T54A-03
Lithospheric structure of the Sea of Japan from surface wave tomography

Friday, 18 December 2015: 16:30
304 (Moscone South)
Bill Fry, GNS Science-Institute of Geological and Nuclear Sciences Ltd, Lower Hutt, New Zealand, Hiroshi Sato, University of Tokyo, Bunkyo-ku, Japan, Tetsuya Takeda, National Research Institute for Earth Science and Disaster Prevention, Tsukuba, Japan, Qi-Fu Chen, Key Laboratory of Earth and Planetary Physics, Institute of Geology and Geophysics, Chinese Academy of Sciences, Beijing, China, David A Okaya, University of Southern California, Los Angeles, CA, United States and Kelin Wang, Geological Survey of Canada Sidney, Sidney, BC, Canada
Abstract:
We investigate the surface wave and shear wave velocity structure of the Sea of Japan based on group and phase velocity measurements made on broad-band, cross-correlated ambient noise. Continuous data from terrestrial broadband stations surrounding the sea are filtered, cross correlated on a day-by-day basis, and then stacked. The correlation functions are processed with multiple filters and group velocities are manually selected from 7s to 50s. Subsequent to multiple filtering, we apply phase-matched filtering and unwrap the phase of the resulting signal. This phase is then used to determine phase velocities by selecting an appropriate number of wave-cycles appropriate for the average velocity structure. The interstation dispersion curves are then inverted for 2D isotropic and anisotropic surface wave maps at discrete periods. In a second stage of inversion, the 2D isotropic inversion results are combined at each spatial node to create a "1D" dispersion curve. We use a linearized, iterative process to model the 1D dispersion at each node for depth-dependent shear-wave velocities. The 1D models are then combined to form at 3D model of shear wave velocity. We image slow shear-wave anomalies under the central basin and relatively fast velocities under the Yamamoto and Japan Basins and offshore of the western Japan shelf. Current estimates of azimuthal anistoropy from our inversions are poorly constrained due to sparse data distribution. Ongoing efforts are aimed at refining anisotropy estimates by increasing data density from noise correlations by increasing the spatial coverage of our database. Our isotropic and anisotropic models will be presented, as will a first attempt at defining lithospheric thickness based on radial anisotropy determined from our inversions.