LAUSR

We develop an algorithm for a Moho depth recovery from gravity and gravity gradiometry data and apply this method to estimate the Moho depth beneath the Tibetan Plateau. The basic idea of this algorithm is to describe mathematically the Moho depth undulations in terms of a condensation layer with respect to a mean Moho depth, instead of applying more commonly used isostatic compensation schemes. Expressions that functionally relate gravity field quantities with a (Moho) condensation layer are derived in spectral and spatial domains. The main advantage of this algorithm is that a functional relation between gravity field quantities and surface density anomalies, and consequently Moho depth undulations, has a linear form. The proposed algorithm is tested using satellite gravity and gravity gradiometry data. The Moho depth (taken with respect to the geoid surface) estimates obtained based on applying this algorithm are validated against global and regional seismic Moho results at the study area of Tibet. We also compare the result with the corresponding Moho depth estimates obtained by applying the Parker–Oldenburg and Vening Meinesz–Moritz (VMM) methods. The validation shows that results from all three gravimetric methods are similar, and they also closely agree with a regional seismic Moho model. Nevertheless, the VMM method and our algorithm in this comparison overperform the Parker–Oldenburg's method. The analysis of results also reveals that the newly developed algorithm provides better result (in terms of the RMS fit with a regional seismic Moho model) when applied for a Moho determination from gravity gradiometry instead of gravity data.