New approaches to shear wave splitting tomography

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The speed at which seismic waves travel in the Earth's upper mantle depends on the direction of wave propagation, a phenomenon known as seismic anisotropy. Seismic anisotropy arises when a mantle rock is sheared or stretched by the process of mantle convection; therefore, observations of anisotropy provide seismologists with a method of inferring mantle convection patterns. While measurements of seismic anisotropy from recordings of earthquake waves that have passed through the mantle are relatively straightforward, it is a major challenge to decipher the exact location or depth of the anisotropic structure. One strategy for overcoming this challenge is to move towards an approach that provides an image or picture of anisotropy in the upper mantle, using a technique known as tomography. Much in the same way that medical tomography can provide an image of the inside of a person's body, seismic tomography yields an image of the structure of the Earth's deep interior. The PI will provide support and mentoring for a PhD student. Codes being developed during the research will be openly available via GitHub. The PI and graduate student will also provide outreach in the form of presentations to the general public.The application of shear wave splitting tomography has been a long-standing goal in the study of upper mantle anisotropy, but there are only a few examples of published studies that have successfully implemented it. The challenges are many: the inverse problem is highly nonlinear and sensitivity kernels for the inversion depend strongly on the starting model; a large number of parameters are needed for a complete description of the anisotropy; robust shear wave splitting measurements are often difficult to make for noisy data. This project will meet those challenges by developing and applying a framework for finite-frequency SKS splitting intensity tomography that implements a model space search approach for probing parameter space. The investigators propose three specific activities. Activity #1 comprises the completion and implementation of a theoretical and computational framework for our splitting intensity tomography approach. The team is extending existing theory for finite-frequency sensitivity kernels to a new parameterization scheme that takes advantage of constraints on olivine elasticity from mineral physics. They will complete the implementation of a model space search algorithm, based on a Markov chain Monte Carlo approach, for inverting splitting intensity observations. Finally, the investigators will test their implementation with a series of synthetic anisotropic models and splitting intensity datasets, designed to understand the limitations, resolution, and parameter tradeoffs of their imaging approach. Activity #2 will involve the implementation of the shear wave splitting intensity tomography framework for several real-world data sets from dense broadband seismic networks. Activity #3 will extend their model space search approach to simultaneously include other types of observations that constrain upper mantle anisotropy, including anisotropic receiver functions and surface wave phase velocity measurements.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.