Mapping the Moho with seismic surface waves: A review, resolution analysis, and recommended inversion strategies

The strong sensitivity of seismic surface waves to the Moho is evident from a mere visual inspection of their dispersion curves or waveforms. Rayleigh and Love waves have been used to study the Earth's crust since the early days of modern seismology. Yet, strong trade-offs between the Moho depth and crustal and mantle structure in surface-wave inversions prompted doubts regarding their capacity to resolve the Moho. Here, we review surface-wave studies of the Moho, with a focus on early work, and then use model-space mapping to establish the waves' sensitivity to the Moho depth and the resolution of their inversion for it. If seismic wavespeeds within the crust and upper mantle are known, then Moho-depth variations of a few kilometres produce large (>1%) perturbations in phase velocities. However, in inversions of surface-wave data with no a priori information (wavespeeds not known), strong Moho-depth/shear-speed trade-offs will mask similar to 90% of the Moho-depth signal, with remaining phase-velocity perturbations similar to 0.1% only. In order to resolve the Moho with surface waves alone, errors in the data must thus be small (up to similar to 0.2% for resolving continental Moho). With larger errors, Mohodepth resolution is not warranted and depends on error distribution with period. An effective strategy for the inversion of surface-wave data alone for the Moho depth is to, first, constrain the crustal and upper-mantle structure by inversion in a broad period range and then determine the Moho depth in inversion in a narrow period range most sensitive to it, with the first-step results used as reference. Prior information on crustal and mantle structure reduces the trade-offs and thus enables resolving the Moho depth with noisier data; such information should be used whenever available. Joint analysis or inversion of surface-wave and other data (receiver functions, topography, gravity) can reduce uncertainties further and facilitate Moho mapping. (C) 2013 Elsevier B.V. All rights reserved.