Constraining Anisotropic Shear-Wave Velocity and Its Scaling to Compressional Velocity and Density throughout the Mantle Using Wide-Spectrum Seismic Data

Abstract:

We use a large dataset of normal-mode splitting functions, surface-wave phase anomalies, long-period waveforms, and body-wave travel times to investigate the resolution of anisotropic velocities, density and discontinuity topography in the Earth’s mantle. Our starting point is our new anisotropic shear-wave-velocity model S362ANI+M, which is an update to the model S362ANI (Kustowski et al., 2008). S362ANI+M was derived using additional normal-mode splitting-function observations. The isotropic part of the new model has strong variations in the transition zone and is well correlated with several recent global tomographic models. The anisotropic part of S362ANI+M is restricted to the upper ~300 km in the mantle and is similar to S362ANI. When radial anisotropy is allowed throughout the mantle, large-scale anisotropic patterns are observed in the lowermost mantle with v_SV > v_SH beneath Africa and South Pacific and v_SH > v_SV beneath several circum-Pacific regions. However, small improvements in fits to the data on adding anisotropy at depth leave the question open on whether large-scale radial anisotropy is required in the transition zone and in the lower mantle. We demonstrate that mode-splitting data reduce tradeoffs between isotropic velocity and anisotropy in the lowermost mantle for the even-degree variations. Anisotropic variations in the mid mantle are also suppressed with the addition of mode-splitting data. The seismic observables used in this study have different sensitivity to mantle heterogeneity; the long-period mantle waveforms and mode-splitting data, for example, are also sensitive to V_P and ⍴ structure. Most tomographic models adopt a priori scaling relationships between variations in shear velocity and other elastic parameters. We introduce an approach to estimate the scaling ratios from seismic data wherein we impose, with increasing weights, a priori correlations between variations in V_S and that of V_P and ⍴. The V_S-V_P and V_S-⍴ correlations and corresponding fit to data are examined to estimate depth-dependent scaling ratios. This approach allows us to investigate the resolution of scaling ratios from current datasets in different regions of the Earth’s mantle.