Regional recovery of the gravity field from satellite gravity gradiometer and gravity vector data using collocation

The method of least squares collocation has been used to investigate the regional recovery of the gravity field from satellite gravity gradiometer (SGG) data and gravity vector data derived from, e.g., satellite-to-satellite tracking (SST). We chose a region centered over the European Alps where the gravity anomalies showed a (large) standard deviation of 60 mGal. Mean gravity anomalies were used to generate SGG data at a satellite altitude of 200 km. As SGG data we used the second-order derivatives in radial direction, across-track, and the mixed radial/cross-track derivative, all assumed to have an associated noise equal to 0.01 EU (Eotvos unit =EU, 1 EU=10−9 s−2). As gravity data we used the three components of the gravity vector, assuming that the associated errors were uncorrelated noise with standard deviation equal to 1 mGal. The satellite data in the test area were used in combination to predict 0.5° mean gravity anomalies and geoid heights. Ground truth data were used to investigate the quality of the recovery. The difference between observed and computed values have a standard deviation equal to 22 mGal in the best case. The use of the gravity vector data gave no improvement when added to the SGG data. The use of topographic information with 5 arc min resolution (ETOPO5U) gave, after removal of severe errors, a 17-mGal standard deviation of observed minus computed values. This is a much smaller improvement than expected but is due to errors in the topographic values.