Testing five of the simplest upper mantle anisotropic velocity parameterizations using teleseismic S and SKS data from the Billings, Montana PASSCAL array

Huaiyu Yuan, Ken Dueker, Derek L. Schutt

Research output: Contribution to journalArticlepeer-review

11 Citations (Scopus)

Abstract

Five of the simplest parameterizations of upper mantle anisotropy are tested and ranked for a data set collected on a dense temporary PASSCAL seismic array located 100-km NE of Yellowstone. These hexagonal symmetry anisotropy models possess either one or two layers with either flat or dipping fast velocity axis (FVA). Recordings from fifteen high quality direct-S and SKS arrivals are stacked to provide accurate waveform and error estimates. Source normalization is accomplished using the cross-convolution technique. A direct Monte Carlo Neighborhood Algorithm is used to map the posteriori model probability density (PPD) volume. Using the F test, we find that models with purely flat FVA can be rejected at >97% probability. Our best model (P5) is a two layer dipping FVA parameterization, albeit the two layer model with one flat and one dipping FVA can only be rejected at 80% probability. The best model has a lower layer with a N65°E FVA strike and a -12° dip (down to the southwest), and an upper layer with a N20°W FVA strike and a -47° FVA dip (down to the southeast). The bottom asthenospheric layer FVA strikes parallel to North America's absolute plate motion direction and dips opposite to what passive plate shear of the asthenosphere would predict. The upper lithospheric layer is consistent with LPO accretion associated with north directed drift of the North American plate during the Mesozoic. Comparison between the SKS-and direct S-wave data sets shows that the direct S waves improve resolution of the double layer anisotropic model parameters.

Original languageEnglish
Article numberB03304
JournalJournal of Geophysical Research: Solid Earth
Volume113
Issue number3
DOIs
Publication statusPublished - 4 Mar 2008
Externally publishedYes

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