2004
DOI: 10.1016/j.epsl.2004.06.005
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A new inference of mantle viscosity based upon joint inversion of convection and glacial isostatic adjustment data

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Cited by 589 publications
(643 citation statements)
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References 44 publications
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“…The viscosity for diffusion creep (equation (1)) does not depend on the temperature difference across the boundary layer and therefore does not depend on whether the temperature difference driving small-scale convection is at its rheological threshold. Solutions for dry diffusion creep yield viscosities between 1.0 10 20 and 1.2 10 20 Pa s, close to the range of postglacial rebound estimates, 2.0 10 20 −5.3 10 20 Pa s [Cianetti et al, 2002;Mitrovica and Forte, 2004;Paulson et al, 2007]. Just below the lithosphere, viscosity should be slightly lower than such average values (see, e.g., the radial viscosity profile shown by Mitrovica and Forte [2004]), which is in agreement with our results.…”
Section: Overviewsupporting
confidence: 81%
“…The viscosity for diffusion creep (equation (1)) does not depend on the temperature difference across the boundary layer and therefore does not depend on whether the temperature difference driving small-scale convection is at its rheological threshold. Solutions for dry diffusion creep yield viscosities between 1.0 10 20 and 1.2 10 20 Pa s, close to the range of postglacial rebound estimates, 2.0 10 20 −5.3 10 20 Pa s [Cianetti et al, 2002;Mitrovica and Forte, 2004;Paulson et al, 2007]. Just below the lithosphere, viscosity should be slightly lower than such average values (see, e.g., the radial viscosity profile shown by Mitrovica and Forte [2004]), which is in agreement with our results.…”
Section: Overviewsupporting
confidence: 81%
“…In a similar manner, the top frame indicates that good fits are obtained only for UMV values greater than 10 21 Pas for the chosen values of LMV and LT. These viscosity values are higher than those commonly estimated using near-field [e.g., Mitrovica and Forte, 2004] and far-field data [e.g., Lambeck et al, 2014]; however, they are compatible with a recent estimate based on RSL data from the circum-Caribbean region [Milne and Peros, 2013].…”
Section: Estimating Optimal Model Parameterscontrasting
confidence: 44%
“…The resulting ice history and viscosity structure are coupled, meaning that unrealistic GIA predictions might result from using those deglaciation models in combination with arbitrary viscosity profiles. However, large errors and trade-offs in the sea level records, unevenly distributed and difficult to date, cause large uncertainties in the resulting models and leave abundant room for independent improvements in both the ice history and the viscosity structure (e.g., Mitrovica and Forte 2004).…”
Section: Modelling Gia and Present-day Model Uncertaintymentioning
confidence: 99%