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17 results for “Petrology”
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>
Data Tables from contribution titled "Joint geophysical-petrological modeling on the Ivrea geophysical body beneath Valsesia, Italy: Constraints on the continental lower crust" published in Geochemistry, Geophysics, Geosystems
<p><strong>TABLE CAPTIONS</strong></p> <p><strong>Table 1: </strong>Average and specific bulk compositions of the representative exposed primitive rocks of the deep lower crust and upper mantle of the IVZ (Balmuccia and Lower Mafic Complex in Valsesia, Finero in Val Cannobina, and Sessera river in Val Sessera) used for the Perple_X calculations using the two thermodynamic models STX11 and HP02. Mn, Ni, P, and Cr were not used for the Perple_X calculations. Mg# is calculated as Mg / (Mg + Fe) (mole fractions). Symbols in the last row indicate the rock compositions that are reported (✓) and not reported (✗) in Figure 5. Average compositions are normalized to 100 wt.% on a volatile-free basis; specific compositions report original totals and H<sub>2</sub>O contents estimated based on the volumetric proportions hydrous minerals (amphibole and phlogopite) at the scale of the bulk rock. References: 1) Voshage et al. (1990); 2) Voshage et al. (1990), Shervais and Mukasa (1991), Hartmann and Wedepohl (1993), Rivalenti et al. (1995), and Mukasa and Shervais (1999); 3) Pin and Sills (1986); 4) Pin and Sills (1986), Shervais and Mukasa (1991), Hartmann and Wedepohl (1993), Rivalenti et al. (1995), and Mukasa and Shervais (1999); 5) Shervais and Mukasa (1991) and Mazzucchelli et al. (2009); 6) Sinigoi et al. (1991; 2011); 7) Hartmann and Wedepohl (1993); 8) Coltorti and Siena (1984); 9) Siena and Coltorti (1989), Lu et al. (1997a; b), and Stähle et al. (2001).</p> <p> </p> <p><strong>Table 2: </strong>Summary of <em>V<sub>P</sub></em> and <em>r</em> from the thermodynamic calculations based on representative rock compositions listed in Table 1. Mineral abbreviations: Pl = plagioclase, Spl = spinel, Grt = garnet, Ky = kyanite, Px = pyroxene, Cr-Di = Cr-diopisde, Am = amphibole, Phl = phlogopite.</p>
Data for figures in: Modal petrology and mineral chemistry of Apollo 17 Drive Tube Section 73002
<p class="MsoNormal">The Apollo 17 mission returned samples from the Taurus-Littrow Valley of the Moon. Key features of the site are a basaltic valley floor partially enclosed by South Massif and North Massif mountains and the Sculptured Hills, which consist of feldspar-rich, highland lithologies. A recently opened soil core sampled an inferred landslide deposit at the base of South Massif. Study of a suite of polished grain mounts of six size fractions of <1 mm material from 14 depth intervals of the ~18 cm soil column shows that all size fractions from the upper 5–6 cm are richer in agglutinates, an indicator of surface exposure, than the deeper material, which is among the most agglutinate-poor Apollo 17 regolith reported. Regolith breccia, crystalline melt breccia, and noritic igneous rocks are the most abundant fragment types. Mare basalt, glasses, and agglutinates are minor components throughout. The observations are consistent with deposition of the highland-dominated material in a landslide, which did not preserve any previous stratigraphy, followed by in situ maturation, with only minor additions of mare lithologies from nearby basaltic regolith, due to the inefficiency of lateral transport on the Moon.</p>
Supporting material for the article "Insights on the brachinite parent body: a petrological and microstructural study of 10 brachinites"
<p>This upload contains the dataset of the 10 brachinites concerned by the study "Insights on the brachinite parent body: a petrological and microstructural study of 10 brachinites". All files are paired as cpr and crc files, and can be processed with AZtec crystal or MTEX (open-source Matlab toolbox available at https://mtex-toolbox.github.io/).</p>
Data for figures in: Modal petrology and mineral chemistry of Apollo 17 Drive Tube Section 73002
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Hales discontinuity in the southern Indian continental lithosphere: seismological and petrological models
<p>We model the shear wave velocity structure of the Hales-discontinuity beneath the Eastern Dharwar Craton and Southern Granulite Terrain in Southern India using P-wave receiver function (P-RF) analysis and joint inversion with Rayleigh wave phase velocity dispersion. For this study we use data from seismological stations HYB, GBA and KOD. We isolated P-RFs where the Hales phase is distinct and model them using joint data analysis. We also use common conversion point stack profiles constructed by depth migrating P-RFs through the velocity model and show that the Hales discontinuity is undulatory in nature. We perform petrological modeling of the Hales discontinuity and fianlly propose a geodynamic model for its evolution. </p>
Thermal regime and petrologic metamorphism in Alaska: Implications for subduction interface and wedge earthquakes
<p>Characterized by repeated large earthquakes, slow slips, and tectonic tremors with their simultaneous release of large amounts of energy, the unstable subduction interface beneath Alaska presents a chance to understand the composite dynamic transition from deep to shallow subduction channel where these enigmatic fault slips and seismic events occur. The complex subducted slab morphology associated with the frequent occurrence of various types of faulting behaviors in Alaska is poorly understood. Our result shows that the subduction of the Pacific plate and the subsequent release of large amounts of fluid likely contribute to the repeated fast and slow earthquakes there, as evidenced by the petrological metamorphic transition in the incoming plate. The offshore Alaska seismogenic zone, as well as the slow earthquakes identified near the Upper Cook Inlet, compare well with the distribution of slab dehydration slivers, including large destructive earthquakes that have occurred in Alaska. The fluid upwelling from dewatered oceanic crust and the continental wedge serpentinizing is probably related to various transportation pathways controlled by dip angle and upwell in the predominant direction following the subduction channel or veins in the overriding lithosphere.</p>
Determination of complex refractive indices and optical properties of volcanic ashes in the thermal infrared based on generic petrological compositions: supplementary material
<p>This dataset contains supplementary material to the paper "Determination of complex refractive indices and optical properties of volcanic ashes in the thermal infrared based on generic petrological compositions", doi: 10.1016/j.jvolgeores.2021.107174</p> <p>It contains a set of volcanic ash refractive indices and optical properties derived for certain microphysical properties.</p> <p>For more information please consider the manuscript or contact the authors.</p>
X-ray microtomography as a tool for investigating the petrological context of Precambrian cellular remains
<p>Supplementary information from the paper "X-ray microtomography as a tool for investigating the petrological context of Precambrian cellular remains", features in a Geological Society Publication in memory of Professor Martin Brasier, University of Oxford.</p> <p>Datasets comprise:<br> -- A zipped Drishti volumes for all CT scans reported in the paper, which can be used for both 3D visualisations and to inspect the underlying data.<br> -- A .7z split zip file of one Drishti volume above 2GB.<br> -- An HDMI movie showing digital visualisations for all of the scans reported in the paper. </p>
The dataset for Evaluation of plume-induced continental crust growth rate in early Earth: Insight from integrated petrological-thermo-mechanical modeling
<p>All data of model results for the paper <em>Evaluation of plume-induced continental crust growth rate in early Earth: Insight from integrated petrological-thermo-mechanical modeling</em>.</p> <p>Contents of this dataset includes:</p> <p>A list for models and data of model results are provided in the zip file. </p> <p>The files suffixed *.grd are grid datas that can be draw by GMT.</p> <p>The files suffixed *.info are datas of the evolution of volume of the continental crust and TTGs in the model.</p> <p>The files suffixed *.prn are datas of P-T condtions of continental crust generation by partial melting.</p> <p>The files suffixed *.py are python codes for visualization of the volume of continental crust and P-T datas.</p>
Petrological and chemical modifications during impact melting and cooling in shocked lunar regolith: Insights from heterogeneous Chang'E-5 impact melt-bearing particle
<p>Petrological, mineralogical and chemical data of the lunar impact-melt bearing particle C10 from the Chang'E-5 regolith, and scripts for mesoscale modeling and mixing composition calculations.</p>
Supplementary Material - PhD Thesis - "Unravelling the heat budget of the Lepontine dome: interdisciplinary geological, petrological, thermodynamic and geochronological study of shear zones"
<p>Supplementary material of the PhD thesis titled:<br> "<strong>Unravelling the heat budget of the Lepontine dome: interdisciplinary geological, petrological, thermodynamic and geochronological study of shear zones</strong>" by <em>Alessia Tagliaferri</em> (2023)</p> <p>Content: Excel table datasets, Matlab codes, figures, movies.</p> <p> </p>
Thermal regime and petrologic metamorphism in Alaska: Implications for subduction interface and wedge earthquakes
Open the record for dataset details and reuse information.
Hales discontinuity in the southern Indian continental lithosphere: seismological and petrological models
Open the record for dataset details and reuse information.
Petrology, Age, and Rift Origin of Ultramafic Lamprophyres (Aillikites) at Mount Webb, a New Alkaline Province in Central Australia
<p>APPENDIX_A: LA-ICP-MS and EPMA analyses for pyrope garnet and Cr diopside used in study.</p>
The Lithospheric Structure of the Saharan Metacraton from 3D Integrated Geophysical-Petrological Modelling
<p>We provide the final lithospheric model of Saharan Metacraton resulting from our work presented in the manuscript. It is part of the archive file “Model_data_2020-02-06”</p>
Multi-stage evolution of the South Australian Craton: petrological constraints on the architecture, lithology, and geochemistry of the lithospheric mantle
<p>APPENDIX_A: LA-ICP-MS and EPMA analyses for pyrope garnet and Cr diopside used in study.</p>
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