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In the last few decades, satellites have acquired various potential data sets hundreds of kilometers above the Earth's surface. Conventionally, these global magnetic and gravitational data sets are approximated by using spherical harmonics that allow straightforward work with both fields outside the Earth's mass. In this article, we present an alternative approach for working with potential data in mass-free space given over a regular coordinate grid on a spherical surface. The algorithm is based on an iterative scheme and the Poisson integral equation for the sphere. With help from the Fourier transform, global potential (magnetic or gravitational) data can efficiently be continued from a mean orbital sphere down to a reference surface without using the spherical harmonics. This is illustrated both with simulated magnetic field data and with real data from the satellite gradiometry mission GOCE. In the case of simulated magnetic data and the downward continuation for 450 km, we have achieved a root mean square at the level of 0.05 nT, while it was <1 E (eotvos) for real GOCE data continued for 250 km. The crucial point is to apply the algorithm twice as a large part of noise can be removed from the input data. [ABSTRACT FROM AUTHOR]

The global crustal model CRUST1.0 (refined using additional global datasets of the solid topography, polar ice sheets and geoid) is used in this study to estimate the average densities of major crustal structures. We further use this refined model to compile the gravity field quantities generated by the Earth's crustal structures and to investigate their spatial and spectral characteristics and their correlation with the crustal geometry in context of the gravimetric Moho determination. The analysis shows that the average crustal density is 2,830 kg/m, while it decreases to 2,490 kg/m when including the seawater. The average density of the oceanic crust (without the seawater) is 2,860 kg/m, and the average continental crustal density (including the continental shelves) is 2,790 kg/m. The correlation analysis reveals that the gravity field corrected for major known anomalous crustal density structures has a maximum (absolute) correlation with the Moho geometry. The Moho signature in these gravity data is seen mainly at the long-to-medium wavelengths. At higher frequencies, the Moho signature is weakening due to a noise in gravity data, which is mainly attributed to crustal model uncertainties. The Moho determination thus requires a combination of gravity and seismic data. In global studies, gravimetric methods can help improving seismic results, because (1) large parts of the world are not yet sufficiently covered by seismic surveys and (2) global gravity models have a relatively high accuracy and resolution. In regional and local studies, the gravimetric Moho determination requires either a detailed crustal density model or seismic data (for a combined gravity and seismic data inversion). We also demonstrate that the Earth's long-wavelength gravity spectrum comprises not only the gravitational signal of deep mantle heterogeneities (including the core-mantle boundary zone), but also shallow crustal structures. Consequently, the application of spectral filtering in the gravimetric Moho determination will remove not only the gravitational signal of (unknown) mantle heterogeneities, but also the Moho signature at the long-wavelength gravity spectrum. [ABSTRACT FROM AUTHOR]