Lithospheric Structure of the Juan De Fuca and Gorda Plates From Ambient Noise

Date: 4/24/2019

Time: 06:00 PM

Room: Grand Ballroom

We estimate Rayleigh wave empirical Green’s functions (EGFs) by cross-correlating vertical component ambient noise data from the 4-year deployment of the Cascadia Initiative (CI) ocean bottom seismometers (OBSs). Tilt and compliance noise are removed from the vertical component records prior to cross-correlation. Daily cross-correlations are then stacked over the duration of each station’s deployment. We invert for a 3-D shear wave velocity model of the crust and upper mantle using Bayesian Monte Carlo inversion applied to Rayleigh wave phase and group velocity maps which are estimated from the EGFs.

We perform and compare results from two different parameterizations of 3-D shear wave velocity structure for the sediments, crust and uppermost mantle that differ in the mantle. One is a seismic parameterization in which we use five cubic B-splines for the mantle shear wave speed to a depth of 100 km. The second is a thermal plate model parameterization in which we model the shear wave velocity in the oceanic upper mantle via a temperature model and convert it to shear wave speeds based on mantle composition and Q models. The thermal parameterization is based on temperature of the top of the mantle, mantle cooling age and the potential temperature of the underlying adiabatic mantle.

Given these 3-D models, we address the following questions: (1) How well do the dispersion measurements fit with these two parameterizations of mantle structure? (2) Does the thermal model fit the data from midocean ridge to continental shelf or for only part of the region? (3) Is there an age-dependent relationship for mantle shear wave velocity on the plates? Are the age-dependent relationships the same for different profiles on the same plate? Do the Juan de Fuca and Gorda plates have the same age-dependent relationship? (4) In the resulting models, is there information about partial melt in the mantle?

Presenting Author: Hongda Wang

Authors