Joint body- and surface-wave transdimensional Monte Carlo imaging of upper mantle anisotropy

Summary

Seismic body and surface waves provide complimentary sensitivities to isotropic and anisotropic elastic properties of Earth’s upper mantle. However, joint inversions remain challenging because of the traditionally different inversion algorithms employed for body- and surface-wave phases. In this study, we implement a transdimensional probabilistic method based on the reversible-jump Markov chain Monte Carlo algorithm to simultaneously invert P-, S- and Rayleigh-wave data. By sampling irregularly meshed anisotropic velocity models with complexities adaptable to heterogeneous data constraints, we populate an ensemble of variable solutions describing the observations within the uncertainties. The method is validated using independent synthetic seismograms simulated in an anisotropic upper mantle plume model. We show how the different sensitivities of the data translate into different constraints on upper mantle structure, and the quantitative metrics that can be used to explore solution non-uniqueness and quantify uncertainties.