HR: 0800h
AN: S51A-0975    [Abstracts]
TI: Testing a suite of multi-layer dipping anisotropy models with teleseismic shear wave array data
AU: * Yuan, H
EM: yuan@uwyo.edu
AU: Dueker, K
EM: dueker@uwyo.edu
AB: While shear-wave splitting provides wonderful new constraints with respect to mantle deformation, nonetheless most datasets are limited in their ability to constrain anisotropic models more complex than a single layer with a flat (horizontal) fast velocity axis (FVA). Often this limitation results from single station data which is often contaminated by signal generated noise. In our analysis, data from a 30-station 90-km diameter broad-band array deployed in SW Montana provides 9 SKS and 7 direct-S events that are stacked to attenuate signal generated noise and provide good error estimation crucial to statistical model ranking. To quantify the resolving power of this dataset, the posterior model probability density (PPD) volumes for a suite of seven models are compared. The forward problem is calculated using ray-theory and the model is parameterized as a set of flat velocity layers with possible dipping FVA. Source normalization is performed using the cross-convolution method which approximates the source waveform as linearly polarized before entering the anisotropic receiver-side structure. To search the N-dimensional model space for low misfit models, the Neighborhood Algorithm is used. The seven models tested are the combination of one, two, or three layers with each layer either possessing a flat FVA or a dipping FVA. Comparison of the different model PPD volumes (using 1- and 2-D probability density marginals) and F-test statistics shows that models more complex than a single layer of flat FVA anisotropy are required by the data. Our best model is two layers of dipping anisotropy whose fit to the data are better than a single flat layer model at >80% confidence. The PPD for this model is compact and uni-modal and can be reasonably approximated as a multivariate Gaussian. However, a three layer dipping anisotropy model produces non-compact multi-modal marginals with large covariance between model parameters. We conclude that: 1) use of direct S- arrivals provides a significant increase in model resolution; 2) models with a lower layer FVA that dips 20-40­a down to the SW is a robust requirement of the data; 3) array data provide improved resolution with respect to single station data. The dipping FVA found may be attributed to the Yellowstone plume (see additional URL) that rises 100 km to the SE of our array.
UR: http://faculty.gg.uwyo.edu/dueker/assorted_yellowstonE_hotspot.htm
DE: 7200 SEISMOLOGY
DE: 7203 Body waves
DE: 7218 Lithosphere (1236)
SC: Seismology [S]
MN: Fall Meeting 2005