Global Moho from the combination of the CRUST2.0 model and GOCE data

The discontinuity surface between Earth crust and mantle, the so-called Moho, is commonly estimated by means of seismic or gravimetric methods. Usually these methods do not yield the same result since they are based on different geological and geophysical hypotheses, as well as different data types, also in terms of quality and spatial distribution. In particular, global crust models based only on seismic data (e.g. the CRUST2.0 model) can be locally very accurate since seismic profiles give an almost direct observation of the actual crust structure, but can be quite uninformative in large regions where no data are available or they are too inhomogeneous. On the contrary, when using satellite gravity observations like those provided by the ESA mission GOCE, information on the Moho can be inferred from a uniform and global data set. However, Moho models estimated by gravity data are in general characterized by simplified hypotheses to guarantee the uniqueness of the solution of the inverse gravitational problem. The aim of this work is to attenuate these drawbacks by combining the seismic global model CRUST2.0 with gravity observations from the GOCE satellite mission. More specifically, the used GOCE data are grid values at mean satellite altitude estimated by the so-called space-wise approach. After reducing the data to a two-layer model by removing the effect of topography, bathymetry and sediments, a combined inversion driven by a priori information on the CRUST2.0 accuracy and by the error covariance structure of the GOCE grids is performed. In addition, the observation errors as well as the error due to the data reduction are tentatively taken into account to estimate the accuracy of the final Moho model. The result is an update of the CRUST2.0 Moho model with a 0.5° × 0.5° resolution, which at the same time contains seismic and geological information and it is consistent, at 20 mE level, to the actually observed gravity field. A first comparison with the CRUST2.0 Moho shows that in the continental crust the mean difference between the two models is of the order of 1.5 km with standard deviations depending on the considered region. As expected, the main variations (standard deviation of the order of 7 km) are located in South America, Africa and Antarctica where very few data in the CRUST2.0 were originally used. In the rest of the world, differences have a standard deviation of about 4 km. As for the oceanic crust, it can be noted that the corrections to the CRUST2.0 model are of the order of 3 km (mean value) with a standard deviation of 6 km. Finally, the solution computed in this paper has been compared with a set of Moho models at different scales from global to local ones showing that it is reasonably consistent (differences of about 5 km standard deviation) also with seismic observations.