Probabilistic inversion of receiver functions for layered seismic anisotropy and application to the anisotropic lithosphere of Southern New England

SUMMARY This study introduces a novel inversion approach to resolve the layered anisotropic structure of the Earth’s crust and upper mantle using harmonic patterns observed in Ps receiver functions (RFs). Designed for dense seismic networks, our method effectively captures the complexity and deformation of subsurface structures by leveraging the decomposition of RF patterns into five harmonic functions representing distinct terms in a harmonic regression model. Our approach combines residual weighting at individual and coherency weighting between stations to reduce noise and enhance structural signal, followed by a direct inversion of harmonic patterns alongside a multiphase stack. This process is optimized using a Markov chain Monte Carlo framework to iteratively explore model space and define posterior distributions, which yields robust model parameter estimates with quantified uncertainties. We validated our approach with both synthetic models and real data from the dense SEISConn seismic transect in Northern Connecticut. The synthetic test highlighted the reliability of coherency weighting in reducing noise. Real data analysis revealed anisotropic and structural features consistent with geological expectations and previous studies, including shallow anisotropy in western Connecticut, a shallowing Moho towards the Hartford basin, and indications for a west-dipping layer beneath the Moho in the lithospheric mantle. Our approach offers a promising tool for revealing the details of anisotropic features beneath dense seismic profiles, facilitating insights into tectonic history and lithospheric deformation.