[S14-P] Poster

[S14-P-05] Detecting Seismic Anisotropy in the Mantle Transition Zone with SS Precursors

^○Quancheng Huang¹, Nicholas Schmerr¹, Lauren Waszek², Caroline Beghein³, Erik Weidner³ (1.University of Maryland, College Park, USA, 2.New Mexico State University, Las Cruces, USA, 3.University of California, Los Angeles, USA)

Mineral physics experiments predict that the minerals in the transition zone (wadsleyite and ringwoodite) can have up to 8–13 % anisotropy. Seismic anisotropy is produced when anisotropic minerals are aligned by mantle flow; e.g., upwelling plume or subducting slab. However, the observation of seismic anisotropy in the mantle transition zone (MTZ) is a challenging measurement due to the limited resolution of current methods. We use a body wave approach, the SS precursors, to study the anisotropy of MTZ and associated mantle dynamics. Here, we use a broadband SS data set of 45,624 records to detect azimuthal anisotropy present near the 410 and 660 km discontinuities. Due to the low amplitude of SS precursors, we employ a slowness stacking method to improve the signal to noise ratio. We partition our data into geographic bins of SS precursor bounce points that sample with enough azimuthal coverage to be further broken down into azimuthal bins. Our goal is the detection of travel time and amplitude variance of SS precursors with azimuth. We generate synthetic seismograms by perturbing PREM model in the transition zone to predict travel time and amplitude change of SS precursors with different strength of anisotropy. We identify bin locations of South America and South Pacific Ocean that have sufficient azimuthal coverage to produce stable stacks. These bins have travel time and amplitude variations of the SS precursors that show little to no dependence on azimuth. We combine all the bins above subduction zones to detect azimuthal anisotropy caused by subduction flows. The subduction zone bins have significant travel time and amplitude variations with azimuth but their uncertainties are relatively large. The azimuthal anisotropy is quantified by fitting modeling curves to data variations, which indicates that the MTZ beneath subduction zones can have 1- 4% anisotropy. We will do further correction for the topography of MTZ to reduce the uncertainty.