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23 results for “Earth's mantle”
A compositional model of the Earth's mantle transition zone from SS and PP data
<p>This dataset provides the thermochemical model of the Earth's mantle transition zone obtained from the inversion of travel-times and amplitudes of seismic waves reflected at mineralogical phase transitions (PP and SS precursors).</p> <p>3 columns : latitude (degree), longitude (degree), potential temperature Tpot (Kelvin), basalt fraction (min 0.0, max 1.0)</p>
Dataset and Software for The Relationships Between Large-scale Variations in Shear Velocity, Density, and Compressional Velocity in the Earth's Mantle
<p><strong>Is there a chemically distinct reservoir in the Earth?</strong><br><strong>Do superplumes overly denser-than-average material?</strong><br><strong>Can we detect these anomalies with seismic data?</strong><br><strong>Can we evaluate statistical significance of the features in tomography?</strong></p><p>This study presents the <strong>strongest evidence</strong> to date (ca. 2015) of <strong>large-scale thermo-chemical heterogeneities in the lowermost mantle</strong> using the full spectrum of seismic data. A large data set of surface-wave phase anomalies, body-wave travel times, normal-mode splitting functions and long-period waveforms is used to investigate the scaling between shear velocity, density and compressional velocity in the Earth's mantle (ϱ=dln ρ/dln vS, ν=dln vS/dln vP). Our preferred joint model consists of denser-than-average anomalies (∼1% peak-to-peak) at the base of the mantle roughly coincident with the low-velocity superplumes. The relative variation of shear velocity, density and compressional velocity in our study disfavors a purely thermal contribution to heterogeneity in the lowermost mantle, with implications for the long-term stability and evolution of superplumes.</p><p><strong>Note on Odd Degree Structure:</strong></p><p>Since the self-coupled normal-mode splitting observations constrain only even-degree density variations, all inversions strongly disfavored even-degree vS-ρ correlation (R2 ~ –0.46 to –0.25) in the lowermost mantle, which also disfavors a purely thermal contribution to heterogeneity in this region. However, the starting assumptions on positive vS-ρ correlation persisted in the remaining regions and for odd degree variations. In viscosity inversions with the geoid, opposing sign of the correlation of the longest wavelength even-versus odd-degree structure maps into a region of reduced viscosity in the lower mantle (Rudolph et al., 2020, doi:10.1029/2020gc009335). While important for such dynamical implications, <strong>odd-degree density variations in the lowermost mantle are poorly constrained in this study and should not be interpreted</strong>. We therefore used even-degree variations up to degree 6 for our inferences on thermo-chemical variations in the lowermost mantle (Figure 14), and provide those values in the files below.</p><p><strong>Feedback/Questions?</strong> Please contact Raj Moulik (<a href="https://rajmoulik.com">rajmoulik.com</a>) at <a href="mailto:moulik@caa.columbia.edu?subject=Query%20from%20Zenodo">moulik@caa.columbia.edu</a> </p><p><strong>Reference:</strong></p><p><i>Please cite the following work if you use this data or software.</i></p><ul><li>Moulik, P. & Ekström, G., 2016. The relationships between large-scale variations in shear velocity, density and compressional velocity in the Earth's mantle, <i>J. Geophys. Res.</i>, <strong>121</strong>, doi: <a href="http://dx.doi.org/10.1002/2015JB012679">10.1002/2015JB012679</a>. <a href="https://rajmoulik.com/Publications/MoulikEkstrom_JGR2016.pdf"><i>pdf</i></a></li></ul><p><i>You can also cite the dataset and software from this Zenodo page (Optional).</i></p><p>Moulik, P. & Ekström, G. (2016). Dataset and Software for The Relationships Between Large-scale Variations in Shear Velocity, Density, and Compressional Velocity in the Earth's Mantle. In J. Geophys. Res. Solid Earth (v1.0, Vol. 121, pp. 2737–2771). Zenodo. doi: <a href="https://doi.org/10.5281/zenodo.8356540">10.5281/zenodo.8356540</a></p><p><strong>Data Products:</strong></p><ul><li><strong>ME16_Figures(</strong><a href="https://zenodo.org/api/files/9aa99409-20ae-495e-b5a3-288fd57ecaeb/ME16_Figures.tar.gz"><strong>.tar.gz</strong></a><strong> or </strong><a href="https://zenodo.org/api/files/9aa99409-20ae-495e-b5a3-288fd57ecaeb/ME16_Figures.pdf"><strong>.pdf</strong></a><strong>)</strong> - contains all figures from the paper in .png format</li><li><a href="https://zenodo.org/api/files/9aa99409-20ae-495e-b5a3-288fd57ecaeb/ME16"><strong>ME16</strong></a><strong> - </strong>Coefficients of the spline basis functions for each parameter. Refer cij in equation 3. This is our preferred global model of anisotropic elastic parameters and density. Density variations are allowed to deviate from a constant scaling with shear-velocity variations in the lowermost mantle, which is required to fit the longest-period normal modes (e.g. 0S2). Radial anisotropy is confined to the uppermost mantle (that is, since the anisotropy is parameterized with only the four uppermost splines, it becomes very small below a depth of 250 km, and vanishes at 410 km). This is an updated version of S362ANI+M (Moulik and Ekström, 2014) which did not solve independently for density and compressional-wave velocity variations and imposed a constant scaling throughout the mantle instead (ϱ=0, ν=1/0.55).</li><li><a href="https://zenodo.org/api/files/9aa99409-20ae-495e-b5a3-288fd57ecaeb/STW105"><strong>STW105</strong></a> - reference model used in ME16. Described in Kustowski et al. (2008)</li><li><a href="https://zenodo.org/api/files/9aa99409-20ae-495e-b5a3-288fd57ecaeb/setup.cfg"><strong>setup.cfg</strong></a><strong> - </strong>Some configuration metadata relevant to this model for reproducibility.</li><li><a href="https://zenodo.org/api/files/9aa99409-20ae-495e-b5a3-288fd57ecaeb/epix.tar.gz"><strong>epix.tar.gz</strong></a> - Perturbations in horizontally (<i>vsh</i>) and vertically polarized shear velocity (<i>vsv</i>), Voigt-average isotropic shear-wave (<i>vs</i>) and compressional-wave velocity (<i>vp</i>), density (<i>rho</i>). anisotropy (<i>as</i>) and topography of the internal boundaries. This is calculated from the spline coefficients at every 1 by 1 degree cell-centered pixel and at every ~25 km depth region from Moho to the core-mantle boundary and stored in extended pixel format (.epix) ASCII files. Even-degree variations up to degree 6 are provided for density (<i>rho_even6)</i> and isotropic shear-wave velocity (<i>vs_even6</i>), which should be used for density inferences on thermochemical structure (See note above).</li><li><a href="https://zenodo.org/api/files/9aa99409-20ae-495e-b5a3-288fd57ecaeb/ME16.BOX25km_PIX1X1.avni.nc4"><strong>ME16.BOX25km_PIX1X1.avni.nc4</strong></a> - The perturbations in a standard AVNI format that utilizes the NETCDF4 container format. This file can be read in Python using either xarray or AVNI libraries. For example, to plot even-degree variations up to degree 6 in Voigt-averaged shear velocity perturbations at the bottom of the mantle (2875-2891 km depth)<ul><li><i>import xarray as xr</i></li><li><i>ds = xr.open_dataset('ME16.BOX25km_PIX1X1.avni.nc4')</i></li><li><i>ds['vs_even6'][-1].plot()</i></li></ul></li><li><a href="https://zenodo.org/api/files/9aa99409-20ae-495e-b5a3-288fd57ecaeb/PROGRAMS.tar.gz"><strong>PROGRAMS.tar.gz</strong></a> - Fortran tools for obtaining model values at specific locations. After creating the executables from source code in the <i>src</i> folder, the <i>readme</i> script generates most of the epix files provided in epix.tar.gz above<strong>.</strong></li><li><a href="https://zenodo.org/api/files/9aa99409-20ae-495e-b5a3-288fd57ecaeb/profilescaling.txt"><strong>profilescaling.txt</strong></a> - contains the median scaling ratios as used in Figure 15(a).</li><li><a href="https://zenodo.org/api/files/9aa99409-20ae-495e-b5a3-288fd57ecaeb/scaling3D_MoulikJGR16.tar.gz"><strong>scaling3D_MoulikJGR16.tar.gz</strong></a> - contains the scaling ratios and poisson ratio calculated from the joint model, as used in Figure 15(b).</li></ul>
Self-consistent models of Earth's mantle and core from long-period seismic and tidal constraints
<p>This dataset consists of a collection of self-consistent radial seismic Earth models. The models are derived by inverting a large set of normal-mode centre-frequencies, quality factors, and geodetic data, including mass, moment of inertia, and tidal response.</p><p>The dataset is accompanied by a research paper titled "Self-consistent models of Earth's mantle and core from long-period seismic and tidal constraints" (DOI: <a href="https://doi.org/10.1093/gji/ggad254">10.1093/gji/ggad254</a>). The paper presents the methodology and findings related to the development of the models.</p><p>This version (V0.2) of the dataset replaces the previous version (V0.1). </p><p><strong>Dataset Details</strong></p><p>The dataset includes confidence intervals (CIs) for these parameters at 25%, 50%, and 75% levels that are representative of the uncertainty of the sampled model parameters. For example, the files <a href="https://zenodo.org/api/files/fa9f19f0-bf6a-41a8-8ca7-489a5b1b9c49/screm-25p-high.dat?versionId=b3b349c2-0a0b-48cc-b1f3-90137b8d1dcb">screm-25p-high.dat</a> and <a href="https://zenodo.org/api/files/fa9f19f0-bf6a-41a8-8ca7-489a5b1b9c49/screm-25p-low.dat?versionId=81db34f2-29f4-48aa-95c4-bb73b050a47f">screm-25p-low.dat</a> contain the upper and lower bound of the 25% CI sampled model range. A python plotting script is available, which plots the CIs.</p><p>The dataset files are provided in comma-separated values (CSV) format, containing the following columns:</p><ol><li><strong>Radius (km)</strong>: Radial distance from the center of the Earth.</li><li><strong>Depths (km)</strong>: Depth from the surface of the Earth.</li><li><strong>Density (g/cm³)</strong>: Radial density structure.</li><li><strong>P-wave velocity (vp) (km/s)</strong>: Radial compressional (P) wave velocity structure</li><li><strong>S-wave velocity (vs) (km/s)</strong>: Radial shear (S) wave velocity structure.</li><li><strong>Qkappa</strong>: Radial bulk attenuation structure.</li><li><strong>Qmu</strong>: Radial shear wave attenuation structure.</li><li><strong>Bulk Modulus (K) (GPa)</strong>: Radial bulk modulus structure.</li><li><strong>Shear Modulus (Mu) (GPa)</strong>: Radial shear modulus structure.</li><li><strong>Pressure (GPa)</strong>: Radial pressure profile.</li><li><strong>Temperature (K)</strong>: Radial geothermal profile.</li></ol><p><strong>Citation</strong></p><p>If you use this dataset in your research or refer to the models, please cite the following paper:</p><p><strong>Title:</strong> Self-consistent models of Earth's mantle and core from long-period seismic and tidal constraints<br><strong>Authors:</strong> J. Kemper, A. Khan, G. Helffrich, M. van Driel, D. Giardini<br><strong>Journal:</strong> Geophysical Journal International<br><strong>Year: </strong>2023<br><strong>DOI:</strong> <a href="https://doi.org/10.1093/gji/ggad254">10.1093/gji/ggad254</a></p><p>Please also acknowledge the dataset by providing a link to the Zenodo repository and its DOI.</p><p>Bibtex:<br>@article{Kemper_etal23,<br>author = {Kemper, J and Khan, A and Helffrich, G and van Driel, M and Giardini, D},<br>title = "{Self-consistent models of Earth's mantle and core from long-period seismic and tidal constraints}",<br>journal = {Geophysical Journal International},<br>pages = {ggad254},<br>year = {2023},<br>month = {06},<br>issn = {0956-540X},<br>doi = {10.1093/gji/ggad254},<br>url = {https://doi.org/10.1093/gji/ggad254},<br>} </p><p> </p>
Dataset for "Seismological Expression of the Iron Spin Crossover in Ferropericlase in the Earth's Lower Mantle"
<p>The folder contains data related to the publication: Shephard, Houser, Hernlund, Trønnes, Valencia-Cardona, Wentzkovitch (2021) Seismological Expression of the Iron Spin Crossover in Ferropericlase in the Earth’s Lower Mantle. Accepted for publication in Nature Communications.</p> <p>It include numerical grids, a simple plotting script, colour maps, and images (jpg and ps files). There is a README file explaining the content and uses of the these additional data files.</p>
Flow at the Earth's core mantle boundary between 1900.0 and 2014.0
<p>The files contain the spherical harmonics coefficients of the velocity field at the Earth's core mantle boundary between 1900.0 and 2014.0.</p> <p>Uncertainties are provided through the standard deviation associated with each coefficient.</p>
How to assess similarities and differences between mantle circulation models and Earth using disparate independent observations: Data and Analysis
<p>Dataset includes simulation output produced by a TERRA simulation for `How to assess similarities and differences between mantle circulation models and Earth using disparate independent observations'. </p> <p> </p> <h3><strong>Description of data file contents</strong></h3> <ul> <li><strong>NC*comp.tar.gz</strong> - compressed archives containing NetCDF files (file-per-process) with TERRA grid data including temperature, velocity, interpolated bulk composition, denisty, and voscosity fields. Can be read using <a title="terratools" href="https://github.com/mantle-convection-constrained/terratools" target="_blank" rel="noopener">terratools</a>. *dump number</li> <li><strong>NC_seis_037.tar.gz</strong> - compressed archive containing NetCDF files (file-per-process) with predicted seismic properties at the resolution of the TERRA grid generated from the present day state of the simulated mantle, including elastic and anelastic Vs and Vp, bulk sound velocity, and predicted density from mineral phyiscs tables. Can be read using <a title="terratools" href="https://github.com/mantle-convection-constrained/terratools" target="_blank" rel="noopener">terratools</a>.</li> <li><strong>NC_hpes_037.tar.gz</strong> - compressed archive containing NetCDF files (file-per-process) with interpolated abundances at the resolution of the TERRA grid for isotopes including the heat-producing elements ^40^K, ^232^Th, ^235^U and ^238^U. Can be read using <a title="terratools" href="https://github.com/mantle-convection-constrained/terratools" target="_blank" rel="noopener">terratools</a>.</li> <li><strong>P_files_037.tar.gz</strong> - compressed archive of TERRA P-files (particle files).</li> <li><strong>C_files_037.tar.gz</strong> - compressed archive of TERRA C-files (grid state files) - together with the P-files describe the full present day state of the simulation. </li> <li><strong>seis_filtered_037.tar.gz</strong> - compressed archive (file-per-layer) with reparameterised and seismically filtered (against S40RTS) present day Vs field.</li> <li><strong>seis_tables.tar.gz</strong> - compressed archive contianing lookup tables of seismic properties for the 3 principal lithologies assumed in the TERRA simulation (harzburgite, lherzolite and basaltic crust).</li> <li><strong>density_037.sph</strong> - Spherical harmonic coefficients for the density field in format to be read by the <a title="propagator" href="https://zenodo.org/records/12696774" target="_blank" rel="noopener">propagator matrix code.</a></li> <li><strong>plumes.pkl, ridges.pkl</strong> - Files containing tracer particle information for particles associated with plumes and ridges. </li> <li><strong>plumes_ridges.py</strong> - Python script containing example code for reading and plotting plumes.pkl and ridges.pkl files. </li> <li><strong>ptcls_rdgs_plms.py, interrogate_particles.py</strong> - Python script and module containing required functions for carrying out post processing routine generating the plumes.pkl and ridges.pkl files. Requires <a title="terratools" href="https://github.com/mantle-convection-constrained/terratools" target="_blank" rel="noopener">terratools</a>.</li> <li><strong>hst.dat </strong>- Time series of key simulation properties including mantle temperature profile used for calcualting CMB heat flux. </li> <li><strong>terra, interra</strong> - TERRA executable and input parameter file.</li> <li><strong>pyflowng.zip</strong> - Compressed directory containing version of the `pyflowng` code used in this work.</li> <li><strong>mode_splitting_methods.zip</strong> - Compressed directory contianing synthetic splitting function predictions and maps.</li> </ul> <p> </p> <h3><strong>Dump Numbers</strong></h3> <p>Below is a table of dump numbers (final three digits of file names) and the corresponding model times.</p> <table> <tbody> <tr> <td><strong>Dump number </strong></td> <td><strong>Model time (Ma)</strong></td> </tr> <tr> <td>037</td> <td>0 (present day)</td> </tr> <tr> <td>027</td> <td>10</td> </tr> <tr> <td>026</td> <td>20</td> </tr> <tr> <td>025</td> <td>30</td> </tr> <tr> <td>024</td> <td>40</td> </tr> <tr> <td>023</td> <td>50</td> </tr> <tr> <td>022</td> <td>60</td> </tr> <tr> <td>021</td> <td>70 </td> </tr> <tr> <td>020</td> <td>80</td> </tr> <tr> <td>019</td> <td>90</td> </tr> <tr> <td>018</td> <td>100</td> </tr> </tbody> </table>
Core-mantle partitioning and the bulk Earth abundances of hydrogen and carbon: implications for their origins
Open the record for dataset details and reuse information.
Datasets for Russell & Jones, Transport and eruption of mantle xenoliths creates a lagging problem, Communications Earth and Environment
<p>Example datasets for Russell & Jones, Transport and eruption of mantle xenoliths creates a lagging problem, Communications Earth and Environment </p>
Modeling liquid transport in the Earth's mantle as two-phase flow: Effect of an enforced positive porosity on liquid flow and mass conservation
<p>These data files include the raw data for the figures shown in Lee et al. titled as 'Modeling liquid transport in the Earth’s mantle as two-phase flow: Effect of an enforced positive porosity on liquid flow and mass conservation'. <br> </p>
Data used in the recently submitted AGU manuscript "Global Mantle Conductivity Imaging using 3-D GDS Inversion with Real Earth Surface Conductivity Constraint"
<p>Main data used in the recently submitted AGU manuscript "Global Mantle Conductivity Imaging using 3-D GDS Inversion with Real Earth Surface Conductivity Constraint"</p>
Melting and Defect Transitions in FeO up to Pressures of Earth's Core-Mantle Boundary
<p>The tables here represent the Source Data for Figure 6 in the manuscript titled "Melting and defect transitions in FeO up to pressures of Earth's core-mantle boundary.</p>
Quantum critical phase of FeO spans conditions of Earth's lower mantle
<p>The tables here represent the Source Data for figures in the manuscript titled "Quantum critical phase of FeO spans conditions of Earth's mantle base".</p><p> </p>
The elasticity of seifertite at lowermost mantle conditions: implication for velocities anomaly at the Earth's core-mantle boundary
<p>the open data of the study "<span>The elasticity of seifertite at lowermost mantle conditions: implication for</span><span> </span><span>velocities anomaly at the Earth's core-mantle boundary"</span></p>
Data set "Narrow, fast, and "cool" mantle plumes caused by strain-weakening rheology in Earth's lower mantle" (G-cubed)
<p>This archive contains data related to the manuscript “Narrow, fast, and “cool” mantle plumes caused by strain-weakening rheology in Earth’s lower mantle” by Gülcher et al., (G-cubed). It contains output quantities and selected fields for the numerical models shown and discussed in the paper (M###). Moreover, it contains the input parametric files implemented in StagYY. Please read the README.dat file for more information. </p>
Melting of Hydrated Subducted Lithospheric Mantle for the Origin of Ultra-Low Velocity Zones in the Cold Regions of Earth's Core-Mantle Boundary
<p>These are the datasets used in the figures. We submitted our manuscript to a peer-reviewed journal (Date: 2024-JUL-05).</p>
Core Origin of Seismic Velocity Anomalies at the Earth's Core-Mantle Boundary
<p>Datasets supporting the findings in the article "Core Origin of Seismic Velocity Anomalies at the Earth's Core-Mantle Boundary"</p>
Globally Distributed Subducted Materials along the Earth's Core-Mantle Boundary: Implications for Ultra-low Velocity Zones
<p>Supplemental movie files related to the geodynamic models in our manuscript "Globally Distributed Subducted Materials along the Earth’s Core-Mantle Boundary: Implications for Ultra-low Velocity Zones"</p>
Dataset and Software for An anisotropic shear velocity model of the Earth's mantle using normal modes, body waves, surface waves and long-period waveforms
<p><strong>What is the nature of flow in the mantle?</strong><br> <strong>How fast do waves travel anywhere on Earth?</strong><br> <strong>Where can radial anisotropy be robustly detected?</strong><br> <strong>Can we reconcile a broad spectrum of seismic data? What are the benefits?</strong></p> <p>We use normal-mode splitting functions in addition to surface-wave phase anomalies, body-wave travel times and long-period waveforms to construct a three-dimensional model of anisotropic shear-wave velocity in the Earth's mantle. This is the <strong>first tomographic study</strong> to exploit the sensitivity of mode-splitting data to constrain radial anisotropy in the Earth's mantle jointly with several other types of data. Our modeling approach inverts for mantle velocity and anisotropy as well as transition-zone discontinuity topographies, and incorporates new crustal corrections for the splitting functions that are consistent with the nonlinear corrections we employ for the waveforms. Our preferred anisotropic model, S362ANI+M, is an update to the earlier model S362ANI, which did not include normal-mode splitting functions in its derivation.</p> <p><strong>Feedback/Questions?</strong> Please contact Raj Moulik (<a href="https://rajmoulik.com">rajmoulik.com</a>) at <a href="mailto:moulik@caa.columbia.edu?subject=Query%20from%20Zenodo">moulik@caa.columbia.edu</a> </p> <p><strong>Reference:</strong></p> <p><em>Please cite the following work if you use this data or software.</em></p> <ul> <li>Moulik, P. & Ekström, G., 2014. An anisotropic shear velocity model of the Earth's mantle using normal modes, body waves, surface waves and long-period waveforms, <em>Geophys. J. Int.</em>, <strong>199</strong>(3), 1713-1738, doi: <a href="http://dx.doi.org/10.1093/gji/ggu356">10.1093/gji/ggu356</a>. <em><a href="https://rajmoulik.com/Publications/MoulikEkstrom_GJI2014.pdf">pdf</a></em></li> </ul> <p><em>You can also cite the dataset and software from this Zenodo page (Optional).</em></p> <ul> <li> <p>Moulik, P. & Ekström, G., 2014. Dataset and Software for An anisotropic shear velocity model of the Earth's mantle using normal modes, body waves, surface waves and long-period waveforms. In Geophys. J. Int. (v1.0, Vol. 199, pp. 1713–1738). Zenodo. doi: <a href="https://doi.org/10.5281/zenodo.8357379">10.5281/zenodo.8357379</a></p> </li> </ul> <p><strong>Data Products:</strong></p> <ul> <li><a href="https://zenodo.org/api/files/a15ed123-5262-4c4b-9806-1b50e7f8ee82/S362ANIplusM_Figures.tar.gz"><strong>S362ANIplusM_Figures.tar.gz</strong></a> - contains all figures from the paper in .png format</li> <li><a href="https://zenodo.org/api/files/a15ed123-5262-4c4b-9806-1b50e7f8ee82/S362ANI%2BM_MapViewsCrossSections.pdf"><strong>S362ANI+M_MapViewsCrossSections.pdf</strong></a> - Some cross sections and map views at various depths in the mantle</li> <li><strong><a href="https://zenodo.org/api/files/a15ed123-5262-4c4b-9806-1b50e7f8ee82/S362ANI%2BM">S362ANI+M</a> - </strong>Coefficients of the spline basis functions for each parameter. Refer c<sub>ij</sub> in equation 11. This is our preferred global model of shear-wave velocity. In this model, radial anisotropy is confined to the uppermost mantle (that is, since the anisotropy is parameterized with only the four uppermost splines, it becomes very small below a depth of 250 km, and vanishes at 410 km). This is an updated version of S362ANI (Kustowski et al., 2008) which did not include normal modes in its derivation. Please note the stronger isotropic shear velocity anomalies in the transition zone.</li> <li><a href="https://zenodo.org/api/files/a15ed123-5262-4c4b-9806-1b50e7f8ee82/STW105"><strong>STW105</strong></a> - reference model used in S362ANI+M. Described in Kustowski et al. (2008)</li> <li><strong><a href="https://zenodo.org/api/files/a15ed123-5262-4c4b-9806-1b50e7f8ee82/setup.cfg">setup.cfg</a> - </strong>Some configuration metadata relevant to this model for reproducibility.</li> <li><a href="https://zenodo.org/api/files/a15ed123-5262-4c4b-9806-1b50e7f8ee82/epix.tar.gz"><strong>epix.tar.gz</strong></a> - Perturbations in horizontally (vsh) and vertically polarized shear velocity (vsv), Voigt-average isotropic velocity (vs), ansotropy (as) and topography of the internal boundaries. This is calculated from the spline coefficients at every 1 by 1 degree cell-centered pixel and at every ~25 km depth region from Moho to the core-mantle boundary and stored in extended pixel format (.epix) ASCII files. </li> <li><a href="https://zenodo.org/api/files/a15ed123-5262-4c4b-9806-1b50e7f8ee82/S362ANI%2BM.BOX25km_PIX1X1.avni.nc4"><strong>S362ANI+M.BOX25km_PIX1X1.avni.nc4</strong></a> - The perturbations in a standard AVNI format that utilizes the NETCDF4 container format. This file can be read in Python using either xarray or AVNI libraries. For example, to plot vs perturbations at 24.4-50 km depth range <ul> <li><em>import xarray as xr</em></li> <li><em>ds = xr.open_dataset('S362ANI+M.BOX25km_PIX1X1.avni.nc4')</em></li> <li><em>ds.vs[0].plot()</em></li> </ul> </li> <li><strong>Fortran Code</strong> <ul> <li><a href="https://zenodo.org/api/files/a15ed123-5262-4c4b-9806-1b50e7f8ee82/readme"><strong>readme</strong></a> - contains a description of all files in the folder below</li> <li><a href="https://zenodo.org/api/files/a15ed123-5262-4c4b-9806-1b50e7f8ee82/PROGRAMS.tar.gz"><strong>PROGRAMS.tar.gz</strong></a> - tools for obtaining model values at specific locations and some GMT plotting tools</li> </ul> </li> <li><a href="https://zenodo.org/api/files/a15ed123-5262-4c4b-9806-1b50e7f8ee82/GRD.tar.gz"><strong>GRD.tar.gz</strong></a> - longitude-latitide-velocity files with vsh, vsv, and Voigt average in km/s evaluated on a grid of points at many depths in the mantle</li> </ul>
Data from: Ice-VII inclusions in diamonds: evidence for aqueous fluid in Earth’s deep mantle
Open the record for dataset details and reuse information.
Water-induced Diamond Formation at Earth's Core-Mantle Boundary
<p>Experimental results</p>
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
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.