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712 results for “Mantle”
Centre frequencies and uncertainties for "Evidence for a kilometre-scale seismically slow layer atop the core-mantle boundary from normal modes"
<p>A table containing the centre frequencies and uncertainties used for the study presented in "Evidence for a kilometre-scale seismically slow layer atop the core-mantle boundary from normal modes". This table is the same as is contained in the supplementary materials of that paper.</p> <p>Russell, S., Irving, J. C. E., Jagt, L., & Cottaar, S. (2023). Evidence for a kilometer-scale seismically slow layer atop the core-mantle boundary from normal modes. Geophysical Research Letters, 50, e2023GL105684. <a href="https://doi.org/10.1029/2023GL105684">https://doi.org/10.1029/2023GL105684</a></p>
Tectonic evolution and deep mantle structure of the eastern Tethys since the latest Jurassic
<p>Uploaded by Sabin Zahirovic (sabin.zahirovic@sydney.edu.au)<br>6 August 2018</p> <p>Notes:</p> <p>Plate reconstructions can be downloaded from: <br><a href="https://www.earthbyte.org/webdav/ftp/Data_Collections/Zahirovic_etal_ESR_EasternTethys_Supplement.zip" target="_blank" rel="noopener">https://www.earthbyte.org/webdav/ftp/Data_Collections/Zahirovic_etal_ESR_EasternTethys_Supplement.zip</a></p> <p>The relevant seafloor paleo-agegrid can be downloaded from:<br><a href="https://www.earthbyte.org/webdav/ftp/Data_Collections/Zahirovic_etal_2016_ESR_AgeGrid/" target="_blank" rel="noopener">https://www.earthbyte.org/webdav/ftp/Data_Collections/Zahirovic_etal_2016_ESR_AgeGrid/</a> </p> <p>This is internal revision 888 of the 2015_v2 seafloor age-grid. </p> <p>Citation:<br>Zahirovic, S., Matthews, K. J., Flament, N., Müller, R. D., Hill, K. C., Seton, M., and Gurnis, M., 2016, Tectonic evolution and deep mantle structure of the eastern Tethys since the latest Jurassic. Earth Science Reviews, v. 162, p. 293-337."<br><a href="https://www.sciencedirect.com/science/article/pii/S0012825216302872%22" target="_blank" rel="noopener">https://www.sciencedirect.com/science/article/pii/S0012825216302872%22</a> </p>
Testing absolute plate reference frames and the implications for the generation of geodynamic mantle heterogeneity structure
<div>Description of Resources - Shephard et al. (2012)</div> <div> </div> <div>This file provides a detailed description of all of the files that make up the data collection associated with the publication: Shephard, G. E., Bunge, H. P., Schuberth, B. S., Müller, R. D., Talsma, A. S., Moder, C., & Landgrebe, T. C. W. (2012). Testing absolute plate reference frames and the implications for the generation of geodynamic mantle heterogeneity structure. Earth and Planetary Science Letters, 317, 204-217. doi: <a href="https://doi.org/10.1016/j.epsl.2011.11.027" target="_blank" rel="noopener">10.1016/j.epsl.2011.11.027</a></div> <div> </div> <div>Note: For information on file formats and what programs to use to interact with various file formats, see "File Formats and Recommended Programs”.</div> <div> </div> <div>This data collection includes both the rotations and topologically closed polygons* for each of the 5 absolute reference frames that were tested in the publication. They are to be loaded in GPlates (<a href="http://www.gplates.org" target="_blank" rel="noopener">http://www.gplates.org</a>).</div> <div> </div> <div>*Topologically closed plate polygons are constructed from the intersection of ridges, transforms, subduction zones and other plate boundary geometries. These 'resolved topologies' are valid at 1 Myr intervals. The plate boundary geometries and plate polygons have been assigned plate reconstruction IDs to allow them to be reconstructed using the supplied rotation files. </div> <div> </div> <div>The files associated with this data collection include:</div> <div>• <strong>Hybrid hotspot model (Moving and Fixed hotspots) (HHS)</strong></div> <div>* Caltech_Global_20110311HHS.gpml (37 MB) - topologically closed plate polygons and plate boundary geometries</div> <div>* Caltech_Global_20110412HHS.rot (287 KB)- global rotation model</div> <div> </div> <div>• <strong>Fixed hotspot model (FHS)</strong></div> <div>* Caltech_Global_20110311FHS.gpml (36.8 MB) - topologically closed plate polygons and plate boundary geometries</div> <div>* Caltech_Global_20110412FHS.rot (291 KB) - global rotation model</div> <div> </div> <div>•<strong> Hybrid hotspot and palaeomagnetic model (PMG)</strong></div> <div>* Caltech_Global_20110311PMG.gpml (35.9 MB) - topologically closed plate polygons and plate boundary geometries</div> <div>* Caltech_Global_20110412PMG.rot (287 KB) - global rotation model</div> <div> </div> <div>• <strong>Subduction reference frame model (SUB)</strong></div> <div>* Caltech_Global_20110311SUB.gpml (36 MB) - topologically closed plate polygons and plate boundary geometries</div> <div>* Caltech_Global_20110412SUB.rot (287 KB) - global rotation model</div> <div> </div> <div>• <strong>Hybrid hotspot and TPW-corrected palaeomagnetic model (TPW)</strong></div> <div>* Caltech_Global_20110311TPW.gpml (36.8 MB) - topologically closed plate polygons and plate boundary geometries</div> <div>* Caltech_Global_20110412TPW.rot (287 KB)- global rotation model</div> <div> </div> <div>Project files (.gproj) are included for each .gpml/.rot pair.</div> <div> </div> <div>This article has additional supplementary data available with the online publication.</div> <div> </div> <div> </div> <div>Additional notes:</div> <div>*.rot contains the rotations for all plates and topological polygons.</div> <div>Each model is specific according to the African Plate (Plate ID 701) rotations. The rotations for all other plates are the same across each of the five models with the exception of cross-overs involving Pacific/Panthalassa plates for times earlier than 83.5Ma; these must be absolute reference frame specific and were re-calculated for each model. Programs used to calculate the new finite rotations include "adder" and "seaflow" </div> <div> </div> <div>*.gpml and .shp files contain continuously closing plate polygons i.e. from plate boundaries, from 140 Ma to present-day in 1 million year increments. </div> <div>These files differ slightly from those used in the paper, but are the most up-to-date version (as at May 2011) and are based on an updated model, Seton et al. (2012).</div> <div>They are specific to each of the five absolute reference frames. </div> <div> </div> <div>Note on velocity calculations in GPlates:</div> <div>GPlates calculates the velocity within each plate based on the stage rotation for that time period and averages for that respective period. For this reason, the velocities of a plate do not change incrementally within the time period and then abruptly change according to the next time period/stage rotation. </div> <div>This is also why there appears to be a "jump" in velocity magnitude and direction between 140 and 139 Ma.</div>
The tectonic evolution of the Arctic since Pangea breakup: Integrating constraints from surface geology and geophysics with mantle structure
<div>Description of Resources - Shephard et al. (2013)</div> <div> </div> <div>This file provides a detailed description of all of the files that make up the data collection associated with the publication: Shephard, G. E., Müller, R. D., & Seton, M. (2013). The tectonic evolution of the Arctic since Pangea breakup: Integrating constraints from surface geology and geophysics with mantle structure. Earth-Science Reviews, 124(0), 148-183. doi: <a href="https://doi.org/10.1016/j.earscirev.2013.05.012" target="_blank" rel="noopener">10.1016/j.earscirev.2013.05.012</a></div> <div> </div> <div>Note: For information on file formats and what programs to use to interact with various file formats, see "File Formats and Recommended Programs”.</div> <div> </div> <div>Note: This paper is based on a global model (Seton et al., 2012), which should also be referenced if looking globally or regions other than the Arctic or northern Panthalassa.</div> <div> </div> <div>The files that make up the tectonic reconstruction model include:</div> <div>• <strong>Rotations </strong>- This is a global rotation model (based on Seton et al., 2012) that includes the new rotations for the Arctic.</div> <div>* Shephard_etal_ESR2013.rot (373 KB)</div> <div> </div> <div>• <strong>Coastlines </strong>- These are present day coastlines that have been assigned plate reconstruction ids to allow them to be reconstructed using the rotation file.</div> <div>* Shephard_etal_ESR2013_Coastlines.gpml (34.1 MB)</div> <div>* Shephard_etal_ESR2013_Coastlines.txt (3.2 MB)</div> <div>* Shephard_etal_ESR2013_Coastlinesc.kml (6.3 MB; datum - WGS 1984)</div> <div>* Shephard_etal_ESR2013_Coastlines.shp (3.2 MB inc auxiliary files; datum - WGS 1984)</div> <div> </div> <div>• <strong>Static polygons </strong>- These are closed polygons that split present day Earth's surface into regions that can be assigned to a given plate id, and therefore reconstructed back through time using the rotation file. These polygons can be used to cookie-cut and assign plate ids to geometry and raster data (for more information on this feature please visit http://gplates.org or http://earthbyte.org).</div> <div>* Shephard_etal_ESR2013_staticpolygons.gpml (19.4 MB)</div> <div>* Shephard_etal_ESR2013_staticpolygons.txt (2.7 MB)</div> <div>* Shephard_etal_ESR2013_staticpolygons.kml (4.4 MB; datum - WGS 1984)</div> <div>* Shephard_etal_ESR2013_staticpolygons.shp (2.3 MB inc auxiliary files; datum - WGS 1984)</div> <div> </div> <div>• <strong>Plate boundary geometries and resolved topologies</strong> – Resolved topologies comprise ridges, transforms, subduction zones and other plate boundary geometries. These boundaries intersect to form closed plate polygons ('resolved topologies') that are valid at 1 Myr intervals (0-200 Ma). The plate boundary geometries and plate polygons have been assigned plate reconstruction ids to allow them to be reconstructed using the rotation file.</div> <div>* Shephard_etal_ESR2013_platebounds.gpml (27.7 MB) - contains both plate boundaries and resolved topological plate polygons</div> <div>* Resolved topologies:</div> <div>- topology_*.00Ma.txt (20.6 MB)</div> <div>- topology_*.00Ma.shp (12.5 MB inc auxiliary files; datum - WGS 1984)</div> <div> </div> <div> </div> <div>References</div> <div> </div> <div>M. Seton, R.D. Müller, S. Zahirovic, C. Gaina, T.H. Torsvik, G. Shephard, A. Talsma, M. Gurnis, M. Turner, S. Maus, M. Chandler, (2012). Global continental and ocean basin reconstructions since 200 Ma. Earth-Science Reviews, 113(3–4), 212-270. doi:<a href="https://doi.org/10.1016/j.earscirev.2012.03.002" target="_blank" rel="noopener">10.1016/j.earscirev.2012.03.002</a></div>
Topographic fingerprint of deep mantle subduction
<p>This dataset contains the extracted velocities (Vt, Vconv), the time, as well as the surface topographic signals (Hsurf, Hdyn) of the models presented in the paper.</p>
Constraints on mantle viscosity and Laurentide ice sheet evolution from pluvial paleolake shorelines in the western United States: Datasets
<p>*********** Please view the README.txt file for detailed documentation of data. ***********</p> <p><strong>Title:</strong> Constraints on mantle viscosity and Laurentide ice sheet evolution from pluvial paleolake shorelines in the western United States: Datasets</p> <p><strong>Version: </strong>1.0</p> <p><strong>Date of Release: </strong>2019/12/16</p> <p><strong>Identifier: </strong>10.5281/zenodo.3576251</p> <p><strong>Associated publication:</strong> Austermann, J., Chen, C.Y., Lau, H.C.P., Maloof, A.C., and Latychev, K. (2019) Constraints on mantle viscosity and Laurentide ice sheet evolution from pluvial paleolake shorelines in the western United States. <em>Earth and Planetary Science Letters</em>. doi: 10.1016/j.epsl.2019.116006</p> <p><strong>Link to publication: </strong><a href="https://doi.org/10.1016/j.epsl.2019.116006">https://doi.org/10.1016/j.epsl.2019.116006</a></p> <p><strong>Suggested citation: </strong>Please reference the associated publication above when using any datasets or materials described in the README file.</p> <p><strong>Contact information:</strong> Jacky Austermann (jackya@ldeo.columbia.edu) and Christine Y. Chen (cychen.earth@gmail.com)</p> <p>--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------</p> <p>This directory contains the following datasets:</p> <p>SHORELINE FEATURE ELEVATION DATA</p> <ul> <li><strong>Bonneville_Provo_Sehoo_shoreline_feature_elev_Austermann2019_EPSL.xlsx</strong>: shoreline feature elevation measurements of the Bonneville, Provo, and Sehoo lake stages of Lake Bonneville and Lake Lahontan; original measurements were made by Adams et al. (1999), Chen and Maloof (2017), and Currey (1982)</li> </ul> <p>MODELED RECONSTRUCTIONS OF LAKE VOLUME AND PALEOTOPOGRAPHY</p> <ul> <li><strong>LakeBonneville_NAICE_l20.ump02p25.lmp5VM5.mat:</strong> model output for Lake Bonneville, including reconstructions of lake volume and paleotopography</li> <li><strong>LakeLahontan_NAICE_l20.ump02p25.lmp5VM5.mat</strong>: model output for Lake Lahontan, including reconstructions of lake volume and paleotopography</li> </ul>
Tables of results for lower mantle grain size and viscosity estimates
<p>Data on diffusivity, grain size, and viscosity calculations are shown in Figs. 7-10 and Figs. S4-S5 in Okamoto and Hiraga's "A Common Diffusional Mechanism for Creep and Grain Growth in Polycrystalline Rocks: Application to Lower Mantle Viscosity Estimates".</p>
Data set of 'Adiabatic temperature profile in the mantle, revised'
<p>P-V-T data of the four major mantle minerals, olivine, wadselyite, ringwoodite, and bridgmanite</p> <p>The original data are as follows:</p> <p>Olivine: https://doi.org/10.1016/j.pepi.2008.08.002</p> <p>Wadsleyite: https://doi.org/10.1029/2009GL038107</p> <p>Ringwoodite: https://doi.org/10.1029/2004JB003094</p> <p>Bridgmanite; https://doi.org/10.1029/2009GL039318 https://doi.org/10.1029/2011JB008988</p> <p>The temperatures were recalculated using https://doi.org/10.1016/j.pepi.2019.106348</p> <p>The pressures were recalculated using https://doi.org/10.1029/2011JB008988</p> <p> </p>
WINTERC-G: a global upper mantle thermochemical model from coupled geophysical–petrological inversion of seismic waveforms, heat flow, surface elevation and gravity satellite data
<p>WINTERC-G: A global, temperature and compositional model of the lithosphere<br> and upper mantle.<br> Version: v5.4, December 2020, J. Fullea, S. Lebedev, Z. Martinec, N. Celli<br> <br> Contact: Javier Fullea (jfullea@ucm.es)<br> Facultad de Fisica,<br> Universidad Complutense de Madrid (UCM),<br> Spain<br> ////////<br> Geophysics Section,<br> Dublin Institute for Advanced Studies<br> Dublin, Ireland<br> </p> <p>TYPE:<br> This contains files with:<br> i) the model directly on the triangular grid solved for in the surface wave inversion.</p> <p> ii) an interpolated grid at 0.5 deg lateral resolution for the density and density discontinuities used in the gravity field data inversion<br> </p> <p>If you have any questions regarding the methodology or the construction<br> of the model, please contact the authors. If you use the model, we would<br> request that you cite the reference indicated below, and appreciate<br> your feedback regarding the model and its application.</p> <p>Citation:</p> <p>Fullea, J., Lebedev, S., Martinec, Z., & Celli, N. L. (2021). WINTERC-G: mapping the upper mantle thermochemical heterogeneity from coupled geophysical–petrological inversion of seismic waveforms, heat flow, surface elevation and gravity satellite data. Geophysical Journal International, 226(1), 146-191.</p> <p>*******************************<br> Summary: construction of the model.<br> WINTERC-G is a Waveform tomography and Gravity (geoid and gravity anomalies and gradiometric measurements<br> from ESA's GOCE mission) INversion model of the TEmpeRature and Composition of the lithosphere and upper mantle at<br> global scale. WINTERC-G is based on upon the integrated geophysical-petrological<br> approach LitMod (Afonso et al., 2008; Fullea et al. 2009) and, hence, all<br> relevant mantle rock physical properties modelled (seismic velocities and density) are<br> computed within a thermodynamically self-consistent framework allowing for a direct<br> parameterization in terms of the temperature and composition of the lithosphere-upper<br> mantle. The inversion is a two-step procedure. In a first step, we invert surface-wave, Rayleigh and Love<br> fundamental mode dispersion curves from a high resolution global dataset measured using waveform inversion,<br> along with surface heat flow and elevation (isostasy) for temperature and crustal structure<br> using a point-wise, non-linear, gradient-search inversion<br> over a triangular grid with an average 225 km lateral inter-knot spacing. In a second step we<br> use a fully parallelized spherical harmonic formalism to invert satellite gravity field data in<br> order to refine the initial crustal density and mantle composition distributions from the step 1<br> for a fixed temperature field.</p> <p>The parameter space in step 1 includes crust (densities and S-wave velocities for a three-layered crust)<br> and mantle variables (the depth of the thermal Lithosphere-Athenosphere-Boundary,<br> the thickness of the sublithospheric thermal buffer, the sublithospheric temperatures at 3 different<br> equispaced nodes down to 400 km, the lithospheric and sublithospheric mantle compositon, and<br> the the radial anisotropy at the 3 crustal layers and at 56, 80, 110, 150, 200, 260, 330,<br> and 400 km depths.</p> <p>The parameter space in step 2 is defined by the average crustal density, and the<br> mantle composition in the lithosphere and sublithosphere.<br> We use the output crustal density from step 1 as the<br> initial value in step 2 inversion. Mantle densities are derived based on the output temperature<br> field from step 1 (kept fixed) and the bulk mantle composition inversion variables.</p> <p> </p> <p> </p> <p>*******************************</p> <p>This archive contains the following files:<br> README (this file)<br> WINTERC-G_Vp-Vs.lis (triangular grid)<br> WINTERC-G_rad_anis_Vs.lis (triangular grid)<br> WINTERC-G_Temperature.lis (triangular grid)<br> WINTERC-G_Density.lis (triangular grid)<br> WINTERC-G_LAB.lis (triangular grid)<br> WINTERC_T_rho_1D.z (1D average model of temperature and density)<br> rho_*_out.xyz (0.5 deg egular grid for gravity field)<br> ETOPO2_km_continental.xyz (0.5 deg egular grid for gravity field)<br> ETOPO2_km_depth_Ice.xyz (0.5 deg egular grid for gravity field)<br> ETOPO2_km_depth_Bed.xyz (0.5 deg egular grid for gravity field)<br> Global_Moho_WINTERC-G.xyz (0.5 deg egular grid for gravity field)</p> <p><br> Files in the triangular grid with an average 225 km lateral inter-knot spacing (12232 grid points):</p> <p>* WINTERC-G_Vp-Vs.lis: Vp and Vs (in km/s) in all model columns with a vertical grid step of 2 km<br> Format for each column:<br> #Column number longitude latitude depth(km, <0 downwards) Vp (km/s) Vs(km/s)<br> 5640 93.72 4.135 -5.0 3.91 2.11</p> <p><br> * WINTERC-G_rad_anis_Vs.lis: radial anisotropy, (Vsh-Vsv)/Vs_iso (in %) in all model columns with a vertical grid step of 2 km<br> Format for each column:<br> #Column number longitude latitude depth(km, <0 downwards) anisotropy (%)</p> <p>* WINTERC-G_Temperature.lis: temperature (in ºC) in all model columns with a vertical grid step of 2 km<br> Format for each column:<br> #Column number longitude latitude depth (km, <0 downwards) T (ºC) dT (%) dT(K) <br> 6437 297.20 -2.524 -259.000 1431.9 -1.91 -27.9<br> The anomalies dT are in % and K with respect to the 1D model in WINTERC_T_rho_1D.z (column 2).</p> <p>* WINTERC-G_Density.lis: density (in kg/m3) in all model columns with a vertical grid step of 2 km<br> Format for each column:<br> #Column number longitude latitude depth(km, <0 downwards) rho (kg/m3) drho(%) drho(kg/m3)<br> The anomalies drho are in % and kg/m3 with respect to the 1D model in WINTERC_T_rho_1D.z (column 3).</p> <p>* WINTERC_T_rho_1D.z: 1D average model of temperature (column 2 in ºC) and density (column 3 in kg/m3) with a vertical grid step of 2 km <br> 5.00000000 0.0000000000000000 6.0259973839110526<br> 3.00000000 0.0000000000000000 38.960571309690394<br> 1.00000000 0.33634006819423840 174.42296045978722<br> -1.00000000 3.8888495253719624 1692.8437489147236<br> -3.00000000 23.974111923225379 1863.8834351235944<br> -5.00000000 47.727920701943034 2568.2414495590924<br> -7.00000000 89.633398074381162 2819.8386016341910<br> -9.00000000 137.01489361657013 2839.5325893195904<br> -11.0000000 182.35233447017222 2897.6600872935287<br> -13.0000000 224.46247069572485 2945.2036923862997<br> -15.0000000 260.63395547331390 3069.6809340323475<br> -17.0000000 292.28175449521456 3132.4574175461721<br> -19.0000000 322.29571965406632 3145.5747337463940<br> -21.0000000 351.58698283375054 3157.2401512748038<br> -23.0000000 380.30002225705056 3177.0000420059773<br> -25.0000000 408.50259805632055 3183.6651032398490<br> -27.0000000 436.22632217636487 3190.9586785996116<br> -29.0000000 463.48733903170023 3198.9369509456310<br> -31.0000000 490.29841705549831 3209.7229872383764<br> -33.0000000 516.71149258457456 3221.6329506091679<br> ...</p> <p>Files in the interpolated regular grid at 0.5 deg lateral resolution used for gravity field data inversion:</p> <p> * rho_c_out.xyz: average crustal density<br> * rho_submoho_out.xyz: mantle density below the Moho discontinuity<br> * rho_*_out.xyz: mantle density defined at different model depths: 20, 35, 56, 80, 110, 150, 200, 260, 330 and 400 km.</p> <p> Format for the density files:<br> # longitude latitude density (kg/m3)<br> <br> Files containing layer discontinuities:</p> <p> * ETOPO2_km_continental.xyz: surface elevation including ice sheet and 0 in marine areas (km, <0 upwards)</p> <p> * ETOPO2_km_depth_Ice.xyz: surface elevation including ice sheet (km, >0 downwards, <0 above sea level)</p> <p> * ETOPO2_km_depth_Bed.xyz: bedrock surface elevation without ice sheet (km, >0 downwards, <0 above sea level)</p> <p> * Global_Moho_WINTERC-G.xyz: crust-mantle discontinuity depth (km, >0 downwards)</p> <p> Format for the discontinuity files:<br> # longitude latitude depth (km)<br> <br> <br> The gravity field in WINTERC-G is computed using an spherical harmonic formalism and a model discretization<br> in 13 layers with laterally varying density. The first 7 layers are characterized by top and bottom boundaries with laterally varying radius whereas the last 6 layers are defined by top and bottom boundaries with constant radius:</p> <p>1/ Water: from ETOPO2_km_continental.xyz to ETOPO2_km_depth_Ice.xyz with rho=1030 kg/m3 (constant vertically)</p> <p>2/ Ice: from ETOPO2_km_depth_Ice.xyz to ETOPO2_km_depth_Bed.xyz with rho=910 kg/m3 (constant vertically)</p> <p>3/ Crust: from ETOPO2_km_depth_Bed to Global_Moho_WINTERC-G.xyz with rho=rho_c_out.xyz (constant vertically)</p> <p>4/ submoho-20km: from Global_Moho_WINTERC-G.xyz to z_20km (file with 20 km everywhere except where z_moho>20km) with rho=rho_submoho_out.xyz (top) and rho=rho_20km_out.xyz (bottom)</p> <p>5/ 20km-36km: from z_20km (file with 20 km everywhere except where z_moho>20km) to z_36km (file with 36 km everywhere except where z_moho>36km) with rho=rho_20km_out.xyz (top) and rho=rho_36km_out.xyz (bottom)</p> <p>6/ 36km-56km: from z_36km (file with 36 km everywhere except where z_moho>36km) to z_56km (file with 56 km everywhere except where z_moho>56km) with rho=rho_36km_out.xyz (top) and rho=rho_56km_out.xyz (bottom)</p> <p>7/ 56km-80km: from z_56km (file with 56 km everywhere except where z_moho>56km) to 80 km depth with rho=rho_56km_out.xyz (top) and rho=rho_80km_out.xyz (bottom)</p> <p>The next 6 layers are computed using the constant radius option:</p> <p>8/ 80km-110km: from z=80km to z=110 km with rho=rho_80km_out.xyz (top) and rho=rho_110km_out.xyz (bottom)</p> <p>9/ 110km-150km: from z=110km to z=150 km with rho=rho_110km_out.xyz (top) and rho=rho_150km_out.xyz (bottom)</p> <p>10/ 150km-200km: from z=150km to z=200 km with rho=rho_150km_out.xyz (top) and rho=rho_200km_out.xyz (bottom)</p> <p>11/ 200km-260km: from z=200km to z=260 km with rho=rho_200km_out.xyz (top) and rho=rho_260km_out.xyz (bottom)</p> <p>12/ 260km-330km: from z=260km to z=330 km with rho=rho_260km_out.xyz (top) and rho=rho_330km_out.xyz (bottom)</p> <p>13/ 330km-400km: from z=330km to z=400 km with rho=rho_330km_out.xyz (top) and rho=rho_400km_out.xyz (bottom)</p> <p> </p> <p> </p>
Normal mode splitting function predictions for mantle anisotropy
<p>Predictions for normal mode splitting functions for 6 models of mantle anisotropy, accompanying the paper published in Geophysical Journal International by Restelli, Koelemeijer & Ferreira (2023). This is version 2 related to the revised manuscript. </p> <p>More details can be found in the README. </p>
Shear Wave Splitting and Mantle Flow beneath Alaska Data Set
<p>Entire data set for the (under review) publication "Shear Wave Splitting in Alaska."</p> <p>McPherson_S1_Station_Info is a table that contains the following columns (with header row): Station Name, Network, Latitude (Deg), Longitude (Deg). This is a table of all the seismic stations in Alaska and western Canada that we downloaded data from. Only stations that were active from Jan 1, 2010, to Aug 18, 2017 are included.</p> <p>McPherson_S2_Event_Info is a table that contains the following columns (with header row): Julian Date, Origin Time, Latitude (Deg), Longitude (Deg), Depth (km), Magnitude (Mw). This is a table of all the seismic events that occurred between Jan 1, 2010, to Aug 18, 2017 within the distance range 80 to 140 degrees from a station, over moment magnitude 5.</p> <p>McPherson_S3_Results_Info is a table that contains the following columns (with header row): Station Name, Back Azimuth (Deg), Distance (Deg), Fast Direction (Deg), Lower Bound (Deg), Upper Bound (Deg), Time Difference (sec), Lower Bound (sec), Upper Bound (sec), Julian Date, Origin Time. This table contains all of the minimum energy method (Silver & Chan, 1991) results that are displayed in Figures 4, 6-12 of the paper under review.</p> <p>McPherson_S4_Nulls_Info is a table that contains the following columns (with header row): Station Name, Back Azimuth (Deg), Distance (Deg), Julian Date, Origin Time. This tables contains all the null results displayed in Figure 5 of the paper under review.</p>
Dataset for "Deflected Mantle Flow and Shearing-aligned Lithospheric Melt under the Strike-slip Dead Sea Rift"
<p>Dataset 1: All of the individual shear-wave splitting measurements in the Dead Sea rift, including 1855 A and B measurements and 1088 Null measurements</p> <p>Dataset 2: Three component seismic waveforms used for shear-wave splitting measurement, for PKS, SKKS, and SKS, respectively</p> <p>Dataset 3: Earthquake catalogue with magnitude Mb 2.6 or above in the Dead Sea rift. Downloaded from the International Seismological Centre (https://www.isc.ac.uk/)</p> <p> Reference: International Seismological Centre (2024), On-line Bulletin, [Dataset] doi:10.31905/D808B830</p> <p>Dataset 4: Holocene Volcano List. Downloaded from Global Volcanism Program (https://volcano.si.edu/volcanolist_holocene.cfm)</p> <p> Reference: Global Volcanism Program, 2024. Volcanoes of the World (v. 5.2.2; 22 Aug 2024). Distributed by Smithsonian Institution, compiled by Venzke, E. [Database] doi:10.5479/si.GVP.VOTW5-2024.5.2</p>
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>
Datasets for "Ice Content of Mantling Materials in Deuteronilus Mensae, Mars"
<p>These are supporting datasets for the paper titled, "Ice Content of Mantling Materials in Deuteronilus Mensae, Mars," Baker and Carter, 2023, Journal of Geophysical Research: Planets. Data Set S1 (ds01.txt) is a text file table of SHARAD radargrams analyzed in the paper. Data Sets S2 and S3 (ds02.zip and ds03.zip) are provided as ESRI shapefiles (.shp) and compressed as separate zip files. The shapefiles can be opened in most geographical information systems (GIS) software. Shapefiles consist of three individual files: main file (.shp), index file (.shx), and dBASE table (.dbf). Descriptions of each column or attribute in the text file or shapefile is provided in the readme documentation.</p>
Unified Structures of Temperature and Composition of Lower Mantle (USTCLM)
<p>Compositional and thermal state of the lower mantle from joint 3D inversion with seismic tomography and mineral elasticity</p> <p>Data including Vp&Vs structure, chemical proportion, and thermal and density structure.</p> <p><br> </p>
Unified Structures of Temperature and Composition of Lower Mantle (USTCLM)
<p>Unified Structures of Temperature and Composition of Lower Mantle (USTCLM)</p> <p>Author: Xin Deng <br> 769615090@qq.com</p> <p>Compositional and thermal state of the lower mantle from joint 3D inversion with seismic tomography and mineral elasticity</p> <p>Data including Vp&Vs structure, chemical proportion, and thermal and density structure.</p> <p><br> Related: https://doi.org/10.1073/pnas.2220178120</p>
Dataset for "Adjoint Waveform Tomography for Crustal and Upper Mantle Structure the Middle East and Southwest Asia for Improved Waveform Simulations Using Openly Available Broadband Data"
<p>This dataset contains the MESWA (Middle East and Southwest Asia) seismic model and auxiliary data used in the creation of the model (Rodgers, 2023). MESWA is a three-dimensional model of the seismic properties of crust and upper mantle of the Middle East and Southwest Asia. The MESWA model is provided in NetCDF format (readable by for example, <em>xarray</em>, Hoyer & Hamman, <a href="https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2021JB022930#jgrb55516-bib-0057">2017</a>) and HDF5 format for viewing with <em>ParaView</em> (Ahrens et al., <a href="https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2021JB022930#jgrb55516-bib-0002">2005</a>) and interaction with <em>Salvus</em> (Afanasiev et al., <a href="https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2021JB022930#jgrb55516-bib-0001">2019</a>). </p> <p> </p> <p>Also included are the earthquake source parameters for all 327 Global Centroid Moment Tensor events considered in this study in ASCII text format. Also included are lists of the selected 192 inversion events and 66 validation events in ASCII text format. Lastly, we include a list of all receivers used in the creation and validation of MESWA. This is a simple ASCII file with the event name and receiver name (composed of the network_code and station_code).</p> <p> </p> <p>The following table provides a listing of the files in the dataset:</p> <table> <tbody> <tr> <td> <p><strong>File</strong></p> </td> <td> <p><strong>Description</strong></p> </td> </tr> <tr> <td> <p>MESWA.nc</p> </td> <td> <p>MESWA model in NetCDF format</p> </td> </tr> <tr> <td> <p>MESWA.h5</p> </td> <td> <p>MESWA model in HDF5 format, used by Salvus</p> </td> </tr> <tr> <td> <p>MESWA.xmdf</p> </td> <td> <p>Auxiliary file for MESWA.h5, used to import model into Paraview</p> </td> </tr> <tr> <td> <p>events_project.csv</p> </td> <td> <p>Table of event source parameters for all 327 events considered in the project</p> </td> </tr> <tr> <td> <p>inversion_events_192.csv</p> </td> <td> <p>Table of 192 inversion events </p> <p>(ASCII comma separated value)</p> </td> </tr> <tr> <td> <p>validation_events_66.csv</p> </td> <td> <p>Table of 66 validation events </p> <p>(ASCII comma separated value)</p> </td> </tr> <tr> <td> <p>events_receivers_inversion.csv</p> </td> <td> <p>Table of waveform (event-receiver-channel) data used in the inversion (ASCII comma separated value)</p> </td> </tr> <tr> <td> <p>events_receivers_validation.csv</p> </td> <td> <p>Table of waveform (event-receiver-channel) data used in the validation (ASCII comma separated value)</p> </td> </tr> </tbody> </table> <p> </p> <p> </p> <p><strong>References</strong></p> <p>Afanasiev, M, C Boehm, M van Driel, L Krischer, M Rietmann, DA May, MG Knepley, and A Fichtner (2019). Modular and flexible spectral-element waveform modelling in two and three dimensions, <em>Geophys. J. Int.</em>, 216(3), 1675–1692, doi: 10.1093/gji/ggy469</p> <p> </p> <p>Ahrens, J., Geveci, B., & Law, C. (2005). Paraview: An end-user tool for large data visualization. <em>The Visualization Handbook</em>, 717(8). <a href="https://doi.org/10.1016/b978-012387582-2/50038-1">https://doi.org/10.1016/b978-012387582-2/50038-1</a></p> <p> </p> <p>Hoyer, S., & Hamman, J. (2017). Xarray: N-D labeled arrays and datasets in Python. <em>Journal of Open Research Software</em>, 5(1). <a href="https://doi.org/10.5334/jors.148">https://doi.org/10.5334/jors.148</a></p> <p> </p> <p>Rodgers, A. (2023). Adjoint Waveform Tomography for Crustal and Upper Mantle Structure the Middle East and Southwest Asia for Improved Waveform Simulations Using Openly Available Broadband Data, technical report, LLNL-TR- 851939.</p> <p> </p> <p><strong>Acknowledgements</strong></p> <p>This project was support by Lawrence Livermore National Laboratory’s Laboratory Directed Research and Development project 20-ERD-008 and the National Nuclear Security Administration. This work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344. LLNL-MI-852402</p> <p> </p>
Supplementary data to "Destruction and regrowth of lithospheric mantle beneath large igneous provinces"
<p>Database files to accompany "<em>Destruction and regrowth of lithospheric mantle beneath large igneous provinces</em>", By <a href="http://www.science.org/doi/10.1126/sciadv.adf6216">Stephenson et al. (2023)</a>. The article can be accessed by following <a href="http://www.science.org/doi/10.1126/sciadv.adf6216">this permanent link</a>.</p> <p>The primary resources in this database are (i) estimates of melt equilibration pressure and temperature calculated using the scheme of <a href="https://github.com/fmcnab/meltPT">McNab & Ball (2023)</a>; (ii) a database of lithospheric thickness estimates beneath modern intraplate magmatic provinces using geochemical and seismological techniques; (iii) a database of the outlines and ages of large igneous provinces, substantially updated from <a href="http://https://doi.org/10.1029/93RG02508">Coffin & Eldholm (1994)</a>, and <a href="https://doi.org/10.5670/oceanog.2006.13">Coffin et al. (2006)</a>; (iv) a database of large igneous province eruption centres; and (v) a document of references used to build these databases. Files are numbered as in the Supplementary Information of <a href="http://www.science.org/doi/10.1126/sciadv.adf6216">the paper.</a> Please see below for more details.</p> <ol> <li><strong>Data S1</strong>. A database of global geochemical compositions of mafic intraplate magmatic rocks compiled by <a href="http://doi.org/10.1038/s41467-021-22323-9">Ball et al (2021)</a>, and corresponding estimates of melt equilibration pressure and temperature P<sub>eq</sub> and T<sub>eq</sub>, respectively; <a href="http://www.science.org/doi/10.1126/sciadv.adf6216">this study</a>). Note that authors should cite <a href="http://doi.org/10.1038/s41467-021-22323-9">Ball et al. (2021)</a> in reference to the global geochemical database. They should cite <a href="http://www.science.org/doi/10.1126/sciadv.adf6216">Stephenson et al (2023)</a> in reference to the global equilibration pressure and temperature estimates, in which case they should also cite <a href="http://github.com/fmcnab/meltPT">McNab & Ball (2023)</a>, whose software was used to calculate P<sub>eq</sub> and T<sub>eq</sub>.</li> <li><strong>Data S2</strong>. A spreadsheet containing modern-day lithospheric thickness estimates beneath modern intraplate provinces. For complete references to geochemical analyses contained in this database, please see <a href="https://doi.org/10.1038/s41467-021-22323-9">Ball et al (2021)</a>. The database includes lithospheric thickness estimates obtained <ul> <li>by exploiting melt equilibration pressure and temperature <a href="http://www.science.org/doi/10.1126/sciadv.adf6216">(this study)</a>;</li> <li>by inverse modelling of rare earth element compositions <a href="https://doi.org/10.1038/s41467-021-22323-9">(Ball et al., 2021)</a>; and</li> <li>from the lithospheric thickness model of<a href="https://doi.org/10.1038/s41561-020-0593-2"> Hoggard et al. (2020)</a>, which is based upon the tomographic model of <a href="https://doi.org/10.1093/gji/ggt095">Schaeffer & Lebedev (2013)</a>.</li> </ul> </li> <li><strong>Data S3</strong> & <strong>S4</strong>. A database containing outlines of magmatic provinces dating back to 750 Ma, including <ul> <li>a directory (Data_S3.zip) containing the unfiltered database shape files (lips.shp, lips.shx, lips.dbf, lips.cpg). This directory also contains the same data in a multisegment text file for plotting in the Generic Mapping Tools (polys_ID_age_unfiltered.dat) in which each polygon is separated by '>' where the header indicates polygon ID and time since eruption. And</li> <li>a database filtered for final magmatic event in a given location (Data_S4.dat), where each polygon header also contains '>' ID age polygon_area'. See <a href="http://www.science.org/doi/10.1126/sciadv.adf6216">the paper</a> for methodological details.</li> </ul> </li> <li><strong>Data S5</strong>. A database of located LIP eruption centres.</li> <li><strong>Data S6</strong>. A pdf document of references. The document includes <ul> <li>references used to update locations and ages of the large igneous province database of <a href="http://doi.org/10.5670/oceanog.2006.13">Coffin et al. (2006)</a>;</li> <li>references for existing lithospheric thickness models used test our observed LAB depth as a function of time relationship; and</li> <li>references used to locate the eruption centres of mantle plumes (i.e. Data S5; <a href="http://www.science.org/doi/10.1126/sciadv.adf6216">this study</a>).</li> </ul> </li> </ol>
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>
ScienceDex guides
Understand access before you commit
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)
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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.