GOCE is ESA's gravity field mission and the first satellite ever that measures gravitational gradients in space, that is, the second spatial derivatives of the Earth's gravitational potential. The goal is to determine the Earth's mean gravitational field with unprecedented accuracy at spatial resolutions down to 100 km. GOCE carries a gravity gradiometer that allows deriving the gravitational gradients with very high precision to achieve this goal. There are two types of GOCE Level 2 gravitational gradients (GGs) along the orbit: the gravitational gradients in the gradiometer reference frame (GRF) and the gravitational gradients in the local north oriented frame (LNOF) derived from the GGs in the GRF by point-wise rotation. Because the V X X , V Y Y , V Z Z and V X Z are much more accurate than V XY and V Y Z , and because the error of the accurate GGs increases for low frequencies, the rotation requires that part of the measured GG signal is replaced by model signal. However, the actual quality of the gradients in GRF and LNOF needs to be assessed. We analysed the outliers in the GGs, validated the GGs in the GRF using independent gravity field information and compared their assessed error with the requirements. In addition, we compared the GGs in the LNOF with state-of-the-art global gravity field models and determined the model contribution to the rotated GGs. We found that the percentage of detected outliers is below 0.1% for all GGs, and external gravity data confirm that the GG scale factors do not differ from one down to the 10 −3 level. Furthermore, we found that the error of V X X and V Y Y is approximately at the level of the requirement on the gravitational gradient trace, whereas the V Z Z error is a factor of 2-3 above the requirement for higher frequencies. We show that the model contribution in the rotated GGs is 2-35% dependent on the gravitational gradient. Finally, we found that GOCE gravitational gradients and gradients derived from EIGEN-5C and EGM2008 are consistent over the oceans, but that over the continents the consistency may be less, especially in areas with poor terrestrial gravity data. All in all, our analyses show that the quality of the GOCE gravitational gradients is good and that with this type of data valuable new gravity field information is obtained.
Abstract. Current knowledge of the Earth's gravity field and its geoid, as derived from various observing techniques and sources, is incomplete. Within a reasonable time, substantial improvement will come by exploiting new approaches based on spaceborne gravity observation. Among these, the European Space Agency (ESA) Gravity field and steady-state Ocean Circulation Explorer (GOCE) satellite mission concept has been conceived and designed taking into account multi-disciplinary research objectives in solid Earth physics, oceanography and geodesy. Based on the unique capability of a gravity gradiometer combined with satellite-to-satellite high-low tracking techniques, an accurate and detailed global model of the Earth's gravity field and its corresponding geoid will be recovered. The importance of this is demonstrated by a series of realistic simulation experiments. In particular, the quantitative impact of the new and accurate gravity field and geoid is examined in studies of tectonic composition and motion, Glaciological Isostatic Adjustment, ocean mesoscale variability, water mass transport, and unification of height systems. Improved knowledge in each of these fields will also ensure the accumulation of new understanding of past and present sea-level changes.
Comparison of remove-compute-restore and least squares modification of Stokes' formula techniques to quasi-geoid determination over the Auvergne test areaThe remove-compute-restore (RCR) technique for regional geoid determination implies that both topography and low-degree global geopotential model signals are removed before computation and restored after Stokes' integration or Least Squares Collocation (LSC) solution. The Least Squares Modification of Stokes' Formula (LSMS) technique not requiring gravity reductions is implemented here with a Residual Terrain Modelling based interpolation of gravity data. The 2-D Spherical Fast Fourier Transform (FFT) and the LSC methods applying the RCR technique and the LSMS method are tested over the Auvergne test area. All methods showed a reasonable agreement with GPS-levelling data, in the order of a 3-3.5 cm in the central region having relatively smooth topography, which is consistent with the accuracies of GPS and levelling. When a 1-parameter fit is used, the FFT method using kernel modification performs best with 3.0 cm r.m.s difference with GPS-levelling while the LSMS method gives the best agreement with GPS-levelling with 2.4 cm r.m.s after a 4-parameter fit is used. However, the quasi-geoid models derived using two techniques differed from each other up to 33 cm in the high mountains near the Alps. Comparison of quasi-geoid models with EGM2008 showed that the LSMS method agreed best in term of r.m.s.
Summary. The determination of the density distribution of the Earth from gravity data is called the inverse gravimetric problem. A unique solution to this problem may be obtained by introducing a priori data concerning the covariance of density anomalies. This is equivalent to requiring the density to fulfil a minimum norm condition. The generally used norm is the one equal to the integral of the square of the density distribution (L2‐norm), the use of which implies that blocks of constant density are uncorrelated. It is shown that for harmonic anomalous density distributions this leads to an external gravity field with a power spectrum (degree‐variances) which tends too slowly to zero, i.e. implying gravity anomalies much less correlated than actually observed. It is proposed to use a stronger norm, equal to the integral of the square sum of the derivatives of the density distribution. As a consequence of this, base functions which are constant within blocks, are no longer a natural choice when solving the inverse gravimetric problem. Instead a block with a linearly varying density may be used. A formula for the potential of such a block is derived.
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