Resolving lithospheric and athenospheric anisotropy beneath broadband station RSSD in NW South Dakota

Teleseismic shear waves from data-rich broadband station RSSD in the Black Hills of South Dakota are analyzed for the effects of shear wave splitting. Silver and Chan reported a small delay time of 0.6 seconds, which they attribute to an incoherent structural fabric due to multiple deformational episodes since the Achaean. This interpretation requires that shear due to plate motion is either not present or is accommodated at a depth below where the mantle deforms in the dislocation creep regime. A third possibility is that anisotropic fabric due to plate motion is present but cannot be resolved by the Silver and Chan method which assumes one flat layer of anisotropy. To test this third hypothesis, we present a new technique that shows promise in extracting multiple-layered anisotropy structure, such as that due to lithospheric and asthenospheric strain. We model anisotropy at RSSD by testing and statistically ranking possible models of multiple layer structure by comparing observed SKS to predicted SKS using the cross-convolution method of Menke and Levin, and a directed Monte-Carlo search method (the Neighborhood Algorithm) is used to guide the search through parameter space and produce maximum likelihood models. We then use the F test to rank the significance of the relative error reductions between the different model parameterizations. This combination of methods provides for statistical examinations of the fit of various complex models, and proves more effective than fitting back-azimuthal variations of splitting times. Furthermore, we test the power of this method to resolve various multi layer geometries at RSSD by generating and testing synthetic waveforms. Our one-layer model result agrees with that of Silver and Chan in that it indicates very little anisotropy. However, our results for more complex models indicate that larger degrees of anisotropy are in fact present. We present these results in terms of their statistical likelihood, and examine their implications for our ability to resolve lithospheric anisotropy.