DOI: 10.5281/zenodo.4031646
title: Lamb et al. (2020): Global Whole Lithosphere Isostasy datasets

description: Model outputs from Lamb, S., Moore, J., Perez-Gussinye, M., Stern, T. (2020). Global whole lithosphere isostasy: implications for surface elevations, structure, strength and densities of the continental lithosphere, Geochem, Geophys, Geosyst., doi :10.1029/2020GC009150 Data sets supplied here are the outcome of modelling described in the text. Files are given in either ASCII or GMT grd format. Data Set S1 (ds01.grd). Gridded crustal model of Antarctica based on whole lithosphere isostasy described in this study, and used to construct Figure 7c. Data columns are: x distance, y distance, crustal thickness. In GMT grd format with bounds in km -R-3000/3000/-3000/3000 -I5. Uses same projection as Bedmap 2 - see Fretwell et al. (2013) for details of projection. Suggested colour palette in GMT: seis -T0/60/2.5 -I Data Set S2 (ds02.xyz). Average elevation and crustal thickness of continental interiors calculated in this study, used to plot Figure 3c and described in text, using a standard lithospheric thickness of 100 km. Data columns are: Name, area, average elevation (m), average reduced elevation for 100 km standard lithosphere (m), average lithospheric thickness (km), average crustal thickness (km), 1 sigma uncertainty in elevation (m) or reduced elevation (m), 1 sigma uncertainty in lithospheric thickness (km), 1 sigma uncertainty in crustal thickness (km). ASCII file. Data Set S3 (ds03.grd). Gridded elevation anomalies (observed elevation – elevation calculated from whole lithosphere isostasy), as described in text and used to construct Figure 8. Data columns are: Longitude, Latitude, elevation anomaly (m). In GMT grd format with bounds in degrees -R-179/179/-60/80 -I1. Suggested colour palette in GMT: seis -T-2000/2000/200 -Z -I -M -D --COLOR_NAN=white Data Set S4 (ds04.grd). Gridded global crustal density perturbation model calculated to give zero elevation anomaly, based on elevation anomalies in Data Set 3, used to plot Fig. 9a. Data columns are: Longitude, Latitude, crustal density perturbation in kgm<sup>-3</sup>. In GMT grd format with bounds in degrees -R-179/179/-60/80 -I1. Suggested colour palette in GMT: seis -T-200/200/10 -Z -I -M -D --COLOR_NAN=white Data Set S5 (ds05.grd). Gridded global conductive lithosphere mantle density perturbation model calculated to give zero elevation anomaly, based on elevation anomalies in Data Set 3, used to plot Fig. 9b. Data columns are: Longitude, Latitude, mantle density perturbation in kgm<sup>-3</sup>. In GMT grd format with bounds in degrees -R-179/179/-60/80 -I1. Suggested clour palette in GMT: seis -T-50/50/5 -Z -I -M -D --COLOR_NAN=white Data Set S6 (ds06.grd). Gridded global crustal thickness perturbation model calculated to give zero elevation anomaly, based on elevation anomalies in Data Set 3, used to plot Fig. 9c. Data columns are: Longitude, Latitude, crustal thickness in km. In GMT grd format with bounds in degrees -R-179/179/-60/80 -I1. Suggested colour palette in GMT: seis -T-10/10/1 -Z -I -M -D --COLOR_NAN=white Data Set S7 (ds07.grd). Gridded global conductive lithosphere thickness perturbation model calculated to give zero elevation anomaly, based on elevation anomalies in Data Set 3, used to plot Fig. 9d. Data columns are: Longitude, Latitude, thickness in km. In GMT grd format with bounds in degrees -R-179/179/-60/80 -I1. Suggested colour palette in GMT: seis -T-100/100/5 -Z -I -M -D --COLOR_NAN=white Data Set S8 (ds08.grd). Compilation of gridded ratios of elastic thickness to conductive lithospheric thickness in the continents used to construct Figure 10c and d. Data columns are: Longitude, Latitude, ratio of elastic thickness to conductive lithospheric thickness from sources cited below. In GMT grd format with bounds in degrees -R-179/179/-60/80 -I1. Suggested colour palette in GMT: rainbow -T0/1/0.05 -Z -I -D --COLOR_NAN=white <em>Data references:</em> <em>Lowry, A.R. and Pérez-Gussinyé, M., 2011. The role of crustal quartz in controlling Cordilleran deformation. Nature, 471(7338), 353-357.</em> <em>Pérez‐Gussinyé, M., Lowry, A.R., Watts, A.B. and Velicogna, I., (2004). On the recovery of effective elastic thickness using spectral methods: examples from synthetic data and from the Fennoscandian Shield. Journal of Geophysical Research: Solid Earth, 109(B10).</em> <em>Pérez-Gussinyé, M. and Watts, A.B., (2005). The long-term strength of Europe and its implications for plate-forming processes. Nature, 436(7049), 381.</em> <em>Pérez‐Gussinyé, M., Lowry, A.R. and Watts, A.B., (2007). Effective elastic thickness of South America and its implications for intracontinental deformation. Geochemistry, Geophysics, Geosystems, 8(5).</em> <em>Pérez‐Gussinyé, M., Lowry, A.R., Phipps Morgan, J. and Tassara, A., (2008). Effective elastic thickness variations along the Andean margin and their relationship to subduction geometry. Geochemistry, Geophysics, Geosystems, 9(2).</em> <em>Pérez-Gussinyé, M., Metois, M., Fernández, M., Vergés, J., Fullea, J. and Lowry, A.R., (2009). Effective elastic thickness of Africa and its relationship to other proxies for lithospheric structure and surface tectonics. Earth and Planetary Science Letters, 287(1-2), 152-167.</em> <em>Swain, C.J. and Kirby, J.F., 2006. An effective elastic thickness map of Australia from wavelet transforms of gravity and topography using Forsyth's method. Geophysical Research Letters, 33(2).</em>