMM_stf_optimal.dat: ASCII format file for the estimated optimal moment rate function of a shallow VLFE. Estimation errors were evaluated from five-time simulated annealing procedures for different random seeds. </li> <li>YYYYDDMMHHMM_solution_SP.png: Image file illustrating inversion result based on the single-pulse assumption.</li> <li>YYYYDDMMHHMM_stf_optimal_SP.sac: SAC format file for the estimated optimal moment rate function of a shallow VLFE based on the single-pulse assumption.</li> <li>YYYYDDMMHHMM_stf_optimal_SP.dat: ASCII format file for the estimated optimal moment rate function of a shallow VLFE based on the single-pulse assumption.</li> </ul> <p><strong>Details for methods and results</strong></p> <p><span>Takemura, S.</span>, <span>Yabe, S.</span>, <span>Emoto, K.</span>, & <span>Baba, S.</span> (<span>2025</span>). <span>Along-dip variations in source characteristics of shallow slow earthquakes controlled by topography of subducted oceanic plate</span>. <em>Journal of Geophysical Research: Solid Earth</em>, <span>130</span>, e2024JB030751. <a href="https://doi.org/10.1029/2024JB030751">https://doi.org/10.1029/2024JB030751</a></p>
Seafloor pressure data from 2019 deployment at the Hikurangi subduction zone, New Zealand
<p>We include here hourly seafloor pressure time series (and locations) from a 2019 deployment at the Hikurangi subduction zone, used in "Using seafloor geodesy to detect vertical deformation at the Hikurangi subduction zone: insights from self-calibrating pressure sensors and ocean general circulation models", a paper submitted to JGR: Solid Earth in January 2022.</p> <p><strong>APG_hikurangi_2019.json/.mat: </strong>Seafloor pressure time series data (JSON and MATLAB format) from a deployment at the Hikurangi subduction zone in 2019. The files contain the hourly time series in datetime (UTC) and pressure in hectopascals, with the convention that a decrease in pressure is equivalent to a reduction in the height of the water column (seafloor uplift).</p> <p>The only processing that has been applied to the data is filtering using a 2-day corner lowpass filter for all sites, and the A-0-A correction for the POBS sensors (which are therefore drift corrected). All APGs not equipped with A-0-A still contain sensor drift. Each time series has been adjusted using the mean of the absolute data, which is why the time series for the sites plot about zero - amplitude has been preserved.</p> <p><strong>locations_APG_hikurangi_2019.csv: </strong>Locations of the seafloor pressure sites from a deployment at the Hikurangi subduction zone in 2019. Indicated for each site are the sensor’s institute (UTIG - University of Texas Institute for Geophysics, Austin, USA; GNS Science - GNS Science, New Zealand; LDEO - Lamont-Doherty Earth Observatory, Columbia University, USA; KU - Kyoto University and Tohoku University, Japan), A-0-A drift correction capability, deployment longitude, latitude, and depth, and whether there are usable data. The sensors without usable data either contained data logger issues or were not recovered, and are not included in APG_hikurangi_2019.json/.mat.</p>
Source models for "Across-slab propagation and low stress drops of deep earthquakes in the Kuril subduction zone"
<p>This repository is for the model results for eight deep earthquakes in the Kuril subduction zone modelled using a second-degree moments method in csv format.</p> <p><a href="https://zenodo.org/api/files/ee2b378e-c4a5-4ef0-b07b-e2b2513b3236/Turner_et_al_2022_model_results_subvertical.csv">Turner_et_al_2022_model_results_subvertical.csv</a> - Source models with fixed Amin > 5 km, assuming the sub-vertical fault plane reported in the GCMT catalogue. Event is the GCMT event code. Aspect ratio is the ratio (Amin/Amax). Duration is the rupture duration; Amax is the maximum characteristic fault dimension; Amin is the minimum characteristic fault dimension; Phi is the angle between Amax and the strike; v0 is the centroid velocity; Theta is the angle between the centroid velocity and the strike; and mft is the misfit between the data and the higher-order synthetics calculated for the best-fitting source model obtained from the Monte Carlo inversions.</p> <p> </p> <p><a href="https://zenodo.org/api/files/ee2b378e-c4a5-4ef0-b07b-e2b2513b3236/Turner_et_al_2022_model_results_subvertical.csv">Turner_et_al_2022_model_results_subhorizontal.csv</a> - Source models with fixed Amin > 5 km, assuming the sub-vertical fault plane reported in the GCMT catalogue. Column headers are the same as in <a href="https://zenodo.org/api/files/ee2b378e-c4a5-4ef0-b07b-e2b2513b3236/Turner_et_al_2022_model_results_subvertical.csv">Turner_et_al_2022_model_results_subvertical.csv</a>.</p>
Dataset related to Balazs et al. The dynamics of forearc – back-arc basin subsidence: numerical models and observations from Mediterranean subduction zones
<p>Additional model data to publication by Balazs et al. The dynamics of forearc – back-arc basin subsidence: numerical models and observations from Mediterranean subduction zones</p>
Dataset for the EPSL article: Structure and dynamics of the Tonga subduction zone: new insight from P-wave anisotropic tomography
<p>The obtained 3-D P-wave anisotropic and isotropic velocity models in the Tonga subduction zone.</p> <p>Please find this article: Z. Yu*, D. Zhao and J. Li*. Structure and dynamics of the Tonga subduction zone: New insight from P-wave anisotropic tomography. Earth and Planetary Science Letters, https://doi.org/10.1016/j.epsl.2022.117844<br> </p>
Supplemental data files for: Magnetotelluric data reveals subduction polarity and reactivation of the Mudanjiang suture zone, Northeast China
<p>Data files for a 3-D electrical resistivity model in the Mudanjiang suture zone area, including the observed MT data (the data format is for 3-D inversion using ModEM), and the preferred resistivity model.</p>
Supporting Information for "Investigation of Hikurangi subduction zone slow slip events using onshore and onshore geodetic data" PhD thesis
<p>The data sets included here are those inverted using the TDEFNODE (McCaffrey et al., 2009) inversion code in the PhD thesis "Investigation of Hikurangi subduction zone slow slip events using onshore and onshore geodetic data" to obtain geodetic slip models of the 2013-2016 and February-July 2019 periods at the Hikurangi subduction zone.</p> <p> </p> <p><em>The 2013-2016 period captured the 2013 Kāpiti and 2014/2015 Manawatū slow slip events (SSEs), in addition to the 2013 Cook Strait, 2013 Lake Grassmere, and 2014 Eketāhuna earthquakes. The data related to this model are:</em></p> <p><strong>campaign_gps_2013.ts</strong><br> -campaign GPS time series<br> -columns: Year East East_sigma North North_sigma Up Up_sigma<br> -input using TDEFNODE command ts1</p> <p><strong>coseismic_displacements_2013_07_21.ds </strong><br> -coseismic displacements for Cook Strait earthquake (Hamling et al., 2014)<br> -columns: Longitude Latitude Disp_East Disp_North Sigma_East Sigma_North Site Disp_Up Sigma_Up Time1 Time2<br> -input using TDEFNODE command ds2</p> <p><strong>coseismic_displacements_2013_08_16.ds </strong><br> -coseismic displacements for Lake Grassmere earthquake (Hamling et al., 2014)<br> -columns: Longitude Latitude Disp_East Disp_North Sigma_East Sigma_North Site Disp_Up Sigma_Up Time1 Time2<br> -input using TDEFNODE command ds2</p> <p><strong>onshore_gnss_kapiti_manawatu_2013_2016.ts</strong><br> -GNSS time series<br> -columns: Year East East_sigma North North_sigma Up Up_sigma<br> -input using TDEFNODE command ts1</p> <p><strong>LOS_coseismic_2013_08_16.is<br> -</strong>coseismic Line of Sight displacements for Lake Grassmere earthquake (Hamling et al., 2014)<br> -convention: negative displacement equivalent to ground moving towards the satellite<br> -columns: Longitude Latitude LineOfSight_disp sigma Unit_x Unit_y Unit_z<br> -input using TDEFNODE command is1</p> <p> </p> <p><em>Data related to the February-July 2019 SSE model are:</em></p> <p><strong>onshore_gnss_east_coast_sse_2019.ts</strong><br> -GNSS time series<br> -columns: Year East East_sigma North North_sigma Up Up_sigma<br> -input using TDEFNODE command ts4</p> <p><strong>seafloor_displacement_gisborne.ts</strong><br> -seafloor pressure time series<br> -convention: positive change equivalent to seafloor uplift<br> -columns: Year East East_sigma North North_sigma Up Up_sigma<br> -input using TDEFNODE command ts4</p> <p><strong>seafloor_displacement_hawkebay.ts</strong><br> -seafloor pressure time series<br> -convention: positive change equivalent to seafloor uplift<br> -columns: Year East East_sigma North North_sigma Up Up_sigma<br> -input using TDEFNODE command ts4</p> <p><strong>LOS_SSE_2019.is</strong><br> -SSE-related Line of Sight displacement<br> -convention: positive displacement equivalent to ground moving away from satellite<br> -columns: Longitude Latitude LineOfSight_disp sigma Unit_x Unit_y Unit_z<br> -input using TDEFNODE command is1</p> <p> </p> <p>The TDEFNODE manual can be found here:<br> https://robmccaffrey.github.io/TDEFNODE/manual/tdefnode_manual.html</p> <p>The header lines in the time series files (.ts) take the site inter-SSE rates from the model of Wallace et al. (2012).</p> <p> </p> <p><em>References</em></p> <p>Hamling, I. J., D’Anastasio, E., Wallace, L. M., Ellis, S., Motagh, M., Samsonov, S., Palmer, N., and Hreinsdóttir, S. (2014). Crustal deformation and stress transfer during a propagating earthquake sequence: The 2013 Cook Strait sequence, central New Zealand. <em>Journal of Geophysical Research: Solid Earth</em>, <strong>119</strong>(7):6080–6092.</p> <p>McCaffrey, R. (2009). Time-dependent inversion of three-component continuous GPS for steady and transient sources in northern Cascadia. <em>Geophysical Research Letters</em>, <strong>36</strong>(L07304).</p> <p>Wallace, L. M., Barnes, P., Beavan, J., Van Dissen, R., Litchfield, N., Mountjoy, J., Langridge, R., Lamarche, G., and Pondard, N. (2012). The kinematics of a transition from subduction to strike-slip: An example from the central New Zealand plate boundary. <em>Journal of Geophysical Research: Solid Earth</em>, <strong>117</strong>(B2).</p>
Synthetic dataset of 2342 earthquake/tsunami scenarios targeting the Nankai trough subduction zone
<h2>Summary:</h2> <ul> <li>Data of 2342 hypothetical Nankai Trough events</li> <li>Tsunami propagation is simulated by the GeoClaw software (Clawpack Development Team, 2021).</li> <li>Earthquake realizations generated by the Mudpy software (Melgar, 2020).</li> <li>Data composition is as follows:<br><code>nankai_data</code><br><code>├── quakes</code><br><code>│ ├── dtopofiles</code><br><code>│ │ ├── nankai_xy_zzzzzz.dtt3</code><br><code>│ │ ├── ...</code><br><code>│ ├── png</code><br><code>│ │ ├── nankai_xy_zzzzzz_slip_dtopo.png</code><br><code>│ │ ├── ...</code><br><code>│ └── ruptures</code><br><code>│ ├── nankai_xy_zzzzzz.log</code><br><code>│ ├── nankai_xy_zzzzzz.rupt</code><br><code>│ ├── ...</code><br><code>├── waves</code><br><code>│ ├── nankai_xy_zzzzzz.csv </code><br><code>│ ├── ...</code><br><code>├── gauge_loc.csv</code><br><code>└── wave_seq.npy</code></li> </ul> <h2>Details of each file:</h2> <p>Unzipping `nankai_data.tar.gz` creates two directories and two file: `quakes/`, `waves/`, `gauge_loc.csv` and `wave_seq.npy`.<br>Note that 8 GB of additional storage is required. </p> <ul> <li> <h3>quakes/</h3> Earthquake data of 2342 scenarios. <ul> <li>quakes/dtopofiles/nankai_xy_zzzzzz.dtt3<br>Seafloor deformation of each scenario<br>Mw: x.y, ID: zzzzzz</li> <li>quakes/ruptures/<br>nankai_xy_zzzzzz.rupt stores the rupture for each scenario.<br>nankai_xy_zzzzzz.log has information about the rupture.</li> <li>quakes/png/nankai_xy_zzzzzz_slip_dtopo.png<br>The slip distribution and seafloor deformation due to fault rupture are visualized in PNG format.<br><br></li> </ul> </li> <li> <h3>waves/</h3> <p>2342 .csv files contain time series data of simulated tsunami wave heights<br>The left column has the time (minute) elapsed from the fault rupture<br>The following columns have the wave sequences recorded at each gauge<br>Each file has 2160 rows corresponding to the simulation time steps, 3 [hr] x 3600 [sec/hr] / 5[sec] = 2160.<br><br></p> </li> <li> <h3>gauge_loc_all.csv</h3> The locations of 62 synthetic gauges<br>Gauge IDs are in the left column named ID.<br>The gauge locations are in Longitude and Latitude columns.<br>Some of the synthetic gauges are set by referring to the locations of existing gauges, as shown in the Instruments column.<br><br></li> <li> <h3>wave_seq.npy</h3> Data matrix containing the wave sequences. <br> Loading this binary data by <br> numpy.load('wave_seq.npy') <br> gives a 2342 x 62 x 2160-shaped 3d array.</li> </ul> <p> </p>
Insights into subduction-zone fluid-rock interactions and carbon recycling from magnesium isotopes of subducted ophiolitic mélanges in the Arabian-Nubian Shield
<p><span>Table S1:</span><span> Major element concentrations (in wt%) and Mg isotopic compositions (‰) for the ANS subducted ophiolitic mélanges.</span></p> <p><span>Table S2: Trace element concentrations (ppm) for the ANS subducted ophiolitic mélanges.</span></p>
Catalog of Earthquake Swarms in the Middle America Subduction Zone (2001-2024)
<p>This dataset contains the catalog of earthquake swarms in the Middle America subduction zone from January 2001 to March 2024.</p>
A 3-D kinematic ThermoMechanical model of the Central Andes Subduction Zone at 18°-26°S.
<p>These files contain physical parameters obtained with the preferred thermomechanical model presented in the paper:</p> <p><strong>J. Araya Vargas, J. Sanhueza & G. Yáñez (2021). The role of temperature in the along-margin distribution of volcanism and seismicity in subduction zones: insights from 3-D thermomechanical modelling of the Central Andean margin. Tectonics, 40(11), e2021TC006879. 10.1029/2021TC006879</strong></p> <p>The README file contains a description of the files, coordinate reference system, and a summary of the modeling setup. The detailed description of the employed thermomechanical modeling methodology is provided in the main text and Supporting Information of Araya Vargas, Sanhueza & Yáñez (2021).</p> <p>FILES:</p> <p>SZAndes18s26sTMmodel_temp.csv: whole model temperature<br> SZAndes18s26sTMmodel_dP.csv: mantle flow dynamic pressure.<br> SZAndes18s26sTMmodel_vx.csv: mantle flow velocity, X-axis component.<br> SZAndes18s26sTMmodel_vy.csv: mantle flow velocity, Y-axis component.<br> SZAndes18s26sTMmodel_vz.csv: mantle flow velocity, Z-axis component.</p> <p>DATABASES FIELDS:<br> pMPa = mantle flow dynamic pressure [MPa].<br> tempC = whole model temperature [°C].<br> VXmmyr = mantle flow velocity, X-axis component [mm/yr].<br> VYmmyr = mantle flow velocity, Y-axis component [mm/yr].<br> VZmmyr = mantle flow velocity, Z-axis component [mm/yr].<br> Xkm = X-axis position [km]. World Mercator coordinate system [EPSG code: 54004].<br> Ykm = Y-axis position [km]. World Mercator coordinate system [EPSG code: 54004].<br> Zkm = Z-axis position [km]. Z-coordinate is reported as height from the mean sea level.</p>
Simulation outputs required to generate figures for "Modeling Multi-Scale Deformation Cycles in Subduction Zones with a Continuum Visco-Elastic-Brittle Framework"
<p>This file contains all of the model simulation outputs necessary to produce the figures for the paper "Modeling Multi-Scale Deformation Cycles in Subduction Zones with a Continuum Visco-Elastic-Brittle Framework".</p> <p>Below are the details of which file is required to produce which figure:</p> <p> </p> <p><strong>Figure 5 (De_dam_fields.pdf) </strong></p> <p><a href="https://zenodo.org/api/files/3150cf22-7ee4-4f5a-9cd4-b420ee0dbd91/De_dam_We_0_001_dt_10_5_th_10_10_alpha_4_ddam_10.tar.gz">De_dam_We_0_001_dt_10_5_th_10_10_alpha_4_ddam_10.tar.gz</a></p> <p> </p> <p><strong>Figure 6 (convergence.pdf)</strong></p> <p><a href="https://zenodo.org/api/files/3150cf22-7ee4-4f5a-9cd4-b420ee0dbd91/comp_dt_We_0_001_th_10_10_alpha_4_ddam10.tar.gz">comp_dt_We_0_001_th_10_10_alpha_4_ddam10.tar.gz </a></p> <p>Contains 4 files, each one for a different temporal resolution (delta t).</p> <p> </p> <p><strong>Figure C1 (convergence2.pdf, appendix)</strong></p> <p><a href="https://zenodo.org/api/files/3150cf22-7ee4-4f5a-9cd4-b420ee0dbd91/comp_dt_We_0_1_th_10_9_alpha_4_ddam10.tar.gz">comp_dt_We_0_1_th_10_9_alpha_4_ddam10.tar.gz </a></p> <p><a href="https://zenodo.org/api/files/3150cf22-7ee4-4f5a-9cd4-b420ee0dbd91/comp_dt_We_10_th_10_8_alpha_4_ddam10.tar.gz">comp_dt_We_10_th_10_8_alpha_4_ddam10.tar.gz </a></p> <p>Each contains 4 files, one for each temporal resolution (delta t).</p> <p> </p> <p><strong>Figure 7 (CPU_time.pdf)</strong></p> <p>No simulation output file: all of the necessary information (CPU times) are included in the associated MATLAB code, available in the Github repository.</p> <p> </p> <p><strong>Figure 8 (T_h.pdf)</strong></p> <p><strong>Left panels, a, c, e</strong></p> <p><a href="https://zenodo.org/api/files/3150cf22-7ee4-4f5a-9cd4-b420ee0dbd91/comp_th_We_0_001_dt_10_5_alpha_4_ddam_10.tar.gz">comp_th_We_0_001_dt_10_5_alpha_4_ddam_10.tar.gz </a></p> <p><a href="https://zenodo.org/api/files/3150cf22-7ee4-4f5a-9cd4-b420ee0dbd91/comp_th_We_0_1_dt_10_4_alpha_4_ddam_10.tar.gz">comp_th_We_0_1_dt_10_4_alpha_4_ddam_10.tar.gz </a></p> <p><a href="https://zenodo.org/api/files/3150cf22-7ee4-4f5a-9cd4-b420ee0dbd91/comp_th_We_10_dt_10_3_alpha_4_ddam_10.tar.gz">comp_th_We_10_dt_10_3_alpha_4_ddam_10.tar.gz </a></p> <p>Each contains 4 files, one for each healing time (T_h)</p> <p><strong>Right panels, b, d, f</strong></p> <p>comp_th_We_0_001_dt_10_5_th_10_11_alpha_4_ddam_10.tar.gz</p> <p>comp_th_We_0_001_dt_10_5_th_10_10_alpha_4_ddam_10.tar.gz</p> <p>comp_th_We_0_001_dt_10_5_th_10_9_alpha_4_ddam_10.tar.gz</p> <p>comp_th_We_0_001_dt_10_5_th_10_8_alpha_4_ddam_10.tar.gz</p> <p>comp_th_We_0_1_dt_10_4_th_10_11_alpha_4_ddam_10.tar.gz</p> <p>comp_th_We_0_1_dt_10_4_th_10_10_alpha_4_ddam_10.tar.gz</p> <p>comp_th_We_0_1_dt_10_4_th_10_9_alpha_4_ddam_10.tar.gz</p> <p>comp_th_We_0_1_dt_10_4_th_10_8_alpha_4_ddam_10.tar.gz</p> <p>comp_th_We_10_dt_10_3_th_10_11_alpha_4_ddam_10.tar.gz</p> <p>comp_th_We_10_dt_10_3_th_10_10_alpha_4_ddam_10.tar.gz</p> <p>comp_th_We_10_dt_10_3_th_10_9_alpha_4_ddam_10.tar.gz</p> <p>comp_th_We_10_dt_10_3_th_10_8_alpha_4_ddam_10.tar.gz</p> <p>Each contains 5 files, for 5 different realisations of the model simulations (same parameters, different initial noise on cohesion)</p> <p> </p> <p><strong>Figure 9 (comp_ddam_We_0_001.pdf)</strong></p> <p>comp_ddam_We_0_001_dt_10_5_th_10_10.tar.gz</p> <p>One file for each alpha value (2, 3, 4, 6, 8), one file for each delta d value (0.1, 0.3, 0.5, 0.7, 0.9)</p> <p> </p> <p><strong>Figure 10 (comp_ddam_We_0_1.pdf)</strong></p> <p>comp_ddam_We_0_1_dt_10_4_th_10_9.tar.gz</p> <p>One file for each alpha value (2, 3, 4, 6, 8), one file for each delta d value (0.1, 0.3, 0.5, 0.7, 0.9)</p> <p> </p> <p><strong>Figure 11 (discussion.pdf)</strong></p> <p>u_sfc_We_0_1_dt_10_4_th_10_9_alpha_4_ddam_10.tar.gz</p> <p>u_sfc_We_0_1_dt_10_4_th_10_9_alpha_4_ddam_50.tar.gz</p> <p> </p> <p><strong>SI movie</strong></p> <p>SI_movie.tar.gz</p>
Frictional Properties and Healing Behavior of Tectonic Mélanges: Implications for the Evolution of Subduction Fault Zones
<p>Here, we report data from velocity-step experiments using rocks collected from ancient subduction fault zones, the Lower Mugi and Makimine mélanges of the Cretaceous Shimanto belt. The two mélanges preserve paleotemperature records corresponding to the updip and downdip limits of the seismogenic zone and deformation recording a lower versus higher degree of pressure solution. The compostions of the mélanges analyzed with X-ray diffraction (XRD) are also included in the datasets. Our data show that the Lower Mugi mélange sample exhibits velocity-weakening to velocity-neutral behavior under low normal stress, and the Makimine mélange sample shows velocity-strengthening behavior under high normal stress. This is consistent with the slip behavior observed at the depths they have been subducted to along the plate interface. We also perform a series of slide-hold-slide experiments under different hydrothermal conditions using the Lower Mugi mélange sample to evaluate the role of pressure solution in fault healing and its dependency on temperature. The results show that healing rates increase in tests operated at higher temperatures, which suggests the importance of pressure solution healing along plate interfaces.</p>
Sn velocity model and original catalogue data for essay "Uppermost mantle structure of the Japan subduction zone from Sn tomography"
<p>Sn velocity model and original catalogue data for essay “Uppermost mantle structure of the Japan subduction zone from Sn tomography”</p> <p> </p>
The Impact of the Three-Dimensional Structure of a Subduction Zone on Time-dependent Crustal Deformation Measured by HR-GNSS
<p>Companion data set to the paper "<strong>The Impact of the </strong><strong>Three-Dimensional Structure of a Subduction Zone on Time-dependent Crustal Deformation Measured by HR-GNSS.</strong>" The 'GNSS_Stations' folder contains the GNSS stations used for 2011 <strong>M</strong>7.9 Ibaraki, 2011 <strong>M</strong>7.4 Iwate, 2011A <strong>M</strong>7.3 Miyagi and 2003 <strong>M</strong>8.3 Tokachi 2003 earthquakes. The 'Mesh' folder contains the fault geometry mesh files for the Japan Trench, including the GMSH files. The '3D_velocity_model' folder contains the 3D velocity model for the combined West and East domains of the 3D Japan Integrated Velocity Structure Model in a rfile format and the corresponding ifile format. The 'Ruptures' folder contains the projected rupture models for each earthquake on the Japan Trench mesh and the corresponding 100 realizations of the mean rupture models generated using FakeQuakes. If you use these data, please cite the associated publication:</p> <p>Fadugba, ­O. I., Sahakian, V. J., Diego Melgar, D., Rodgers, A. & Shimony, R. (2023). The Impact of the Three-Dimensional Structure of a Subduction Zone on Time-dependent Crustal Deformation Measured by HR-GNSS.</p>
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Allen Brain Atlas
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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.