HR: 10:50h
AN: S32A-03    [Abstracts]
TI: Investigating the Anisotropic Shear Wave Velocity Structure of the Earth's Mantle
AU: * Ferreira, A M
EM: anaf@earth.ox.ac.uk
AF: School of Environmental Sciences, University of East Anglia, Norwich NR4 7TJ, Norwich, NR4 7TJ, United Kingdom
AU: Woodhouse, J H
EM: john.woodhouse@earth.ox.ac.uk
AF: Department of Earth Sciences, University of Oxford, Parks Road, Oxford OX1 3PR, Oxford, OX1 3PR, United Kingdom
AU: Visser, K
EM: kvis@geo.uu.nl
AF: Faculty of Geosciences, Department of Earth Sciences,Utrecht University, 4 Budapestlaan, 3584 CD Utrecht, Utrecht, 3584 CD, Netherlands
AU: Trampert, J
EM: jeannot@geo.uu.nl
AF: Faculty of Geosciences, Department of Earth Sciences,Utrecht University, 4 Budapestlaan, 3584 CD Utrecht, Utrecht, 3584 CD, Netherlands
AB: The principal tool by which we learn about the upper part of the mantle (the top 1000 km say) is through the study of surface waves and, importantly, surface wave overtones. In this study we combine a variety of existing databases of surface wave phase velocity measurements into a very large data set consisting of more than 9,500,000 dispersion measurements of fundamental and higher mode (up to the 4^th overtone) Rayleigh and Love waves with wave periods between T=35s and T=200s (Visser et al., GRL, 2007; van Heijst and Woodhouse, GJI, 1999; Ekström et al., JGR, 1997). We carry out inversions of this large data set for perturbations in the isotropic S-velocity structure and the anisotropic parameter ζ _s=\frac{v²_SH-v²_SV}{2v²_S} in the top 1000 km of the Earth's mantle. The models are parameterised using spherical harmonic basis functions up to degree 20 for the lateral variations and using 21 spline functions for the depth dependence. We carry out a large number of inversions using a variety of damping schemes and we choose the optimal model using the Akaike Bayesian Information Criterion (ABIC) together with a priori information. In a first step, we invert separately the Rayleigh and Love wave data sets for perturbations in the isotropic SV-velocity and SH-velocity structures, respectively. Our 3D isotropic models share the large scale features of previous global tomographic studies. Furthermore, these isotropic models fit well the various existing subsets of dispersion measurements we use, showing that they are quite compatible with each other. We then invert the complete data set of surface wave dispersion measurements for perturbations in purely isotropic S- velocity structure. The estimated model shows well known large scale anomalies and provides a reasonable fit to the data. In a second step, we address the distribution of radial anisotropy, using fully anisotropic sensitivity kernels. Overall, allowing for radial anisotropy improves the data fit by about 2% compared to a purely isotropic inversion. Nevertheless, for certain surface wave modes, the data fit is improved by more than 10% when allowing for radial anisotropy. We investigate what is the smallest significant amount of anisotropy required by the different subsets of data. Finally, we compare our prefered 3D anisotropic model with previous tomographic studies and discuss possible relationships between flow and anisotropy.
DE: 7208 Mantle (1212, 1213, 8124)
DE: 7255 Surface waves and free oscillations
DE: 7270 Tomography (6982, 8180)
SC: Seismology [S]
MN: 2007 Fall Meeting