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Variable Viscosity Convection in a Compressible Upper Mantle and the Thickness of Continental Lithosphere

  • H. Schmeling
Chapter
Part of the NATO ASI Series book series (ASIC, volume 334)

Abstract

Our knowledge about the viscosity of the earth’s mantle is still limited. Therefore most models assume either a constant or a radially stratified viscosity in the mantle. Laboratory constraints on the temperature-, pressure-, and stress dependent rheology of olivine are used in numerical models of mantle convection to explore the possible variations of the mantle viscosity. In the first part the interaction of compression and variable viscosity in mantle convection is investigated. It is found that the most important effect of compression is the establishment of an adiabatic gradient, which reduces lateral viscosity variations and enhances the downwelling part of the flow. Slab-like sinking structures may develop, while upwelling plumes are retarded. It is shown that compressible upper mantle convection may be roughly approximated by incompressible convection with a reduced activation volume. In the second part sublithospheric, variable viscosity convection is used to study possible effects on the variations of the thickness of the lithosphere. Three different thickness definitions are discussed. It is found that compressibility influences lithospheric thickness variations significantly. Strong thickness variations in which downwelling is associated with thick lithospheric roots are found for mantle heat flows of < 30 mW/m2 and activation volumes larger than perhaps 20 • 10-6 m3. Time-dependent models show that deep roots associated with downwelling may persist for long timescales. The models suggest that the effective viscosity below the lithosphere should vary laterally by 1.5 to 4 orders of magnitude depending on the activation enthalpy.

Keywords

Mantle Convection Adiabatic Heating Viscous Heating Lithospheric Thickness Postglacial Rebound 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Science+Business Media Dordrecht 1991

Authors and Affiliations

  • H. Schmeling
    • 1
  1. 1.University Bayreuth, Bayerisches GeoinstitutBayreuth F.R.Germany

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