SUMMARY The Combination Service for Time-variable Gravity fields (COST-G) operationally provides combinations of monthly Earth gravity field models derived from observations of the microwave ranging instrument of the GRACE Follow-on (GRACE-FO) satellite mission, applying the quality control and combination methodology originally developed by the Horizon 2020 project European Gravity Service for Improved Emergency Management for the data of the GRACE satellites. In the frame of the follow-up Horizon 2020 project Global Gravity-based Groundwater Product (G3P), the GRACE-FO combination is used to derive global grids of groundwater storage anomalies. To meet the user requirements and achieve optimal signal-to-noise ratio, the combination has been further developed and extended to incorporate: • new time-series based on the alternative accelerometer transplant product generated in the frame of the project by the Institute of Geodesy at the Graz University of Technology, which specifically improves the estimation of the C30 coefficient and also reduces the noise at medium to short wavelengths, and • the new time-series AIUB–GRACE-FO–RL02 of monthly GRACE-FO gravity fields, which is derived at the Astronomical Institute of the University of Bern by applying empirical noise modelling techniques. The COST-G quality control confirms the consistency of the contributing GRACE-FO time-series concerning the signal amplitude of seasonal hydrology in large river basins and the secular mass change in polar regions, but it also indicates rather diverse noise characteristics. The difference in the noise levels is taken into account in the combination process by relative weights derived by variance component estimation on the solution level. The weights are expected to be inverse proportional to the noise levels of the individual gravity field solutions. However, this expectation is violated when applying the weighting scheme as developed for the GRACE combination. The reason is found in the high-order coefficients of the gravity field, which are poorly determined from the low–low range-rate observations due to the observation geometry and suffer from aliasing due to the malfunctioning accelerometer onboard one of the GRACE-FO satellites. Hence, for the final G3P-combination a revised weighting scheme is applied where the gravity field coefficients beyond order 60 are excluded from the determination of the weights. The quality of the combined gravity fields is assessed by comparison of the noise content and the signal-to-noise ratio with the individual time-series. Independent validation is provided by the COST-G validation centre at the GFZ German Research Centre for Geosciences, where orbit fits of the low-flying Gravity and steady-state Ocean Circulation Explorer satellite are performed that confirm the high quality of the combined GRACE-FO gravity fields. By the end of the G3P project, the new combination scheme is implemented by COST-G as the new COST-G–GRACE-FO–RL02 and continued to be used for the operational GRACE-FO combination.

A detailed and precise knowledge of ocean bottom topography is essential in many geoscientific and oceanographic applications. Shipborne echo sounding provides the only direct bathymetric method. However, even after decades of applying this technique only a fraction of the global ocean could be covered. Alternatively, gravity data inversion is a feasible method to infer ocean bottom topography since the gravity field correlates with topography at short to medium wavelengths. Gravity field observables are globally provided by dedicated satellite missions like GOCE, GRACE and GRACE-FO and, over the oceans, by satellite altimetry. Regional and local measurements are realised by means of ground-based, shipborne and airborne gravimetry. For the first time in Europe a jet aircraft was used for airborne gravimetry. During the GEOHALO flight campaign over Italy and the Tyrrhenian, Ionian and Adriatic seas in June 2012, the German research aircraft HALO carried an entire suite of geodetic-geophysical instrumentation, including gravity metres. The careful processing of the gravity data acquired by the CHEKAN-AM instrument of the German Research Centre for Geosciences allowed to achieve an accuracy at the mGal level. Subsequently, the Parker-Oldenburg inversion was applied to predict ocean bottom topography along the GEOHALO profiles flown over the ocean. To constrain the parameter space in the inversion we used the Crust1.0 model. Finally, the obtained results were compared to the General Bathymetric Chart of the Oceans in order to estimate the performance of the method. Our study demonstrates that airborne gravimetry aboard a jet aircraft is capable to provide valuable data for regional geoscientific studies.

The paper in question by Van Camp and co-authors [MVC] challenges previous work showing that ground gravity data arising from hydrology can provide a consistent signal for the comparison with satellite gravity data. The data sets used are similar to those used previously, that is, the gravity field as measured by the GRACE satellites versus ground-based data from superconducting gravimeters (SGs) over the same continental area, in this case Central Europe. One of the main impediments in this paper is the presentation that is frequently confusing and misleading as to what the data analysis really shows, for example, the irregular treatment of annual components that are first subtracted then reappear in the analysis. More importantly, we disagree on specific points. Two calculations are included in our comment to illustrate where we believe that the processing in [MVC] paper is deficient. The first deals with their erroneous treatment of the global hydrology using a truncated spherical harmonic approach which explains almost a factor 2 error in their computation of the loading. The second shows the effect of making the wrong assumption in the GRACE/hydrology/surface gravity comparison by inverting the whole of the hydrology loading for underground stations. We also challenge their claims that empirical orthogonal function techniques cannot be done in the presence of periodic components, and that SG data cannot be corrected for comparisons with GRACE data. The main conclusion of their paper, that there is little coherence between ground gravity stations and this invalidates GRACE comparisons, is therefore questionable. There is nothing in [MVC] that contradicts any of the previous papers that have shown clearly a strong relation between seasonal signals obtained from both ground gravity and GRACE satellite data.

The GRACE (Gravity Recovery and Climate Experiment) satellite mission provides global time-series of the Earth's gravity field. In view of limited resolution and noise from the GRACE data, various filtering techniques have been developed to extract an optimal signal. There is no conclusion on the best filter method so far, however. On the other hand, terrestrial gravity observations from superconducting gravimeters (SGs) provide variations of the gravity field with very high accuracy and time resolution, but only at single points. The aim of this study is to compare GRACE-derived temporal gravity variations with gravity time-series within a network of six Central European SG stations. Empirical orthogonal functions (EOF) analysis was applied to detect common signal characteristics over a 3 yr period (2004–2006). rms Differences between the time-series of several GRACE solutions amount to 60 per cent of the rms variability of the individual data sets. The rms differences between the SG and GRACE time-series are about 70 per cent of the rms value of the SG observations. The best agreement between SG and GRACE is obtained when using a Gaussian filter with filter lengths of 800–1250 km for the GRACE data. With the EOF analysis, a common regional signal can be deduced from all gravity data sets. Nevertheless, differences in the first EOF among the GRACE solutions were up to 40 per cent, and differences of up to 50 per cent were found between the SG-based terrestrial and the GRACE-based satellite observations.

Time variable gravity field models derived from the satellite mission GRACE have been demonstrated to be consistent with water mass variations in the global hydrological cycle. Independent observations are provided by terrestrial measurements. In order to achieve a maximum of reliability and information gain, ground-based gravity observations may be deployed for comparison with the gravity field variations derived from the GRACE satellite mission. In this context, the data of the network of superconducting gravimeters (SG) of the 'Global Geodynamics Project' (GGP) are of particular interest. This study is focused on the dense SG network in Central Europe with its long-term gravity observations. It is shown that after the separation and reduction of local hydrological effects in the SG observations especially for subsurface stations, the time-variable gravity signals from GRACE agree well with the terrestrial observations from the SG station cluster.Station stability of the SG sites with respect to vertical deformations was checked by GNSS based observations. Most of the variability can be explained by loading effects due to changes in continental water storage, and, in general, the stability of all stations has been confirmed.From comparisons based on correlation and coherence analyses in combination with the root mean square (RMS) variability of the time series emerges, that the maximum correspondence between the SG and GRACE time series is achieved when filtering the GRACE data with Gaussian filters of about 1000 km filter length, which is in accordance with previous publications.Empirical Orthogonal Functions (EOF) analysis was applied to the gravity time series in order to identify common characteristic spatial and temporal patterns. The high correspondence of the first modes for GRACE and SG data implies that the first EOF mode represents a large-scale (Central European) time-variable gravity signal seen by both the GRACE satellites and the SG cluster. (C) 2011 Elsevier Ltd. All rights reserved.