Expressions for the Global Gravimetric Moho Modeling in Spectral Domain

Abstract

We apply a newly developed numerical method to improve the Moho geometry by the implementation of gravity data. This method utilizes expressions for the gravimetric forward and inverse modeling derived in a frequency domain. Methods for a spectral analysis and synthesis of the gravity field and crust density structures are applied in the gravimetric forward modeling of the consolidated crust-stripped gravity disturbances, which have a maximum correlation with the (a priori) Moho model. These gravity disturbances are obtained from the Earth’s gravity disturbances after applying the topographic and stripping gravity corrections of major known anomalous crust density structures; in the absence of a global mantle model, mantle density heterogeneities are disregarded. The isostatic scheme applied is based on a complete compensation of the crust relative to the upper mantle density. The functional relation is established between the (unknown) Moho depths and the complete crust-stripped isostatic gravity disturbances, which according to the adopted isostatic scheme have (theoretically) a minimum correlation with the Moho geometry. The system of observation equations, which describes the relation between spherical functions of the isostatic gravity field and the Moho geometry, is defined by means of a linearized Fredholm integral equation of the first kind. The Moho depths are determined based on solving the gravimetric inverse problem. The regularization is applied to stabilize the ill-posed solution. This numerical procedure is utilized to determine the Moho depths globally. The gravimetric result is presented and compared with the seismic Moho model. Our gravimetric result has a relatively good agreement with the CRUST2.0 Moho model by means of the RMS of differences (of 3.5 km). However, the gravimetric solution has a systematic bias. We explain this bias between the gravimetric and seismic Moho models by the unmodelled mantle heterogeneities and uncertainties in the CRUST2.0 global crustal model.