Lamb et al. (2020): Global Whole Lithosphere Isostasy datasets

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 th...

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Main Author: Lamb, Simon
Format: Dataset
Language:English
Published: Zenodo 2020
Subjects:
Online Access:https://dx.doi.org/10.5281/zenodo.4031646
https://zenodo.org/record/4031646
id ftdatacite:10.5281/zenodo.4031646
record_format openpolar
institution Open Polar
collection DataCite Metadata Store (German National Library of Science and Technology)
op_collection_id ftdatacite
language English
topic Isostasy
Global lithospheric structure
Global crustal structure
Crustal density
Mantle density
Antarctic crustal structure
Continental elastic thickness
Continental elevations
spellingShingle Isostasy
Global lithospheric structure
Global crustal structure
Crustal density
Mantle density
Antarctic crustal structure
Continental elastic thickness
Continental elevations
Lamb, Simon
Lamb et al. (2020): Global Whole Lithosphere Isostasy datasets
topic_facet Isostasy
Global lithospheric structure
Global crustal structure
Crustal density
Mantle density
Antarctic crustal structure
Continental elastic thickness
Continental elevations
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 -3 . 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 -3 . 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 Data references: Lowry, A.R. and Pérez-Gussinyé, M., 2011. The role of crustal quartz in controlling Cordilleran deformation. Nature, 471(7338), 353-357. 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). 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. 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). 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). 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. 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).
format Dataset
author Lamb, Simon
author_facet Lamb, Simon
author_sort Lamb, Simon
title Lamb et al. (2020): Global Whole Lithosphere Isostasy datasets
title_short Lamb et al. (2020): Global Whole Lithosphere Isostasy datasets
title_full Lamb et al. (2020): Global Whole Lithosphere Isostasy datasets
title_fullStr Lamb et al. (2020): Global Whole Lithosphere Isostasy datasets
title_full_unstemmed Lamb et al. (2020): Global Whole Lithosphere Isostasy datasets
title_sort lamb et al. (2020): global whole lithosphere isostasy datasets
publisher Zenodo
publishDate 2020
url https://dx.doi.org/10.5281/zenodo.4031646
https://zenodo.org/record/4031646
long_lat ENVELOPE(-64.150,-64.150,-84.550,-84.550)
ENVELOPE(-69.117,-69.117,-68.517,-68.517)
geographic Antarctic
Lowry
Perez
geographic_facet Antarctic
Lowry
Perez
genre Antarc*
Antarctic
Antarctica
Fennoscandian
genre_facet Antarc*
Antarctic
Antarctica
Fennoscandian
op_relation https://dx.doi.org/10.5281/zenodo.4031645
op_rights Open Access
Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
cc-by-4.0
info:eu-repo/semantics/openAccess
op_rightsnorm CC-BY
op_doi https://doi.org/10.5281/zenodo.4031646
https://doi.org/10.5281/zenodo.4031645
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spelling ftdatacite:10.5281/zenodo.4031646 2023-05-15T13:36:38+02:00 Lamb et al. (2020): Global Whole Lithosphere Isostasy datasets Lamb, Simon 2020 https://dx.doi.org/10.5281/zenodo.4031646 https://zenodo.org/record/4031646 en eng Zenodo https://dx.doi.org/10.5281/zenodo.4031645 Open Access Creative Commons Attribution 4.0 International https://creativecommons.org/licenses/by/4.0/legalcode cc-by-4.0 info:eu-repo/semantics/openAccess CC-BY Isostasy Global lithospheric structure Global crustal structure Crustal density Mantle density Antarctic crustal structure Continental elastic thickness Continental elevations dataset Dataset 2020 ftdatacite https://doi.org/10.5281/zenodo.4031646 https://doi.org/10.5281/zenodo.4031645 2021-11-05T12:55:41Z 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 -3 . 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 -3 . 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 Data references: Lowry, A.R. and Pérez-Gussinyé, M., 2011. The role of crustal quartz in controlling Cordilleran deformation. Nature, 471(7338), 353-357. 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). 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. 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). 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). 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. 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). Dataset Antarc* Antarctic Antarctica Fennoscandian DataCite Metadata Store (German National Library of Science and Technology) Antarctic Lowry ENVELOPE(-64.150,-64.150,-84.550,-84.550) Perez ENVELOPE(-69.117,-69.117,-68.517,-68.517)