a b s t r a c tWeekly surface loading variations are estimated from a joint least squares inversion of load-induced GPS site displacements, GRACE gravimetry and simulated ocean bottom pressure (OBP) from the finite element sea-ice ocean model (FESOM).In this study, we directly use normal equations derived from reprocessed GPS observations, where station and satellite positions are estimated simultaneously. The OBP weight of the model in the inversion is based on a new error model, obtained from 2 FESOM runs forced with different atmospheric data sets.Our findings indicate that the geocenter motion derived from the inversion is smooth, with nonseasonal RMS values of 1.4, 0.9 and 1.9 mm for the X, Y and Z directions, respectively. The absolute magnitude of the seasonal geocenter motion varies annually between 2 and 4.5 mm. Important hydrological regions such as the Amazon, Australia, South-East Asia and Europe are mostly affected by the geocenter motion, with magnitudes of up to 2 cm, when expressed in equivalent water height.The chosen solar radiation pressure model, used in the GPS processing, has only a marginal effect on the joint inversion results. Using the empirical CODE model slightly increases the annual amplitude of the Z component of the geocenter by 0.8 mm. However, in case of a GPS-only inversion, notable larger differences are found for the annual amplitude and phase estimates when applying the older physical ROCK models. Regardless of the used radiation pressure model the GPS network still exhibits maximum radial expansions in the order of 3 mm (0.45 ppb in terms of scale), which are most likely caused by remaining GPS technique errors.In an additional experiment, we have used the joint inversion solution as a background loading model in the GPS normal equations. The reduced time series, compared to those without a priori loading model, show a consistent decrease in RMS. In terms of the annual height component, 151 of the 189 stations show a reduction of at least 10% in seasonal amplitude.On the ocean floor, we find a positive overall correlation (0.51) of the inversion solution with time series from globally distributed independent bottom pressure recorders.Even after removing a seasonal fit we still find a correlation of 0.45. Furthermore, the geocenter motion has a significant effect on ocean bottom pressure as neglecting it causes the correlation to drop to 0.42.

a b s t r a c tSatellite altimetry and GRACE observations carry both the signature of ocean tides and have in general complementary potential to resolve tidal constituents. It is therefore straightforward to perform a combined estimation of a global ocean tide model based on these two data sources. The present paper develops and applies a three step procedure for generating such a combined ocean tide model. First, the processing of multi-mission altimetry data is described along with the harmonic analysis applied to derive initially a pure empirical ocean tide model. Then the capability of GRACE to sense particular tidal constituents is elaborated and an approach to estimate tidal constituents from GRACE is outlined. In a third step a combination strategy with optimal stochastic data treatment is developed and applied to the altimetry-only tide model EOT08a and four years of GRACE observations, leading to the combined model EOT08ag. The differential contributions of GRACE to EOT08ag remain small and are mainly concentrated to the Arctic Ocean, an area with little or poor altimetry data. In comparison with other tide models, EOT08ag is validated by K-band range residuals, the impact on gravity field modelling and on precise orbit determination and by variance reduction of crossover differences. None of these comparison exhibits a significant improvement over the altimetry-only tide model except for a few areas above 60 • N. Overall the improvements of the combination remain small and appear to stay below the current GRACE baseline accuracy.

Temporal aliasing effects have a large impact on the gravity field accuracy of current gravimetry missions and are also expected to dominate the error budget of Next Generation Gravimetry Missions (NGGMs). This paper focuses on aspects concerning their treatment in the context of Low‐Low Satellite‐to‐Satellite Tracking NGGMs. Closed‐loop full‐scale simulations are performed for a two‐pair Bender‐type Satellite Formation Flight (SFF), by taking into account error models of new generation instrument technology. The enhanced spatial sampling and error isotropy enable a further reduction of temporal aliasing errors from the processing perspective. A parameterization technique is adopted where the functional model is augmented by low‐resolution gravity field solutions coestimated at short time intervals, while the remaining higher‐resolution gravity field solution is estimated at a longer time interval. Fine‐tuning the parameterization choices leads to significant reduction of the temporal aliasing effects. The investigations reveal that the parameterization technique in case of a Bender‐type SFF can successfully mitigate aliasing effects caused by undersampling of high‐frequency atmospheric and oceanic signals, since their most significant variations can be captured by daily coestimated solutions. This amounts to a “self‐dealiasing” method that differs significantly from the classical dealiasing approach used nowadays for Gravity Recovery and Climate Experiment processing, enabling NGGMs to retrieve the complete spectrum of Earth's nontidal geophysical processes, including, for the first time, high‐frequency atmospheric and oceanic variations.

No abstract

No abstract