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WINTERC-G: a global upper mantle thermochemical model from coupled geophysical–petrological inversion of seismic waveforms, heat flow, surface elevation and gravity satellite data

WINTERC-G: A global, temperature and compositional model of the lithosphere            and upper mantle. Version:  v5.4, December 2020, J. Fullea, S. Lebedev, Z. Martinec, N. Celli            Contact:  Javier Fullea (jfullea@ucm.es)           Facultad de Fisica,           Universidad Complutense de Madrid (UCM),           Spain           ////////           Geophysics Section,           Dublin Institute for Advanced Studies           Dublin, Ireland   TYPE:  This contains files with:  i) the model directly on the triangular grid solved for in the surface wave inversion.  ii) an interpolated grid at 0.5 deg lateral resolution for the density and density discontinuities used in the gravity field data inversion   If you have any questions regarding the methodology or the construction of the model, please contact the authors. If you use the model, we would request that you cite the reference indicated below, and appreciate your feedback regarding the model and its application. Citation: 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. ******************************* Summary: construction of the model. WINTERC-G is a Waveform tomography and Gravity (geoid and gravity anomalies and gradiometric measurements from ESA's GOCE mission) INversion model of the TEmpeRature and Composition of the lithosphere and upper mantle at global scale. WINTERC-G is based on upon the integrated geophysical-petrological approach LitMod (Afonso et al., 2008; Fullea et al. 2009) and, hence, all relevant mantle rock physical properties modelled (seismic velocities and density) are computed within a thermodynamically self-consistent framework allowing for a direct parameterization in terms of the temperature and composition of the lithosphere-upper mantle. The inversion is a two-step procedure. In a first step, we invert surface-wave, Rayleigh and Love fundamental mode dispersion curves from a high resolution global dataset measured using waveform inversion, along with surface heat flow and elevation (isostasy) for temperature and crustal structure using a point-wise, non-linear, gradient-search inversion over a triangular grid with an average 225 km lateral inter-knot spacing. In a second step we use a fully parallelized spherical harmonic formalism to invert satellite gravity field data in order to refine the initial crustal density and mantle composition distributions from the step 1 for a fixed temperature field. The parameter space in step 1 includes crust (densities and S-wave velocities for a three-layered crust)  and mantle variables (the depth of the thermal Lithosphere-Athenosphere-Boundary, the thickness of the sublithospheric thermal buffer, the sublithospheric temperatures at 3 different equispaced nodes down to 400 km, the lithospheric and sublithospheric mantle compositon, and the the radial anisotropy at the 3 crustal layers and at 56, 80, 110, 150, 200, 260, 330, and 400 km depths. The parameter space in step 2 is defined by the average crustal density, and the mantle composition in the lithosphere and sublithosphere. We use the output crustal density from step 1 as the initial value in step 2 inversion. Mantle densities are derived based on the output temperature field from step 1 (kept fixed) and the bulk mantle composition inversion variables.     ******************************* This archive contains the following files:   README (this file)   WINTERC-G_Vp-Vs.lis (triangular grid)   WINTERC-G_rad_anis_Vs.lis (triangular grid)   WINTERC-G_Temperature.lis (triangular grid)   WINTERC-G_Density.lis (triangular grid)   WINTERC-G_LAB.lis (triangular grid)   WINTERC_T_rho_1D.z (1D average model of temperature and density)   rho_*_out.xyz (0.5 deg egular grid for gravity field)   ETOPO2_km_continental.xyz (0.5 deg egular grid for gravity field)   ETOPO2_km_depth_Ice.xyz (0.5 deg egular grid for gravity field)   ETOPO2_km_depth_Bed.xyz (0.5 deg egular grid for gravity field)   Global_Moho_WINTERC-G.xyz (0.5 deg egular grid for gravity field) Files in the triangular grid with an average 225 km lateral inter-knot spacing (12232 grid points): * WINTERC-G_Vp-Vs.lis: Vp and Vs (in km/s) in all model columns with a vertical grid step of 2 km  Format for each column:  #Column number longitude latitude depth(km, <0 downwards) Vp (km/s) Vs(km/s)      5640         93.72     4.135       -5.0                3.91     2.11 * 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   Format for each column:   #Column number longitude latitude depth(km, <0 downwards) anisotropy (%) * WINTERC-G_Temperature.lis: temperature (in ºC) in all model columns with a vertical grid step of 2 km  Format for each column:   #Column number longitude latitude depth (km, <0 downwards) T (ºC)   dT (%)   dT(K)         6437         297.20    -2.524     -259.000             1431.9   -1.91     -27.9   The anomalies dT are in % and K with respect to the 1D model in WINTERC_T_rho_1D.z (column 2). * WINTERC-G_Density.lis: density (in kg/m3) in all model columns with a vertical grid step of 2 km  Format for each column:   #Column number longitude latitude depth(km, <0 downwards) rho (kg/m3) drho(%) drho(kg/m3)   The anomalies drho are in % and kg/m3 with respect to the 1D model in WINTERC_T_rho_1D.z (column 3). * 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      5.00000000       0.0000000000000000        6.0259973839110526    3.00000000       0.0000000000000000        38.960571309690394    1.00000000      0.33634006819423840        174.42296045978722   -1.00000000       3.8888495253719624        1692.8437489147236   -3.00000000       23.974111923225379        1863.8834351235944   -5.00000000       47.727920701943034        2568.2414495590924   -7.00000000       89.633398074381162        2819.8386016341910   -9.00000000       137.01489361657013        2839.5325893195904   -11.0000000       182.35233447017222        2897.6600872935287   -13.0000000       224.46247069572485        2945.2036923862997   -15.0000000       260.63395547331390        3069.6809340323475   -17.0000000       292.28175449521456        3132.4574175461721   -19.0000000       322.29571965406632        3145.5747337463940   -21.0000000       351.58698283375054        3157.2401512748038   -23.0000000       380.30002225705056        3177.0000420059773   -25.0000000       408.50259805632055        3183.6651032398490   -27.0000000       436.22632217636487        3190.9586785996116   -29.0000000       463.48733903170023        3198.9369509456310   -31.0000000       490.29841705549831        3209.7229872383764   -33.0000000       516.71149258457456        3221.6329506091679   ... Files in the interpolated regular grid at 0.5 deg lateral resolution used for gravity field data inversion:   * rho_c_out.xyz: average crustal density   * rho_submoho_out.xyz: mantle density below the Moho discontinuity   * rho_*_out.xyz: mantle density defined at different model depths: 20, 35, 56, 80, 110, 150, 200, 260, 330 and 400 km.   Format for the density files:   # longitude latitude density (kg/m3)     Files containing layer discontinuities:  * ETOPO2_km_continental.xyz: surface elevation including ice sheet and 0 in marine areas (km, <0 upwards)  * ETOPO2_km_depth_Ice.xyz: surface elevation including ice sheet (km, >0 downwards, <0 above sea level)  * ETOPO2_km_depth_Bed.xyz: bedrock surface elevation without ice sheet (km, >0 downwards, <0 above sea level)  * Global_Moho_WINTERC-G.xyz: crust-mantle discontinuity depth (km, >0 downwards)   Format for the discontinuity files:    # longitude latitude depth (km)     The gravity field in WINTERC-G is computed using an spherical harmonic formalism and a model discretization 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: 1/ Water: from ETOPO2_km_continental.xyz to ETOPO2_km_depth_Ice.xyz with rho=1030 kg/m3 (constant vertically) 2/ Ice: from ETOPO2_km_depth_Ice.xyz to ETOPO2_km_depth_Bed.xyz  with rho=910 kg/m3 (constant vertically) 3/ Crust: from ETOPO2_km_depth_Bed to Global_Moho_WINTERC-G.xyz with rho=rho_c_out.xyz (constant vertically) 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) 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) 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) 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) The next 6 layers are computed using the constant radius option: 8/ 80km-110km: from z=80km to z=110 km with rho=rho_80km_out.xyz (top) and rho=rho_110km_out.xyz (bottom) 9/ 110km-150km: from z=110km to z=150 km with rho=rho_110km_out.xyz (top) and rho=rho_150km_out.xyz (bottom) 10/ 150km-200km: from z=150km to z=200 km with rho=rho_150km_out.xyz (top) and rho=rho_200km_out.xyz (bottom) 11/ 200km-260km: from z=200km to z=260 km with rho=rho_200km_out.xyz (top) and rho=rho_260km_out.xyz (bottom) 12/ 260km-330km: from z=260km to z=330 km with rho=rho_260km_out.xyz (top) and rho=rho_330km_out.xyz (bottom) 13/ 330km-400km: from z=330km to z=400 km with rho=rho_330km_out.xyz (top) and rho=rho_400km_out.xyz (bottom)

ShareScore

44/100

Overall dataset sharing score

Score breakdown

These five areas show where the dataset supports — or may limit — practical reuse.

Stewardship: 8
Harmonization: 4
Access: 16
Reuse readiness: 8
Engagement: 8

Topics

Composition and structure of the mantle, Gravity anomalies and Earth structure, Joint inversion, Seismic tomography, Cratons, Mid-ocean ridge processes