The gravity field and GGOS

The gravity field of the earth is a natural element of the Global Geodetic Observing System (GGOS). Gravity field quantities are like spatial geodetic observations of potential very high accuracy, with measurements, currently at part-per-billion (ppb) accuracy, but gravity field quantities are also unique as they can be globally represented by harmonic functions (long-wavelength geopotential model primarily from satellite gravity field missions), or based on point sampling (airborne and in situ absolute and superconducting gravimetry). From a GGOS global perspective, one of the main challenges is to ensure the consistency of the global and regional geopotential and geoid models, and the temporal changes of the gravity field at large spatial scales. The International Gravity Field Service, an umbrella “level-2” IAG service (incorporating the International Gravity Bureau, International Geoid Service, International Center for Earth Tides, International Center for Global Earth models, and other future new services for, e.g., digital terrain models), would be a natural key element contributing to GGOS. Major parts of the work of the services would, however, remain complementary to the GGOS contributions, which focus on the long-wavelength components of the geopotential and its temporal variations, the consistent procedures for regional data processing in a unified vertical datum and Terrestrial Reference Frame, and the ensuring validations of long-wavelength gravity field data products.     

On the use of iterative re-weighting least-squares and outlier detection for empirically modelling rates of vertical displacement

The proper identification and removal of outliers in the combination of rates of vertical displacements derived from GPS, tide gauges/satellite altimetry, and GRACE observations is presented. Outlier detection is a necessary pre-screening procedure in order to ensure reliable estimates of stochastic properties of the observations in the combined least-squares adjustment (via rescaling of covariance matrices) and to ensure that the final vertical motion model is not corrupted and/or distorted by erroneous data. Results from this study indicate that typical data snooping methods are inadequate in dealing with these heterogeneous data sets and their stochastic properties. Using simulated vertical displacement rates, it is demonstrated that a large variety of outliers (random scattered and adjacent, as well as jointly influential) can be dealt with if an iterative re-weighting least-squares adjustment is combined with a robust median estimator. Moreover, robust estimators are efficient in areas weakly constrained by the data, where even high quality observations may appear to be erroneous if their estimates are largely influenced by outliers. Four combined models for the vertical motion in the region of the Great Lakes are presented. The computed vertical displacements vary between  − 2 mm/year (subsidence) along the southern shores and 3 mm/year (uplift) along the northern shores. The derived models provide reliable empirical constraints and error bounds for postglacial rebound models in the region.     

Advances in the numerical solution of the linear molodensky problem

The solution of the linear Molodensky problem by analytical continuation to point level is numerically the most convenient of all the theoretically equivalent solutions. It is obtained by successively applying the same integral operator and it does not depend explicitly on the terrain inclination. However, its dependence on the computation point restricts somehow the computational efficiency. The use of the Fourier transform for the evaluation of the integral operator in planar approximation lessens significantly the burden of computations. Using this spectral approach, the problem has been reformulated and solved in the frequency domain. Moreover, it is shown that the solution can be easily split into two steps: (a) “downward” continuation to sea level, which is independent of the computation point, and (b) “upward” continuation from sea to point level, using the values computed at sea level. Such a treatment not only simplifies the formulas and increases the numerical efficiency but also clarifies the physical interpretation and the theoretical equivalence of the continuation solution with respect to the other solution types. Numerical tests have been performed to investigate which terms in the Molodensky series are of significance for geoid and deflection computations. The practical difficulty of differences in the grid spacings of gravity and height data has been overcome by frequency domain interpolation. Presented at theXIX IUGG General Assembly, Vancouver, B.C., August 9–22, 1987.     

Adaptive filtering of GOCE-derived gravity gradients of the disturbing potential in the context of the space-wise approach

Filtering and signal processing techniques have been widely used in the processing of satellite gravity observations to reduce measurement noise and correlation errors. The parameters and types of filters used depend on the statistical and spectral properties of the signal under investigation. Filtering is usually applied in a non-real-time environment. The present work focuses on the implementation of an adaptive filtering technique to process satellite gravity gradiometry data for gravity field modeling. Adaptive filtering algorithms are commonly used in communication systems, noise and echo cancellation, and biomedical applications. Two independent studies have been performed to introduce adaptive signal processing techniques and test the performance of the least mean-squared (LMS) adaptive algorithm for filtering satellite measurements obtained by the gravity field and steady-state ocean circulation explorer (GOCE) mission. In the first study, a Monte Carlo simulation is performed in order to gain insights about the implementation of the LMS algorithm on data with spectral behavior close to that of real GOCE data. In the second study, the LMS algorithm is implemented on real GOCE data. Experiments are also performed to determine suitable filtering parameters. Only the four accurate components of the full GOCE gravity gradient tensor of the disturbing potential are used. The characteristics of the filtered gravity gradients are examined in the time and spectral domain. The obtained filtered GOCE gravity gradients show an agreement of 63–84 mEötvös (depending on the gravity gradient component), in terms of RMS error, when compared to the gravity gradients derived from the EGM2008 geopotential model. Spectral-domain analysis of the filtered gradients shows that the adaptive filters slightly suppress frequencies in the bandwidth of approximately 10–30 mHz. The limitations of the adaptive LMS algorithm are also discussed. The tested filtering algorithm can be connected to and employed in the first computational steps of the space-wise approach, where a time-wise Wiener filter is applied at the first stage of GOCE gravity gradient filtering. The results of this work can be extended to using other adaptive filtering algorithms, such as the recursive least-squares and recursive least-squares lattice filters.     

Use of GRACE determined secular gravity rates for glacial isostatic adjustment studies in North-America

Monthly geopotential spherical harmonic coefficients from the GRACE satellite mission are used to determine their usefulness and limitations for studying glacial isostatic adjustment (GIA) in North-America. Secular gravity rates are estimated by unweighted least-squares estimation using release 4 coefficients from August 2002 to August 2007 provided by the Center for Space Research (CSR), University of Texas. Smoothing is required to suppress short wavelength noise, in addition to filtering to diminish geographically correlated errors, as shown in previous studies. Optimal cut-off degrees and orders are determined for the destriping filter to maximize the signal to noise ratio. The halfwidth of the Gaussian filter is shown to significantly affect the sensitivity of the GRACE data (with respect to upper mantle viscosity and ice loading history). Therefore, the halfwidth should be selected based on the desired sensitivity.It is shown that increase in water storage in an area south west of Hudson Bay, from the summer of 2003 to the summer of 2006, contributes up to half of the maximum estimated gravity rate. Hydrology models differ in the predictions of the secular change in water storage, therefore even 4-year trend estimates are influenced by the uncertainty in water storage changes. Land ice melting in Greenland and Alaska has a non-negligible contribution, up to one-fourth of the maximum gravity rate.The estimated secular gravity rate shows two distinct peaks that can possibly be due to two domes in the former Pleistocene ice cover: west and south east of Hudson Bay. With a limited number of models, a better fit is obtained with models that use the ICE-3G model compared to the ICE-5G model. However, the uncertainty in interannual variations in hydrology models is too large to constrain the ice loading history with the current data span. For future work in which GRACE will be used to constrain ice loading history and the Earth's radial viscosity profile, it is important to include realistic uncertainty estimates for hydrology models and land ice melting in addition to the effects of lateral heterogeneity.     

Contributions of terrestrial and GRACE data to the study of the secular geoid changes in North America

This paper tests and discusses different statistical methods for modelling secular rates of change of the geoid in North America. In particular, we use the method of principal component/empirical orthogonal functions (PC/EOF) analysis to model the geoid rates from Gravity Recovery and Climate Experiment (GRACE) satellite data. As demonstrated, the PC/EOF analysis is useful for studying the contributions from different signals (mainly residual hydrology signals and leakage effects) to the GRACE-derived geoid rates. The PC/EOF analysis leads to smaller geoid rates compared to the conventional least-squares fitting of a trend and annual and semi-annual cycles to the time series of the spherical harmonic coefficients. This is because we filter out particular spatiotemporal modes of the regional geoid changes.We apply the method of least-squares collocation with parameters to combine terrestrial data (GPS vertical velocities from the Canadian Base Network and terrestrial gravity rates from the Canadian Gravity Standardization Net) with the GRACE-derived vertical motion to obtain again the geoid rates. The combined model has a peak geoid rate of 1.4 mm/year in the southeastern area of Hudson Bay contrary to the GRACE-derived geoid rates that show a large peak of 1.6–1.7 mm/year west of Hudson Bay. We demonstrate that the terrestrial data, which have a longer time span than the GRACE data, are important for constraining the GRACE-derived secular signal in the areas that are well sampled by the data.     

The AUSGeoid98 geoid model of Australia: data treatment, computations and comparisons with GPS-levelling data

 The AUSGeoid98 gravimetric geoid model of Australia has been computed using data from the EGM96 global geopotential model, the 1996 release of the Australian gravity database, a nationwide digital elevation model, and satellite altimeter-derived marine gravity anomalies. The geoid heights are on a 2 by 2 arc-minute grid with respect to the GRS80 ellipsoid, and residual geoid heights were computed using the 1-D fast Fourier transform technique. This has been adapted to include a deterministically modified kernel over a spherical cap of limited spatial extent in the generalised Stokes scheme. Comparisons of AUSGeoid98 with GPS and Australian Height Datum (AHD) heights across the continent give an RMS agreement of ±0.364 m, although this apparently large value is attributed partly to distortions in the AHD. Received: 10 March 2000 / Accepted: 21 February 2001