Author ORCID Identifier

https://orcid.org/0009-0001-2246-5955

Date Available

12-15-2023

Year of Publication

2023

Degree Name

Master of Science (MS)

Document Type

Master's Thesis

College

Arts and Sciences

Department/School/Program

Earth and Environmental Sciences (Geology)

First Advisor

Dr. Keely A. O’Farrell

Abstract

Global mantle discontinuities and mantle transition zones are crucial to the earth’s evolution. By employing K-Means clustering, which belongs to cluster analysis in machine learning (ML), on shear velocity variation data, we generate heterogeneity percentage profiles for three different global tomographic models (Models S362WMANI+M, SEMUCB-WM1, and S40RTS). Key cluster percentage shifts, which are observed at around 400 km, 650 km, 1050 km, 1500 km, and 2700 km, suggest global mantle discontinuities at corresponding depths. All profiles also indicate a global discontinuity in the lower mantle between 2200 km and 2600 km. The middle mantle transition zone (MMTZ), bounded between 1050 km and 1500 km discontinuities, is detected for the first time. Mantle convection modeling with the global geoid is conducted using the HC code to demonstrate the viscosity jump in this new MMTZ.

Digital Object Identifier (DOI)

https://doi.org/10.13023/etd.2023.464

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