Effect of Prior Petrological Constraints on Global Upper Mantle Models of Radial Anisotropy

Effect of Prior Petrological Constraints on Global Upper Mantle Models of Radial Anisotropy 3-D models of S-wave radial anisotropy (ξ) in the uppermost mantle obtained with (A) and without (B) prior
petrological constraints. In this convention, a negative ξ corresponds to fast horizontally propagating shear-waves. These models correspond to the mean of the model distributions obtained.
Despite efforts from multiple research groups, large discrepancies remain among global models of seismic anisotropy. Besides the inherent non-uniqueness of inverse tomographic problems, one source of uncertainties can originate from the prior information introduced in the inversion. In the case of inversion of global surface wave phase velocity maps to obtain models of radial anisotropy, prior relationships are often imposed between the different elastic parameters. Inversions are then performed for the best-resolved parameters only, i.e. shear-wave velocity and anisotropy.
</p><p>We tested the robustness of upper- most mantle radial anisotropy models with respect to these prior constraints [Beghein, 2010]. We applied a forward modeling technique [Sambridge, 1999]to fundamental mode Rayleigh and Love wave global phase velocity maps up to spherical harmonic degree 8. This forward modeling approach enabled us to obtain reliable model uncertainties, and to determine which model features are constrained by the data and which are dominated by the prior.
</p><p>We compared the most likely and mean models obtained with and without prior constraints, and found that the most likely models obtained in both cases are highly correlated. This demonstrates that for the best data-fitting solution, the geometry of uppermost mantle radial anisotropy is not strongly affected by prior petrological constraints. We found, however, significant changes in the amplitude of the anomalies, with stronger amplitudes in the best data-fitting model obtained without petrological constraints. This could become an issue when quantitatively interpreting seismic anisotropy models, and thus emphasizes the importance of accurately accounting for parameter uncertainties and trade-offs, and of understanding whether the seismic data or the prior constraints the model.
</p><p>In addition, we showed that model distributions are not necessarily Gaussian a priori, but that imposing petrological constraints can force the models to follow a Gaussian-like posterior distribution in addition to reducing posterior model uncertainties, in agreement with inverse theory. Finally, we demonstrated that the dependence of seismic wave velocities with the age of the ocean floor is robust and independent of prior constraints. A similar age signal exists for anisotropy, but with larger uncertainties without prior constraints.
</p><p>Beghein, C., Radial Anisotropy and Prior Petrological Constraints: a Comparative Study, J. Geophys. Res., 115, 2010.
</p><p>Sambridge, M., Geophysical inversion with a Neighbourhood Algorithm - I. searching a parameter space, Geophys. J. Int., 138 (2), 479–494, 1999</p>


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