Lithospheric thickness and heat flux beneath cratons

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Lithospheric thickness and heat flux beneath
cratons
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
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Questions
How can global seismic tomography contribute to
studies of the thermal structure of the cratons?

• Where are the deep cratonic roots?
• What is the thickness of the cratonic
  lithosphere?
• What is the heat flux through cratons?

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Where are the cratons?
Geological data (Goodwin, 1996)
Geophysical data Heat flow (Pollack et al, 1993)
No information about mantle structure
Unevenly distributed over Earths surface
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Where are the cratons?
Geophysical data Inversion of heat
flow (Artemieva and Mooney, 1998)
Geological data (Goodwin, 1996)
No information about mantle structure
Unevenly distributed over Earths surface
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Seismic surface-waves

• Provide homogeneous coverage in the uppermost
  mantle
• Provide sensitivity to the thermal structure of
  the uppermost mantle

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
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Dispersion maps
100 s Rayleigh wave group velocity
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Local dispersion curves
All dispersion maps Rayleigh and Love wave group
and phase velocities at all periods
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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
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Where are the cratons?
Geological data (Goodwin, 1996)
Geophysical data 3D seismic model (Shapiro and
Ritzwoller, 2002)
150 km
No information about mantle structure
Homogeneous coverage In the uppermost mantle
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Where are the cratons?
Geological data (Goodwin, 1996)
Geophysical data 3D seismic model (Shapiro and
Ritzwoller, 2002)
No information about mantle structure
Homogeneous coverage In the uppermost mantle
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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

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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
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Reformulation of seismic inversion
Heat-flow constrains on temperatures and seismic
speeds at the Moho
Thermal parameterization
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Lithospheric thickness and mantle heat flow in
Canada
From Shapiro et al. (2004)
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.
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Other cratons mantle component of heat flow
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Other cratons lithospheric thickness
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Other cratons lithospheric thickness vs mantle
heat flow
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Conclusions

• Seismic inversions can be reformulated in terms
  of an underlying thermal model.
• Lithospheric thickness beneath cratonic cores
  exceeds 250km.
• Mantle component of the heat flow beneath cratons
  is low ( lt 15 mW/m2).
• 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)
  who postulated that the steady heat flux at the
  base of the lithosphere is supplied by
  small-scale convection.

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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
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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

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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

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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
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Monte-Carlo inversion of the seismic data based
on the thermal description of model
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Monte-Carlo inversion of the seismic data based
on the thermal description of model

• a-priori range of physically plausible thermal
  models

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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)

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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

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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

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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

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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

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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

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Inversion with the seismic parameterization
seismically acceptable models
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Inversion with the seismic parameterization
seismically acceptable models
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Inversion with the seismic parameterization
seismically acceptable models
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3D temperature model of the uppermost mantle
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3D temperature model of the uppermost mantle
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3D seismic model