3D P‐Wave Attenuation Tomography of the Tonga‐Lau Subduction System With Improved Earthquake Source Parameters and a Transdimensional Bayesian Markov Chain Monte Carlo Approach
Abstract
Abstract Seismic attenuation, resulting from anelasticity of Earth's materials, provides critical information on the thermal and compositional characteristics of Earth's interior. Accurately measuring the seismic wave energy loss during propagation and conducting seismic attenuation is challenging, as conventional methods for measuring attenuation suffer from the trade‐offs between estimated source signature and along‐path energy decay, and between damping and smoothing in linear tomography inversions. In this study, we first incorporate independently constrained source parameters to invert for path‐average attenuation, , thereby minimizing the trade‐offs between path and source terms. Then, based on the refined data set, we apply a transdimensional Bayesian Markov Chain Monte Carlo (MCMC) approach to image the 3D attenuation structure with robust uncertainty estimations. We apply these methods to a 1‐year amphibious seismic array in the Tonga subduction zone and its adjacent Lau back‐arc basin. The new measurements fit the data well, and the new 3D tomography results reveal high P‐wave attenuation anomalies in the Tonga‐Lau mantle wedge with the highest attenuation of or beneath the East Lau Spreading Center at 50 km depth. Additionally, a slightly elevated attenuation anomaly is imaged in the mantle transition zone. By combining our new model with a published SV‐wave velocity model, we quantitatively estimate melt porosity at 50 km beneath the back‐arc spreading centers, showing a southward decrease from beneath the Central Lau Spreading Center to around 0 beneath the Valu Fa Ridge.
Fields of Study & Subjects
High-pressure geophysics and materials
earthquake and tectonic studies
Geological and Geochemical Analysis
Publication details
- Journal / source
- Journal of Geophysical Research Solid Earth
- Publisher
- American Geophysical Union (AGU)
- Volume
- 131
- Issue
- 4
- Publication date
- 1 April 2026
- Language
- EN