Lowermost mantle shear-velocity structure from hierarchical trans-dimensional Bayesian tomography

This is a Preprint and has not been peer reviewed. The published version of this Preprint is available: https://doi.org/10.1029/2020JB021557. This is version 1 of this Preprint.

Add a Comment

You must log in to post a comment.


Comments

There are no comments or no comments have been made public for this article.

Downloads

Download Preprint

Supplementary Files
Authors

Sima Mousavi, Hrvoje Tkalčić, Rhys Hawkins, Malcolm Sambridge

Abstract

The core-mantle boundary (CMB) is the most extreme boundary within the Earth where the liquid, iron-rich outer core interacts with the rocky, silicate mantle. The nature of the lowermost mantle atop the CMB, and its role in mantle dynamics, is not completely understood. Various regional studies have documented significant heterogeneities at different spatial scales. While there is a consensus on the long scale-length structure of the inferred S-wave speed tomograms, there are also notable differences stemming from different imaging methods and datasets. Here we aim to overcome over-smoothing and avoid over-fitting data for the case where the spatial coverage is sparse and the inverse problem ill-posed. Here we present an S-wave tomography model at global scale for the Lowermost Mantle (LM) using the Hierarchical Trans-dimensional Bayesian Inversion (HTDBI) framework, LM-HTDBI. Our HTDBI analysis of ScS-S travel times includes uncertainty, and the complexity of the model is deduced from the data itself through an implicit parameterization of the model space. Our comprehensive resolution estimates indicate that short-scale anomalies are significant and resolvable features of the lowermost mantle regardless of the chosen mantle-model reference to correct the travel times above the D’’ layer. The recovered morphology of the Large-Low-Shear-wave Velocity Provinces (LLSVPs) is complex, featuring small high-velocity patches among low-velocity domains. Instead of two large, unified, and smooth LLSVPs, the newly obtained images suggest that their margins are not uniformly flat.

DOI

https://doi.org/10.31223/X5MG8V

Subjects

Earth Sciences, Physical Sciences and Mathematics

Keywords

Bayesian inference, core mantle boundary

Dates

Published: 2021-09-05 06:49

Last Updated: 2021-09-05 13:49

License

CC BY Attribution 4.0 International