A Bayesian approach to assess the importance of crustal corrections in global anisotropic surface wave tomography
Published Web Locationhttps://doi.org/10.31223/osf.io/nvrxz
Several recent studies have demonstrated the importance of crustal corrections when inverting surface wave data to model lateral variations in mantle radial anisotropy. It has also been shown that the choice of the prior crustal model to correct the data can strongly influence the anisotropy model and potentially lead to different geodynamic interpretations. In comparing tomographic models of radial anisotropy obtained from different crustal corrections, these studies did not, however, determine quantitative model uncertainties. Nevertheless, mantle models resulting from different prior crustal corrections are statistically different only if the posterior model errors stemming from the non-uniqueness of the inverse problem are smaller than the effect of the crustal correction itself. Here, we applied a model space search approach to global fundamental and higher mode Rayleigh and Love wave phase velocity maps to determine reliable, quantitative model uncertainties on seismic velocities and radial anisotropy. The technique employed enabled us to describe the model space with a posterior probability density function, and therefore to test whether models obtained from different crustal corrections are statistically different. We thus assessed the significance of the choice of the crustal model by comparing the posterior model errors to the differences in mantle structure resulting from different crustal corrections. We tested prior crustal models CRUST2.0, CRUST1.0 and 3SMAC. Our study shows that the use of prior crustal corrections from different crustal models yields significant discrepancies in mantle velocities around 50 km depth and in radialanisotropy down to 100 km. The impact of the crustal correction on radial anisotropy can extend down to 250 km in some locations. We found that choosing 3SMAC instead of the other crustal models has a stronger influence on the mantle model, but that CRUST1.0 and CRUST2.0 yield statistically identical anisotropy models at all depths, except at a few grid cells. Importantly, the effect of the crustal model is most significant in continental regions and not so much beneath oceans, which has important consequences for determining the depth of continental roots. Our results therefore suggest that improving constraints on crustal structure in continents is essential for our understanding of continent formation. Our work also demonstrates that the prior crustal model does not significantly affect radial anisotropy and velocities at depths greater than 100 km. This implies that if geodynamic interpretations of radial anisotropy below 100 km depth were to account for tomographic model uncertainties, they would not depend on the choice of the prior crustal model. It is therefore important for geodynamicists and seismologists to work in concert and to put effort into determining quantitative tomographic model uncertainties before interpreting the results. Our results also caution against the use of 3SMAC to correct surface wave data for studies of the continental lithosphere and suggest that the solid Earth community would benefit from putting some efforts towards building a revised 3SMAC. The discrepancies between mantle models built based on 3SMAC crustal corrections and those based on CRUST1.0 or CRUST2.0 should also help shed light on the validity of the geodynamical assumptions made in the construction of models like 3SMAC.