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This study presents a solution of the ‘1 cm Geoid Experiment’ (Colorado Experiment) using spherical radial basis functions (SRBFs). As the only group using SRBFs among the fourteen participated institutions from all over the world, we highlight the methodology of SRBFs in this paper. Detailed explanations are given regarding the settings of the four most important factors that influence the performance of SRBFs in gravity field modeling, namely (1) the choosing bandwidth, (2) the locations of the SRBFs, (3) the type of the SRBFs as well as (4) the extensions of the data zone for reducing the edge effect. Two types of basis functions covering the same spectral range are used for the terrestrial and the airborne measurements, respectively. The non-smoothing Shannon function is applied to the terrestrial data to avoid the loss of spectral information. The cubic polynomial (CuP) function which has smoothing features is applied to the airborne data as a low-pass filter for filtering the high-frequency noise. Although the idea of combining different SRBFs for different observations was proven in theory to be possible, it is applied to real data for the first time, in this study. The RMS error of our height anomaly result along the GSVS17 benchmarks w.r.t the validation data (which is the mean results of the other contributions in the ‘Colorado Experiment’) drops by 5% when combining the Shannon function for the terrestrial data and the CuP function for the airborne data, compared to those obtained by using the Shannon function for both the two data sets. This improvement indicates the validity and benefits of using different SRBFs for different observation types. Global gravity model (GGM), topographic model, the terrestrial gravity data, as well as the airborne gravity data are combined, and the contribution of each data set to the final solution is discussed. By adding the terrestrial data to the GGM and the topographic model, the RMS error of the height anomaly result w.r.t the validation data drops from 4 to 1.8 cm, and it is further reduced to 1 cm by including the airborne data. Comparisons with the mean results of all the contributions show that our height anomaly and geoid height solutions at the GSVS17 benchmarks have an RMS error of 1.0 cm and 1.3 cm, respectively; and our height anomaly results give an RMS value of 1.6 cm in the whole study area, which are all the smallest among the participants.

In this contribution, we use all three components of the gravity vector observations to compute a regional geoid and demonstrate the advantages of using the horizontal components alongside the vertical component. We apply the one-step integration method within the remove-compute-restore framework; where the long-wavelength part of the geoid is recovered from Earth’s gravitational models while the harmonicity of the computational space is ensured by removing the topographic effects. We create a system of linear equations using a discretized form of the one-step integration method and use the Tikhonov technique to deal with the numerical instability due to its implicit downward continuation and to determine the geoid at higher resolution, e.g., 1 ′ × 1′. We propose a novel method to estimate the Tikhonov regularization parameter using the discrepancy principal and a stable solution of the geoid at lower resolution, e.g., 3′ × 3′. The results reported are based on real airborne gravity vector observations collected over Colorado, USA. The scattered observations at flight level are directly inverted to the disturbing potential at grid points on the reference ellipsoid, where geoid heights are then computed using Bruns formula. We evaluate the external accuracy of the geoid by comparing it with GNSS/levelling data and estimate the location-based internal uncertainties (error) of the geoid heights through formal error propagation. As part of this contribution, the airborne gravity vector data used in this study are also available for research purposes upon request to the corresponding author.

In this study, a novel three-scale spherical radial basis function (SRBF) modeling method is proposed for regional geoid determination in Colorado. By sequentially constructing the SRBF model across three distinct frequency bands—medium, high, and ultrahigh—this approach effectively captures detailed signals that traditional single- and two-scale SRBF approaches may fail to resolve. In addition, unlike conventional methods that remove residual terrain model (RTM) contributions prior to modeling, the proposed approach retains RTM effects within the SRBF modeling frequency bands, potentially minimizing errors associated with their removal and subsequent restoration. Validation against the geoid slope validation survey 2017 (GSVS17) data indicates that the geoid model derived from the three-scale SRBF approach achieves a standard deviation (STD) of 2.0 cm, outperforming models derived from single- and two-scale SRBF methods. Furthermore, retaining RTM effects during SRBF modeling yields a slight improvement over models where these effects are removed beforehand. These results highlight the effectiveness of the three-scale SRBF method in constructing high-accuracy regional geoid models, particularly in mountainous areas.

The harmonic correction (HC) is one of the key quantities when using residual terrain modelling (RTM) for high-frequency gravity field modelling. In the RTM technique, high-frequency topographic gravitational signals are obtained through removing gravitational effects of a long-wavelength reference surface, e.g., MERIT2160. There might be points located below the reference surface. In such cases, the RTM gravity field is calculated in the non-harmonic condition, HC is therefore required. Over past decades, though various methods have been proposed to handle the HC issue for the RTM technique, most of them were focused on the HC for RTM gravity anomaly rather than for other gravity functionals, such as RTM geoid height. In practice, the HC for RTM geoid height was generally assumed to be negligible, but a detailed quantification was missing for present-day RTM computations. This might cause large errors in the regional geoid determination over rugged areas. In this study, we derive HC expressions for the RTM geoid height in the framework of the classical condensation method. The HC terms are derived under four different assumptions separately: residual masses approximated by an unlimited Bouguer plate, residual masses approximated by a limited Bouguer plate which overcomes the mass inconsistency effect, residual masses approximated by a Bouguer shell which overcomes the effect of planar approximation, and residual masses approximated by a limited Bouguer shell which overcomes the errors induced by both planar approximation and mass-inconsistency. The errors due to various approximations in HC terms are investigated through comparison among various terms. Besides, HC terms are computed using an expansion up to degree and order 2159. Our results show that HC for RTM geoid height is less 1 mm and could be ignored over ∼99% of continental areas, but be of great significance for regional geoid determination over mountain areas, e.g., more than 10 cm effect over very rugged areas. The validation through comparison with terrestrial measurements and a baseline solution of the RTM technique proves that the HC terms provided in this study can improve the accuracy of RTM geoid heights and are expected to be useful for applications of the RTM technique in regional and global gravity field modelling.

In traditional airborne gravimetry, the vertical component of the gravity vector is used as an approximation of the measured magnitude of the gravity vector, which enters the determination of the local geoid. In this study, a comprehensive computational scheme for determining the local geoid using three components of the airborne gravity vector is presented. Our approach extends the existing one-step method for local geoid modeling by incorporating the full gravity vector measured by airborne sensors as boundary values in the gravimetric boundary-value problem. We derive integral kernel functions along with far-zone contributions for the three components of the airborne gravity vector and apply deterministic modifications to them. To validate our derivations, we use a global geopotential model (GGM)-based airborne gravity vectors burdened with realistic colored noise at one of the most challenging test sites for geoid determination, the 1-cm geoid test area in Colorado (USA). Results of closed-loop tests confirm that applying all three components of the GGM-based airborne gravity vector improves the internal accuracy of the geoid by 50% compared to using only the vertical component. We further use real airborne gravity vectors observed at a test site in the same region and show that the STD of the estimated geoid heights evaluated against the reference geoidal heights along the Geoid Slope Validation Survey of 2017 (GSVS17) Line is 2.3 cm using the “traditional approach” and 1.3 cm including the horizontal components. This indicates a significant improvement in the external accuracy (~ 46%) of the geoid when the full gravity vector is used, without using other heterogeneous observations. Graphical Abstract

Recent technological advances in optical atomic clocks are opening new perspectives for the direct determination of geopotential differences between any two points at a centimeter-level accuracy in geoid height. However, so far detailed quantitative estimates of the possible improvement in geoid determination when adding such clock measurements to existing data are lacking. We present a first step in that direction with the aim and hope of triggering further work and efforts in this emerging field of chronometric geodesy and geophysics. We specifically focus on evaluating the contribution of this new kind of direct measurements in determining the geopotential at high spatial resolution ( ≈ 10 km). We studied two test areas, both located in France and corresponding to a middle (Massif Central) and high (Alps) mountainous terrain. These regions are interesting because the gravitational field strength varies greatly from place to place at high spatial resolution due to the complex topography. Our method consists in first generating a synthetic high-resolution geopotential map, then drawing synthetic measurement data (gravimetry and clock data) from it, and finally reconstructing the geopotential map from that data using least squares collocation. The quality of the reconstructed map is then assessed by comparing it to the original one used to generate the data. We show that adding only a few clock data points (less than 1% of the gravimetry data) reduces the bias significantly and improves the standard deviation by a factor 3. The effect of the data coverage and data quality on the results is investigated, and the trade-off between the measurement noise level and the number of data points is discussed.

We developed a refined gravimetric geoid model for Japan on a 1 × 1.5 arc-minute (2 km) grid from a GOCE-based satellite-only global geopotential model and a regional gravity field model updated in this study. First, we have constructed a regional gravity field model for Japan using updated gravity datasets together with a residual terrain model: 323,431 land gravity data, 77,389 shipborne marine gravity data, and Sandwell’s v28.1 altimetry-derived global marine gravity model. Then, the geoid was determined with the gravity field model. The methodology for gravimetric geoid determination was based on the remove–compute–restore technique with Helmert’s second method of condensation of topography (Stokes–Helmert scheme). Here, the hybrid Meissl–Molodensky modified spheroidal Stokes kernel was employed to minimize the truncation error under an appropriate combination of different kinds of gravity data. In addition, a high-resolution GSI-DEM on a 0.4 × 0.4 arc-second (10 m) grid, together with the SRTM-DEM on a 7.5 × 11.25 arc-second (250 m) grid, was utilized for precisely applying terrain correction to the regional gravity field model. Consequently, we created a gravimetric geoid model for Japan, consistent with 971 GNSS/leveling geoid heights distributed over the four main islands of Japan with a standard deviation of 5.7 cm, showing a considerable improvement by 2.3 cm over the previous model (JGEOID2008). However, there remain some areas with large discrepancies between the computed and GNSS/leveling geoid heights in northern Japan (Hokkaido), mountainous areas in central Japan, and some coastal regions. Since terrestrial gravity data are especially sparse in these areas, we speculated that the largeness of the geoid discrepancies there could be partly attributed to the insufficient coverage and accuracy of gravity data. The Geospatial Information Authority of Japan has started airborne gravity surveys to be covered over the Japanese Islands, and in future, we plan to develop a geoid model for Japan further accurately by incorporating airborne gravity data to come.

This paper represents a milestone in the UNB effort to formulate an accurate and self-consistent theory for regional geoid determination. To get the geoid to a sub-centimetre accuracy, we had to formulate the theory in a spherical rather than linear approximation, advance the modelling of the effect of topographic mass density, formulate the solid spherical Bouguer anomaly, develop the probabilistic downward continuation approach, incorporate improved satellite determined global gravitational models and introduce a whole host of smaller improvements. Having adopted Auvergne, an area in France as our testing ground, where the mean standard deviation of observed gravity values is 0.5 mGal, according to the Institute Geographique Nationale (Duquenne in Proceedings of the 1st international symposium of the international gravity field service “gravity field of the earth”, International gravity field service meeting, Istanbul, Turkey, 2006 ), we obtained the standard deviation of the gravity anomalies continued downward to the geoid, as estimated by minimizing the L 2 norm of their residuals, to be in average 3 times larger than those on the surface with large spikes underneath the highest topographic points. The standard deviations of resulting geoidal heights range from a few millimetres to just over 6 cm for the highest topographic points in the Alpine region (just short of 2000 m). The mean standard deviations of the geoidal heights for the whole region are only 0.6 cm, which should be considered quite reasonable even if one acknowledges that the area of Auvergne is mostly flat. As one should expect, the main contributing factors to these uncertainties are the Poisson probabilistic downward continuation process, with the maximum standard deviation just short of 6 cm (the average value of 2.5 mm) and the topographic density uncertainties, with the maximum value of 5.6 cm (the average value of 3.0 mm). The comparison of our geoidal heights with the testing geoidal heights, obtained for a set of 75 control points (regularly spaced throughout the region), shows the mean shift of 13 cm which is believed to reflect the displacement of the French vertical datum from the geoid due to sea surface topography. The mean root square error of the misfit is 3.3 cm. This misfit, when we consider the estimated accuracy of our geoid, indicates that the mean standard deviation of the “test geoid” is about 3 cm, which makes it about 5 times less accurate than the Stokes–Helmert computed geoid.

The International Service for the Geoid (ISG, https://www.isgeoid.polimi.it/, last access: 31 March 2021) provides free access to a dedicated and comprehensive repository of geoid models through its website. In the archive, both the latest releases of the most important and well-known geoid models, as well as less recent or less known ones, are freely available, giving to the users a wide range of possible applications to perform analyses on the evolution of the geoid computation research field. The ISG is an official service of the International Association of Geodesy (IAG), under the umbrella of the International Gravity Field Service (IGFS). Its main tasks are collecting, analysing, and redistributing local, regional, and continental geoid models and providing technical support to people involved in geoid-related topics for both educational and research purposes. In the framework of its activities, the ISG performs research taking advantage of its archive and organizes seminars and specific training courses on geoid determination, supporting students and researchers in geodesy as well as distributing training material on the use of the most common algorithms for geoid estimation. This paper aims at describing the data and services, including the newly implemented DOI Service for geoid models (https://dataservices.gfz-potsdam.de/portal/?fq=subject:isg, last access: 31 March 2021), and showing the added value of the ISG archive of geoid models for the scientific community and technicians, like engineers and surveyors (https://www.isgeoid.polimi.it/Geoid/reg_list.html, last access: 31 March 2021).

This study assesses the effect of the UNB Topographical Density Model on the accuracy of geoid determination in Sarajevo, Bosnia & Herzegovina. Using the KTH method, 1020 gravimetric geoid models were developed, incorporating both constant and variable density values, simple and complete Bouguer anomalies. The study found that the model computed by the UNB Topographical Density Model and complete Bouguer anomalies achieved the highest precision, with an RMSE of 1.33 cm. The final geoid model was adjusted to the old vertical datum (Trieste height), resulting in an RMSE of 3.44 cm when tested with static GNSS points. These findings underscore the importance of incorporating variable density models for improving geoid accuracy and suggest further refinement using local geological data could enhance precision.