2022
DOI: 10.1029/2022gl099476
|View full text |Cite
|
Sign up to set email alerts
|

Present‐Day Upper‐Mantle Architecture of the Alps: Insights From Data‐Driven Dynamic Modeling

Abstract: The dynamics of the Alps and surrounding regions is still not completely understood, partly because of a non‐unique interpretation of its upper‐mantle architecture. In particular, it is unclear if interpreted slabs are consistent with the observed surface deformation and topography. We derive three end‐member scenarios of lithospheric thickness and slab geometries by clustering available shear‐wave tomography models into a statistical ensemble. We use these scenarios as input for geodynamic simulations and com… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
1
1

Citation Types

0
4
0

Year Published

2023
2023
2024
2024

Publication Types

Select...
4
3

Relationship

2
5

Authors

Journals

citations
Cited by 8 publications
(4 citation statements)
references
References 66 publications
0
4
0
Order By: Relevance
“…(1) Shear wave velocities of a tomographic model (an update of the Collaborative Seismic Earth Model CSEM 24 ) were converted to temperatures and densities, using the Gibbs free-energy minimization method 57,58 through the Python application of 23 . A detailed description of the tomographic model, conversion method and the parameters involved is presented as SI.…”
Section: Methodsmentioning
confidence: 99%
See 1 more Smart Citation
“…(1) Shear wave velocities of a tomographic model (an update of the Collaborative Seismic Earth Model CSEM 24 ) were converted to temperatures and densities, using the Gibbs free-energy minimization method 57,58 through the Python application of 23 . A detailed description of the tomographic model, conversion method and the parameters involved is presented as SI.…”
Section: Methodsmentioning
confidence: 99%
“…2d) underlain by a two-layered crystalline crust (Figs. 2f and g km/s to ~6.5 km/s and an average density of 2700 kg/m3; g) Thickness of the lower mafic crystalline continental crust characterized by average velocities of ~6.5 to 7 km/s and an average density of 3000 kg/m3; h) Thickness of the oceanic crust with an average density of 2900 kg/m3; i) Thickness of the lower crustal high-velocity/high-density bodies, characterized by average velocities > 7 km/s and an average density of 3000 kg/m3 at the passive continental margins near the COT (COT-LCB; derived from 17 ) and by an average density of 3100 kg/m3 along the GIRF (GIFR layer 3) as derived by forward gravity modelling; j) Depth to the thermal Lithosphere-Asthenosphere Boundary (LAB) extracted as the 1300 °C isotherm from the temperature distribution obtained by velocity conversion 23 of the shear wave tomography 24 . Green and blue stippled lines are the previously proposed tracks of the Iceland plume 25,26 .…”
Section: Variation Of Lithospheric Configurationmentioning
confidence: 99%
“…Shear-wave velocities (Vs) at 200 km depth 57 are converted to temperature using Gibbs free-energy minimisation algorithm, for details see 58 . We pre-compute anharmonic Vs from stable phase and mineral assemblages at upper-mantle pressure and temperature conditions, computed using a Gibbs free-energy minimisation algorithm 59 , using depleted-mid-oceanic-ridge-basalt-mantle (DMM 60 ) as bulk composition.…”
Section: Temperature Distributionmentioning
confidence: 99%
“…Shear-wave velocities (Vs) at 200 km depth (Debayle et al 2020) are converted to temperature using Gibbs free-energy minimisation algorithm, for details see (Kumar et al 2022). We pre-compute anharmonic Vs from stable phase and mineral assemblages at upper-mantle pressure and temperature conditions, computed using a Gibbs free-energy minimisation algorithm (Connolly 2005), using depletedmid-oceanic-ridge-basalt-mantle (DMM(Workman and Hart 2005)) as bulk composition.…”
Section: Temperature Distributionmentioning
confidence: 99%

Thermodynamics of continental deformation

Kumar,
Cacace,
Scheck-Wenderoth
2023
Preprint
Self Cite