HR: 15:10h
AN: T13D-07    [Abstracts]
TI: A Monte Carlo Inversion for Mantle Viscosity From Post-glacial Rebound and the Influence of 3D Variations
AU: * Paulson, A M
EM: archie.paulson@colorado.edu
AF: University of Colorado, Dept of Physics, CB 390 University of Colorado, Boulder, CO 80309 United States
AU: Zhong, S
EM: szhong@anquetil.colorado.edu
AF: University of Colorado, Dept of Physics, CB 390 University of Colorado, Boulder, CO 80309 United States
AU: Wahr, J
EM: wahr@anquetil.colorado.edu
AF: University of Colorado, Dept of Physics, CB 390 University of Colorado, Boulder, CO 80309 United States
AB: Observations of glacial isostatic adjustment (GIA) of the earth's surface can provide important constraints on mantle viscosity structure. In this study, we investigate how well GIA observations are able to constrain the spherically symmetric (1D) viscosity structure of the earth. We generate synthetic PGR data by calculating the response of an earth model with realistic 3D viscosity. The viscosity model is constructed starting from seismic tomography models. Computation of the earth's response includes realistic glacial loading, gravitationally self-consistent ocean loading via the sea level equation, and the effects of polar wander. The computation is performed with the spherical finite element code CitcomSVE [Zhong et al., 2002]. We also develop a fast spectral technique to solve for GIA, including the sea level equation and polar wander effects, for earth models with 1D (spherically symmetric) viscosity structures. Following a Monte Carlo algorithm, the responses of thousands of 1D viscosity models are computed. Their resulting PGR observables are compared to synthetic measurements generated from the realistic 3D earth (solved by the finite element code). The Monte Carlo method attempts to minimize a measure of misfit which includes the following PGR observables: relative sea level (RSL) change at various locations in North America, $\dot{J_{2}}$, polar wander, and the rate of change of higher order gravity Stokes coefficients (anticipated GRACE data). We find that as we attempt to invert for more than just a few parameters in the 1D model (for example, the viscosity in a few layers), there occur many 1D models of low misfit to the 3D data, and that these models may differ widely between each other. We also find that including GRACE data in the inversion improves the radial resolution of the inversion.
DE: 8162 Rheology--mantle
SC: Tectonophysics [T]
MN: 2004 AGU Fall Meeting