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Thermal structure of old continental lithosphere from the inversion of surface-wave dispersion with thermodynamic a-priori constraints. N. Shapiro, M. Ritzwoller, University of Colorado at Boulder. J.-C. Mareschal, Université du Québec à Montréal.
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Thermal structure of old continental lithosphere from the inversion of surface-wave dispersion with thermodynamic a-priori constraints N. Shapiro, M. Ritzwoller, University of Colorado at Boulder J.-C. Mareschal, Université du Québec à Montréal C. Jaupart, Institut de Physique du Globe de Paris
Objectives to reconcile thermal and seismic models of the old continental lithosphere 2. to develop methods for joint inversion of the seismic and the thermal data
Thermal models of the old continental lithosphere from Jaupart and Mareschal (1999) from Poupinet et al. (2003) Constrained by thermal data: heat flow, xenoliths Derived from simple thermal equations Lithosphere is defined as an outer conductive layer Estimates of thermal lithospheric thickness are highly variable
Seismic models of the old continental lithosphere Based on ad-hoc choice of reference 1D models and parameterization Complex vertical profiles that do not agree with simple thermal models Seismic lithospheric thickness is not uniquely defined Additional physical constraints are required to eliminate non-physical vertical oscillations in seismic profiles and to improve estimates of seismic velocities at each particular depth
Inversion of seismic surface-waves 1. Data 2. Two-step inversion procedure global set of broadband fundamental-mode Rayleigh and Love wave dispersion measurements (more than 200,000 paths worldwide) Surface-wave tomography: construction of 2D dispersion maps Inversion of dispersion curves for the shear-velocity model Group velocities 18-200 s. Measured at Boulder. Phase velocities 40-150 s. Provided by Harvard and Utrecht groups
Dispersion maps 100 s Rayleigh wave group velocity
Local dispersion curves All dispersion maps: Rayleigh and Love wave group and phase velocities at all periods
Inversion of dispersion curves All dispersion maps: Rayleigh and Love wave group and phase velocities at all periods Monte-Carlo sampling of model space to find an ensemble of acceptable models
Details of the inversion: seismic parameterization Ad-hoc combination of layers and B-splines Seismic model is slightly over-parameterized Non-physical vertical oscillations Physically motivated parameterization is required
Monte-Carlo inversion: random sampling of the model space Details of the inversion: Monte-Carlo approach Linearized iterative inversion Finds only one best-fit model. Does not provide reliable uncertainty estimates Linearization can be numerically sophisticated
Details of the inversion: Monte-Carlo approach Monte-Carlo inversion: random sampling of the model space Linearized iterative inversion Finds only one best-fit model. Do not provide reliable uncertainty estimations Linearization can be numerically sophisticated Finds an ensemble of acceptable models that can be used to estimate uncertainties Does not require linearization. Easy transformation between seismic and temperature spaces
conversion between seismic velocity and temperature computed with the method of Geos et al. (2000) using laboratory-measured thermo-elastic properties of main mantle minerals and cratonic mantle composition non-linear relation
Monte-Carlo inversion of the seismic data based on the thermal description of model
Monte-Carlo inversion of the seismic data based on the thermal description of model a-priori range of physically plausible thermal models
Monte-Carlo inversion of the seismic data based on the thermal description of model a-priori range of physically plausible thermal models constraints from thermal data (heat flow)
Monte-Carlo inversion of the seismic data based on the thermal description of model a-priori range of physically plausible thermal models constraints from thermal data (heat flow) randomly generated thermal models
Monte-Carlo inversion of the seismic data based on the thermal description of model a-priori range of physically plausible thermal models constraints from thermal data (heat flow) randomly generated thermal models converting thermal models into seismic models
Monte-Carlo inversion of the seismic data based on the thermal description of model a-priori range of physically plausible thermal models constraints from thermal data (heat flow) randomly generated thermal models converting thermal models into seismic models finding the ensemble of acceptable seismic models
Monte-Carlo inversion of the seismic data based on the thermal description of model a-priori range of physically plausible thermal models constraints from thermal data (heat flow) randomly generated thermal models converting thermal models into seismic models finding the ensemble of acceptable seismic models converting into ensemble of acceptable thermal models
Lithospheric structure of the Canadian shield Thermal data: heat flow • Computation of end-member crustal geotherms • Extrapolation of temperature bounds over a large area • Conversion into seismic velocity bounds
Inversion with the seismic parameterization seismically acceptable models
Inversion with the seismic parameterization seismically acceptable models
Inversion with the seismic parameterization seismically acceptable models
Thermal parameterization of the old continental uppermost mantle
Lithospheric thickness and mantle heat flow Power-law relation between lithospheric thickness and mantle heat flow is consistent with the model of Jaupart et al. (1998) who postulated that the steady heat flux at the base of the lithosphere is supplied by small-scale convection.
Conclusions Seismic surface-waves and surface heat flow data can be reconciled over broad continental areas, i.e., both types of observations can be fit with a simple steady-state thermal model of the upper mantle. Seismic inversions can be reformulated in terms of an underlying thermal model. The estimated lithospheric structure is not well correlated with surface tectonic history. The inferred relation between lithospheric thickness and mantle heat flow is consistent with geodynamical models of stabilization of the continental lithosphere (Jaupart et al., 1998).