This session solicits contributions about:
(1) Results from satellite gravimetry missions as well as from non-dedicated satellite missions in terms of
- data analyses to retrieve time-variable and static global gravity field models,
- combination synergies, and
- Earth science applications.
(2) The status and study results for future gravity field missions.
The GRACE Follow-On (GRACE-FO) satellite mission, a partnership between NASA (US) and GFZ (Germany), successfully completed its nominal five-year prime mission phase in May 2023, and is currently in its extended mission phase. GRACE-FO continues the unique essential climate data record of mass change in the Earth system initiated in 2002 by the GRACE mission (2002-2017). The combined GRACE & GRACE-FO data records now span 24 years and provide foundational observations of monthly to decadal global mass changes and transports in the Earth system derived from temporal variations in the Earth’s gravity field. In parallel, as part of NASA’s Earth System Observatory (ESO), a continuity mission called GRACE-Continuity (GRACE-C) scheduled for launch end of 2028 is being developed in partnership between NASA (US) and DLR (Germany), leveraging heritage elements considerably in the design. One departure from heritage, is that the primary ranging instrument on GRACE-C will be a higher precision laser interferometer, capitalizing on the successful demonstration of this technology on GRACE-FO. In this presentation, we will present updates on GRACE-FO in the context of satellite operations, data processing, and science/applications highlights, along with updates on the development of GRACE-C, which is meanwhile in Phase D after having successfully passed the System Integration Review in October 2025. Prospects for achieving gap-free continuity between GRACE-FO and GRACE-C will be presented.
How to cite: Eicker, A., Wiese, D., Landerer, F., Klipstein, W., Dahle, C., Snopek, K., Fischer, S., Save, H., Mccullough, C., Bettadpur, S., and Gaston, R.: Towards 30-years of mass change observations: GRACE Follow-On extended mission phase, and GRACE-Continuity developments, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-16387, https://doi.org/10.5194/egusphere-egu26-16387, 2026.
Being part of the GRACE/GRACE-FO Science Data System, the GFZ Helmholtz Centre for Geosciences is one of the official Level-2 processing centers routinely providing monthly gravity field models. From these models, mass changes at the Earth’s surface can be inferred and a wide range of geoscientists make use of them to study climate related phenomena. Meanwhile, GFZ’s operationally processed monthly gravity fields have been based on release 6 (RL06) processing standards since 2018. However, several processing improvements were already developed during this period, mostly within the Research Unit “New Refined Observations of Climate Change from Spaceborne Gravity Missions” (NEROGRAV) funded by the German Research Foundation DFG. As a result, GFZ now releases a reprocessed and improved RL07 time series.
When developing the new GFZ RL07 processing standards, the main focus was on an optimized stochastic modeling during the GRACE/GRACE-FO gravity field determination. This includes the extension of the stochastic instrument error models, the optimization of the combination of the different observations in terms of relative weighting, and the inclusion of temporally changing non-tidal background model error variance-covariance matrices in the adjustment process. Further changes compared to GFZ RL06 comprise the parameterization as well as the applied background models, e.g., the ocean tide model and the static gravity field model.
This presentation provides an overview of the GFZ RL07 performance compared to RL06 as well as to the latest releases of other processing centers. Improvements stemming from the applied advanced processing strategy lead to a significant reduction of noise (> 30% relative to GFZ RL06), as well as more realistic formal uncertainties of the estimated gravity field parameters.
How to cite: Hauk, M., Dahle, C., Murböck, M., Panafidina, N., Wilms, J., and Neumayer, K. H.: Overview of the reprocessed GFZ RL07 GRACE/GRACE-FO Level-2 time series, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-6384, https://doi.org/10.5194/egusphere-egu26-6384, 2026.
The very original motivation of the Combination Service for Time-variable Gravity fields (COST-G) has been a combination of monthly gravity fields computed by different Analysis Centres (ACs) on Normal EQuation (NEQ) level, thus, taking all formal correlations arising with the orbit and instrument
parameters directly into account. However, already early experiments within the EGSIEM project, where a prototype of the combination
service was developed, showed that the use of different nuisance parameters - set up to absorb observation and background model deficiencies - by each of the ACs leads to diverse formal uncertainty estimates of the spherical harmonic coefficients representing the Earth’s gravity field. Though formally possible, a combination on NEQ-level yielded degraded results. Even more, this rendered an automated combination process, applying Variance Component Estimation (VCE) on NEQ-level to derive relative weights for the individual AC’s contributions, impossible. Meanwhile, realistic uncertainty information is available for the majority of background models, and empirical noise modelling techniques leading to realistic uncertainty estimates are well established among the ACs processing the GRACE Follow-On data. In preparation for ESA’s Next Generation Gravity Mission (NGGM), where the combination of gravity field solutions from different ACs and a contribution from Satellite Laser Ranging (SLR) to stabilise the very low degree spherical harmonic coefficients is foreseen on NEQ-level, the combination strategy has been revisited with GRACE-FO NEQs of AIUB (rl03op), GFZ (preliminary RL07) and TUG (ITSG-Grace_operational) NEQs, as well as LAGEOS 1 and 2 and LARES 2 SLR-NEQs from AIUB and CNES, with very promising results, which we show in this contribution.
In this context, we also introduce the updated operational gravity field solution time series from the AIUB and investigate its impact on the COST-G combination. Background modelling has been revisited and the uncertainty characterisation has been improved by additionally co-estimating daily spherical harmonic coefficients constrained with AOe07 variance-covariance information.
How to cite: Lasser, M., Meyer, U., Öhlinger, F., Hauk, M., Reinquin, F., Dahle, C., Mayer-Gürr, T., and Jäggi, A.: COST-G: Towards normal equation level combination, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-16792, https://doi.org/10.5194/egusphere-egu26-16792, 2026.
The Earth's dynamic oblateness (C20), a crucial component of the time-variable gravity field, is inaccurately estimated by GRACE-FO, currently requiring replacement with Satellite Laser Ranging (SLR) values. This study identifies and corrects a key error source: anomalous accelerometer (ACC) responses to thruster firings. We discovered that the unrealistic response during Roll thruster activations correlates with the ACC's range mode, where increased detection voltage (Vd) heightens sensitivity to platform vibrations.
To address this, we developed a comprehensive physical thruster model, accounting for thrust imbalance (correlated with tank pressure differentials), mounting angle deviations, and center-of-mass (CoM) effects. Calibrated using stable Yaw-thruster data, this model was integrated into an optimized ACC processing workflow, generating new Level-1B products (ACTC1B and ACHTC1B).
Gravity field recovery using the corrected data shows a substantial improvement in C20 estimation. The RMS deviation from the SLR-derived TN-14 solution is reduced to 1.16 × 10-10, a 21.4% enhancement over the uncalibrated baseline. Spatial-temporal analysis suggests that the clustering of Roll thruster firings near the magnetic equator and their periodic modulation may link these high-frequency perturbations to the C20 bias.
This work underscores the critical importance of precise accelerometer calibration for reliable gravity field recovery, provides valuable insights for the instrument design and data processing of future gravity missions, and offers a feasible approach to reduce dependency on SLR-derived C20 values in satellite gravity products. This work has been published in Journal of Geophysical Research (JGR): Solid Earth (Shen et al., 2025, https://doi.org/10.1029/2025JB031121).
How to cite: Shen, Z., Cai, L., and Zhou, Z.: Enhancing GRACE-FO C20 Estimation Precision by Correcting Accelerometer Anomalous Responses to Thruster Firings, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-180, https://doi.org/10.5194/egusphere-egu26-180, 2026.
The Gravity Recovery and Climate Experiment (GRACE) mission, launched in 2002, functions as a probing instrument designed to measure temporal
variations in Earth's gravity field. The mission provides monthly gravity field solutions, expressed as spherical harmonic coefficients. These datasets form the basis for studying large-scale geophysical processes and climate-related mass transport. The framework of fast mascons provides linear mapping between surface mass densities and Level-2 monthly spherical harmonic observations. It is considered equivalent to mascons estimated from Level-1B observations, provided that the spherical harmonic solution covariances are available.
In this work, we investigate three mascon grid geometries: a triangular grid, a quasi-uniform pentagonal-hexagonal grid, and a latitude-longitude equal-area rectangular grid. These grids differ in computational efficiency, representation of sphere topology, and uniform area approximation. We compare the grids based on computational efficiency and area uniformity. We attempt to answer how the global mascon grid design affects the algebraic and spectral properties of the GRACE fast mascon forward operator. We further investigate the catchment average recovery from different mascon geometries.
How to cite: Kapale, V., Devaraju, B., and Guha, S.: Characterizing mascon grid geometries for the GRACE fast‑mascon framework, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-17745, https://doi.org/10.5194/egusphere-egu26-17745, 2026.
This study aims to evaluate the contribution of GRACE Follow-On (GRACE-FO) line-of-sight gravity difference (LGD) observations to the detection of Earth system mass variations. The current GRACE-FO gravity mission implements the low-low satellite-to-satellite tracking (ll-SST) technique. The conventionally derived mass variation products are not able to properly depict sub-monthly extreme weather events (EWEs) and natural hazards, given that data from the affected regions outside the occurrence periods of these short-term phenomena are also considered. However, the LGD connects the gravimetric observations to the intersatellite geometric measurements, allowing for an instantaneous observation of mass changes through intersatellite ranging.
An along-orbit analysis methodology is presented that employs instantaneous LGDs to detect sub-monthly mass variations caused by EWEs. Real intersatellite measurements of the laser ranging interferometer (LRI) on-board the two GRACE-FO satellites provided by Level-1B products are utilized as observations. The residual intersatellite range-acceleration is used as a first-order approximation of the instantaneous LRI-observed LGD, with an optimized band-pass filter (BPF) applied for signal improvement. This instantaneous LGD signal is derived by subtracting reference values computed from reduced-dynamic orbit data of the two satellites, and then corrected for non-tidal effects from atmosphere and ocean. Synthesized LGDs derived from gravity field products, such as GRACE-FO Level-2 time-variable gravity solutions, are compared with the instantaneous LGDs.
A geospatial-domain analysis is conducted using 3°×3° global monthly bin-maps that are generated with a bin-wise weighted average scheme. The two LGD components are therefore compared based on the 2D root mean squares (RMS), not only for selecting the optimal lower cut-off frequency of the BPF but also for validating the algorithm for estimating the instantaneous LGD signal. In addition, a case study of the extreme rainfall in eastern Australia in March 2021 highlights the effectiveness and advantage of the along-orbit method in capturing both monthly and sub-monthly mass variations. Key findings include the detection of terrestrial water storage changes due to the rainfall and the temporal progression of this event, emphasizing the potential of intersatellite LRI observations for near real-time monitoring of Earth system mass variations. It is also demonstrated that, as a tiny component, the residual instantaneous LGD is extremely sensitive to reference values under this processing scheme, which poses substantial challenges to the use of satellite orbits other than pure dynamic orbits for reference value computation in both LGD signal analysis and interpretation.
How to cite: Yan, S., Zingerle, P., Gruber, T., and Pail, R.: Potentials and Deficiencies of GRACE-FO Line-of-Sight Gravity Observations, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-7889, https://doi.org/10.5194/egusphere-egu26-7889, 2026.
Recovering ice mass changes at higher spatial and temporal resolution from GRACE-FO remains challenging when using conventional monthly gravity field solutions. We investigate the capability of GRACE-FO inter-satellite ranging (LRI) observations to resolve ice mass variability. Using the LRI measurements on board GRACE-FO to look at gravity anomalies in the line-of-sight direction is an emerging method for observing large mass changes on sub-monthly timescales. We evaluate the potential of this line-of-sight gravity information to study ice mass change, where signals are dominated by long-term trends and ice stream surges are typically smaller in amplitude than hydrological variations. Using tailored regularisation and complementary altimetry data, we are trying to find and push the limits of GRACE-FO line-of-sight gravity. In this study, we are using Greenland and Iceland during the summer periods of 2019-2022 as a test case to look at both the limits in spatial and temporal resolution.
How to cite: Jenny, B., Jensen, T., and Forsberg, R.: Towards Estimating High-Resolution Ice Mass Changes from GRACE-FO Range Measurements, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-10655, https://doi.org/10.5194/egusphere-egu26-10655, 2026.
One of the applications of satellite gravimetry data from GRACE and GRACE Follow-On (GFO) missions is a comparison with various geophysical models that provide information about mass re-distribution in the Earth system. An example is regional climate models describing the Surface Mass Balance (SMB) of ice sheets and glaciers. Possible goals of such a comparison are model validation, as well as recovery of signals not captured by models. This comparison may be a challenging task because it frequently requires that GRACE-/GFO- based estimates are produced at a small spatial scale and with a high accuracy. These requirements conflict with intrinsic limitations of GRACE/GFO data. Even if random noise is suppressed using dedicated algorithms, the accuracy of the obtained GRACE/GFO-based estimates is inevitably reduced due to signal leakage.
We propose a novel scheme for a comparison of GRACE/GFO-based Spherical Harmonic Coefficients (SHCs) with geophysical models. To mitigate the “internal” signal leakage, we adopt a fully consistent data inversion. This includes, among others, a transformation of geophysical estimates into Spherical Harmonic Coefficients (SHCs). Then, all the sets of SHCs are inverted into the spatial domain using the same data weighting. To mitigate the signal leakage from outside, we estimate mass anomalies over a global set of patches (mascons). To reduce non-uniqueness of the inversion (which may manifest itself, e.g., as Gibbs phenomenon), we exploit available prior knowledge, such as the fact that mass anomalies typically show only a minor variability over the ocean and the accumulation zone of the Greenland Ice Sheet (GrIS). This prior knowledge is introduced in the form of a first-order Tikhonov regularization. To find the optimal regularization parameters, we train the inversion scheme using realistically simulated synthetic data. To capture the geometry of coastlines accurately, we use patches of a relatively small size (about 40x40 km at the latitude of the Greenland’s central part). Since this results in a huge number of unknown parameters, we invert SHCs iteratively, using the Preconditioned Conjugate gradient method.
We apply the proposed scheme to compare seasonal mass anomalies based on GRACE/GFO data and on SMB estimates from the Regional Atmospheric Climate Model RACMO2.3p2. The comparison is limited to the Greenland’s coastal zone, which includes the ablation zone, as well as tundra and isolated ice caps outside it. We split the coastal zone into 12 regions. The linear size of each region is only a few hundred km, i.e., close to the theoretical limit of resolution achievable from GRACE/GFO data. We identify regions where mass anomaly time-series of the two types show a good agreement (< 2 cm RMS in terms of equivalent water heights) and regions where the discrepancies are larger. In most cases, those discrepancies are likely caused by an under- or over-estimation of meltwater runoff, as well as the buffered water storage en route to the ocean, which is sensed by GRACE/GFO, but is not included into SMB models.
How to cite: Ditmar, P., Li, W., Klees, R., Wouters, B., and van den Broeke, M.: Comparison of GRACE(-FO) data with geophysical models at a small spatial scale, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-13864, https://doi.org/10.5194/egusphere-egu26-13864, 2026.
A commonly known limitation in the use of GRACE data is the one-year (July 2017 to May 2018) gap between the end of the GRACE mission and the beginning of the GRACE-FO operation. In this study, we reconstructed total water storage (TWS) at the grid-cell scale using two modeling approaches: a Bias-Aware Machine Learning (ML) model and an autoregressive integrated moving average (ARIMA) model with exogenous variables. Both approaches were applied to CSR mascon GRACE data to reconstruct missing monthly observations. Bias-Aware ML represents a new paradigm of optimal algorithm design, model architecture, and aimed at explicitly detecting, measuring, and mitigating bias in data, models, or outputs.
We applied this approach to the transboundary Bug River Basin (BRB), which spans Poland, Ukraine, and Belarus. An XGBoost ML model was used with multiple groups of high-resolution (0.1°) hydrometeorological variables—precipitation, soil moisture, evapotranspiration, river runoff, and land surface temperature—together with static physiographic variables (elevation, lithology, and land cover) as predictors.
The XGBoost model explains approximately 86% of the variance in GRACE TWS values on unseen test data. Model performance relies strongly on short-term memory, with the TWS rolling average being the most influential predictor. Seasonal variability is well captured; however, the model tends to overestimate TWS in the northern and northwestern regions and underestimate it in the eastern and southeastern areas. Overall performance shows a slight west-to-east decline. Model performance deteriorates for extreme TWS values, indicating limited skill in representing hydrological extremes.
The results indicate that gap filling supported by bias-aware ML substantially outperformed seasonal ARIMA with exogenous variables across the BRB. The correlation coefficient with in situ observations increased from 0.30 to 0.74. We showed that the use of bias-aware ML with engineered predictos, combined with a post-processing stacking framework, provides a significant advantage over traditional extrapolation-based algorithms. We further showed that the trained ML models learned complex relationships between the input datasets and GRACE-derived TWS, resulting in improved performance of the reconstructed GRACE time series. The results of this study are expected to serve as a benchmark for filling data gaps between the GRACE and GRACE-FO missions and for selecting appropriate GRACE solutions for regional hydrological studies.
The study was conducted as part of the project GRANDE-U “Groundwater Resilience Assessment through iNtegrated Data Exploration for Ukraine” (NSF Awards No. 2409395 and 2409396). Vilnius University has received funding from the Research Council of Lithuania (LMTLT), agreement No. S-IMPRESSU-24-3.
How to cite: Solovey, T., Śliwińska-Bronowicz, J., Samalavičius, V., and Stradczuk, A.: Reconstructing GRACE Terrestrial Water Storage Anomalies time series using Bias-Aware Machine Learning, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-1991, https://doi.org/10.5194/egusphere-egu26-1991, 2026.
Time-variable gravity data from the Gravity Recovery and Climate Experiment (GRACE) and GRACE-Follow on (GRACE-FO) satellite missions are widely used in the Earth science community. GRACE/-FO monthly gravity data products contain strong correlated noise and the superposition of various geophysical mass change signals. Therefore, several processing steps are applied to derive user-friendly Level-3/Level-4 data products used for most applications of GRACE/-FO data. These processing steps include the application of de-noising filters and the reduction of signals besides the considered target signal, such as terrestrial water storage. Both steps introduce errors to the data, which finally propagate to the considered application domain: The de-noising step usually does not only suppress noise but also removes parts of the signal. The signal separation step, often performed using physical reduction models, is affected by model errors.
We consider a separation method using machine learning techniques, replacing both the filtering and signal separation steps. The original method was published by Heller-Kaikov et al. in 2026 and showed promising results in a closed-loop simulation setup. Building upon that, we train the neural network-based pattern recognition algorithm on the task of decomposing a sum of time-variable gravity signals and a GRACE-type noise component into the individual components. After training the network on simulated signal and noise components, we test the resulting separation algorithm on real GRACE/-FO Level-2 data. To evaluate the de-noising and signal separation capabilities of our framework, we validate our results against alternative data products such as the GFZ GravIS terrestrial water storage or ice mass change products.
Our results demonstrate how machine learning algorithms can help solve the signal-noise and signal-signal separation problems in spatio-temporal data, therefore representing an alternative to state-of-the-art de-striping filters and reduction model-based signal separation strategies.
Heller-Kaikov, B., Pail, R., Werner, M. (2026): Neural network-based framework for signal separation in spatio-temporal gravity data, Computers & Geosciences, 207. doi: 10.1016/j.cageo.2025.106057
How to cite: Heller-Kaikov, B., Schlaak, M., Pail, R., and Soja, B.: Separation of time-variable gravity signals in GRACE/-FO data with Machine Learning, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-7248, https://doi.org/10.5194/egusphere-egu26-7248, 2026.
Snow Water Equivalent (SWE) is a critical component of the terrestrial water cycle, yet its large-scale variability and sensitivity to climate teleconnections remain poorly constrained due to sparse in situ observations and uncertainties in land surface models. Using monthly GRACE and GRACE-FO observations from 2003–2024, this study investigates the interannual variability of Northern Hemisphere SWE and its relationship with major climate oscillations, including the El Niño–Southern Oscillation (ENSO), the North Atlantic Oscillation (NAO), and the Pacific Decadal Oscillation (PDO). GRACE-derived terrestrial water storage anomalies are disaggregated to estimate SWE variability using a mass-conserving, GRACE-constrained framework over regions north of 34.5°N, corresponding to approximately 65% of the global seasonal snow-covered land area. Empirical Orthogonal Function (EOF) analysis of detrended and deseasonalized SWE anomalies reveals that the first three modes explain approximately 45–60% of total interannual SWE variance. ENSO is significantly correlated with the second and third SWE modes (r = 0.4–0.6, p < 0.05), which together account for 10–25% of regional SWE variance in western North America and parts of Central Asia. ENSO-related SWE anomalies exhibit a clear dipole structure and a lagged response of 1–4 months, with stronger sensitivity during the melt season than the accumulation season. In contrast, NAO-driven modes dominate SWE variability across northern Europe, explaining up to 30% of regional variance. These results demonstrate that large-scale climate teleconnections modulate SWE primarily through persistent precipitation anomalies rather than temperature alone, while ENSO explains a limited but quantifiable fraction of hemispheric-scale snow mass variability.
Keywords: GRACE, Snow water equivalent, ENSO, Climate change, precipitation, snow.
How to cite: Mohasseb, H. A. and Yi, S.: GRACE-Based Assessment of Interannual Snow Water Equivalent Variability and Climate Teleconnections over the Northern Hemisphere., EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-2445, https://doi.org/10.5194/egusphere-egu26-2445, 2026.
The Global Gravity-based Groundwater Product (G3P) reflects observations of global groundwater storage (GWS) variations derived from GRACE/-FO satellite gravimetry. It is calculated from terrestrial water storage (TWS) anomalies by subtracting aggregated and filtered contributions from root-zone soil moisture, glaciers, surface water storage, and snow water equivalent. As such, G3P provides a crucial observational constraint for assessing global groundwater depletion, recharge, and long-term water storage changes related to climate variability and human activities. A central challenge in the analysis of GRACE/-FO-derived water storage time series is the reliable separation of long-term trends, arising from anthropogenic forcing and climate change, from stochastic signals attributable to natural climate variability (“climate noise”) and observational system instabilities. To address this, we introduce a trend analysis framework that uses calibrated parametric time series models to jointly represent trends, seasonal variability, and temporally correlated stochastic processes. By explicitly accounting for short- and long-range memory in the water storage time series, this approach requires minimal assumptions about the underlying physical processes and provides a robust basis for separating long-term trends from stochastic variability using statistical significance testing.
We first validate the framework for TWS by comparing detected trends with previously reported GRACE-based results and by providing consistent and reliable estimates of trend magnitudes and uncertainties. We then apply the framework to derive and analyse trends in GWS variations. Our results show that groundwater storage decrease is the dominant contributor to negative TWS trends in many regions, with Asia (specifically the Middle East, Northern India, Northern China, and South-east Asia) experiencing a decline of about −43 km³ yr⁻¹. At the same time, we reveal previously unobserved trends, including increasing groundwater levels in large parts of Africa (+34 km³ yr⁻¹) and declining trends attributed to droughts in regions such as Southern Africa, Asia, and Eastern Europe. The resulting global budget indicates significant GWS losses of −22 km³ yr⁻¹ and TWS losses of −154 km³ yr⁻¹ (excluding Antarctica and Greenland). Beyond the regional patterns, this study demonstrates how accounting for stochastic memory fundamentally affects trend significance and uncertainty estimates in GRACE/-FO time-variable gravity-field observations.
The proposed framework is scalable and transferable to other Essential Climate Variables, contributing to a more reliable detection of subtle long-term changes in Earth system mass variations.
How to cite: Hohensinn, R., Gou, J., Meyer, U., Boergens, E., Humphrey, V., Dorigo, W., Soja, B., Gruber, A., Eicker, A., Jensen, L., Rast, M., and Güntner, A.: Water storage trends derived from the GRACE/-FO global gravity-based groundwater product (G3P), EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-12360, https://doi.org/10.5194/egusphere-egu26-12360, 2026.
The spurious North-South stripes in gravity field solutions of satellite gravimetry mission such as GRACE and its follow-on (GRACE-FO), are a well known issue. They are thought to be the result of residual non-Gaussian errors, most notably stemming from residual sub-monthly dealiasing model errors, which propagate into the gravity field solutions. The typical pattern is known to be linked to the orbit geometry (e.g. Peidou and Pagiatakis 2020) in combination with the directional sensitivity of the raw observations.
Over the years, various approaches have been developed to reduce these striping patterns as a trade-off against signal attenuation, resulting in varying filtered solutions. One particular type of these approaches stems from using diagonal regularization matrices using approximate or real error-covariance matrices (e.g. Kusche et al 2009, Klees et al 2008, Horvath et al. 2018). These can be done either at the normal equation system level or be formulated as a post-processing filter operator.
In this work, we revisit this regularization principle and explore ways of constraining the East-West and North-South gravity field gradients at given satellite heights.
We show that, in the spherical harmonic domain, the associated regularization matrices resolve to order-block-diagonal matrices with a typical checkerboard pattern separating even and odd degrees.
Furthermore, we compute an empirical degree varying power law for the gradients based on the ESA earth system model (Dobslaw et al 2015). We present the result of testing various regularization strengths and weighing schemes, which are applied to the publicly available normal equation system from ITSG and GFZ. The regularized solutions are compared against conventional filter approaches (DDK filters, Gauss,) in the spatial and spectral domain.
How to cite: Rietbroek, R. and Karimi, S.: A new approach to tackling stripes in gravity field solutions using directional gradient regularization , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-19065, https://doi.org/10.5194/egusphere-egu26-19065, 2026.
The Next Generation Gravity Mission (NGGM) is European Space Agency’s (ESA) next Mission of Opportunity. It aims to extend and improve time series of satellite gravity missions by providing enhanced spatial and temporal resolution time-varying gravity field measurements with reduced uncertainty and latency to address the international user needs as expressed by the International Union of Geodesy and Geophysics (IUGG[1]) and the Global Climate Observing System (GCOS[2]) and demonstrate the critical capabilities for a potential future operational gravity mission.
MAss Change and Geosciences International Constellation (MAGIC) is the European Space Agency (ESA) and National Aeronautics and Space Administration (NASA) jointly developed concept for collaboration on future satellite gravity constellation that addresses the needs of the international user community. MAGIC will consist of the GRACE-C (NASA and German Aerospace Center (DLR)) and NGGM (ESA) staggered deployment of 2 satellite pairs, with progressively improving measurement performance, to form a Bender-type constellation. GRACE-C will continue the successful US-German partnership of GRACE and GRACE-FO, building on important European technologies to ensure continuity and global coverage of observations. NGGM will advance the technology and scientific innovation and will enable the demonstration of applications and operational capabilities for both NGGM and MAGIC, for a panoply of applications critical for climate change monitoring and Earth sciences, e.g. Hydrology, Climate Change, Cryosphere, Oceanography, Solid Earth and Geodesy. NGGM will fly in a lower altitude (~400km), controlled inclined orbit at 70 degrees, with the objective to deliver consistent, quality-assured data products with enhanced high spatial (~150 km) and temporal (sub-weekly) resolutions as well as reduced latency compared to the present state-of-the-art.
This paper provides a status overview of the NGGM implementation, including the on-going B1-B2 bridging phase system and technology pre-development activities. It also presents the scientific perspective of NGGM and MAGIC, detailing their respective science and mission objectives, mission performance metrics, recent algorithmic advancements for NGGM and MAGIC, as well as the anticipated impact on scientific research and applications arising from ESA’s NGGM Phase B1 science studies.
[1] Pail, R., Bingham, R., Braitenberg, C. et al. Science and User Needs for Observing Global Mass Transport to Understand Global Change and to Benefit Society. Surv Geophys 36, 743–772 (2015). https://doi.org/10.1007/s10712-015-9348-9
[2] Terrestrial Water Storage ECV Requirements: The 2022 GCOS ECVs Requirements (GCOS 245)
How to cite: Daras, I., Francois, M., Willemsen, P., Massotti, L., Rousseau, S., Tzeremes, G., and Hernando Aguero, L.: Next Generation Gravity Mission (NGGM) implementation status and scientific outlook, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-17342, https://doi.org/10.5194/egusphere-egu26-17342, 2026.
The SING project aims to evaluate the added value of the NGGM and MAGIC missions for scientific applications and operational services in hydrology, ocean sciences, glaciology, climate sciences, solid earth sciences, and geodesy. Using a closed-loop simulator with a comprehensive description of instrumental and dealiasing errors, synthetic observations of the gravity field have been generated to assess the observability of mass changes occurring in the atmosphere, ocean, hydrosphere, cryosphere, and solid earth for different mission configurations, including GRACE-C (single polar pair), NGGM (single inclined pair), and MAGIC (double pair). Our results indicate significant benefits from the higher spatial and temporal resolution of NGGM and MAGIC, particularly in flood prediction, drought monitoring, and water resource management. These aspects have been explored through dedicated hydrological data assimilation and data-model fusion studies. Additionally, the improved spatial resolution has been shown essential for detecting changes in the Atlantic Meridional Overturning Circulation (AMOC) in the context of climate change. The SING project has been assessing the impact of the NGGM and MAGIC missions on monitoring ice mass changes in mountain glaciers and ice sheets. The greater spatial and temporal resolution of future satellite gravimetry missions have been shown to improve the recovery of the Ocean Heat Content and Earth Energy Imbalance due to better consistency with other ocean monitoring systems such as satellite altimetry. The added value of a second satellite pair has been estimated for monitoring co-seismic and post-seismic processes, as well as improving predictive modeling for geohazards, with a focus on providing timely forecasts that are socially relevant. The project also investigated the impact of the NGGM and MAGIC missions on geodesy by enhancing gravity and geoid models in support of the IHRF realization, its time evolution, and precise orbit determination. The results of the SING project will provide further validation for the NGGM and MAGIC mission concepts and contribute to the preparation of NGGM and MAGIC products into operational services.
How to cite: Pfeffer, J. and the SING consortium: Studying the Impact of the NGGM and MAGIC future satellite gravity missions for scientific applications and operational services, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-18908, https://doi.org/10.5194/egusphere-egu26-18908, 2026.
The technology demonstrator instrument, laser ranging interferometer (LRI), aboard the two-satellite constellation GRACE-FO mission has been highly successful in measuring the changing range between the spacecraft. The phase data measured by the optical electronics of the LRI is filtered by the Laser Ranging Processor (LRP) and transmitted to the onboard computer (OBC), which then beams it to the ground stations.
We will discuss the LRI data processing on-ground for GRACE-FO and the development of technology and data analysis for future gravity missions.
The post-processing, on ground, involves calculating one-way range retrieval, range rate, range acceleration, and the scale factor. It employs various algorithms to detect non-gravitational events in the data, including phase jumps and single-event upsets. The LRI's one-way range sensitivity can be shown to be 1000 times better than that of the conventional microwave ranging instrument (MWI/KBR). This success has led to all future gravity-field retrieval missions to have an LRI-equivalent as their primary ranging instrument.
The NGGM is the first twin-satellite gravity mission by the European Space Agency (ESA), estimated to launch in 2032. The ranging instrument onboard NGGM is called the Laser Tracking Instrument (LTI). All components of this instrument are designed, implemented and tested in Europe.
Our group is primarily involved with developing and testing the engineering model (EM) of the Instrument Control Unit (ICU). This instrument is similar to the LRP of GRACE-FO. The ICU consists of an RTG4 FPGA and a GR740 processor. We developed the software and firmware to enable the ICU to measure the phase from the optical bench in various operating modes and control the laser. The processor within the ICU is responsible for filtering and decimating the phase data and packaging it into ECSS standard PUS telemetry packets. To communicate with the ICU, an onboard computer simulator (OBC-SIM) was developed. This OBC-SIM can send telecommands to and receive telemetry from the ICU over a SpaceWire interface. This telemetry can be recorded and analysed with similar post-processing to the LRI.
All in all, the presentation will provide an overview of the data processing for GRACE-FO and the subsequent activities in the development of the software, OBC-SIM, and post-processing of the data for the ICU EM.
How to cite: Bekal, P., Müller, V., Misfeldt, M., Schiefer, P., Oberschulte, T., and Heinzel, G.: Data Analysis for Laser Ranging from GRACE-FO to NGGM, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-18023, https://doi.org/10.5194/egusphere-egu26-18023, 2026.
The ESA-led Next Generation Gravity Mission, as the successor to the GRACE-FO mission, will use a Laser Tracking Instrument (LTI) as its primary and only inter-satellite ranging instrument, which will be developed entirely in Europe. The Instrument Control Unit (ICU), as one development to replace prior US contributions, is expected to acquire range information through phase readout of the laser interference, control the Optical Bench Electronics, stabilize the laser frequency, and communicate with the Onboard Computer. As a joint venture development with the Laser Interferometer Space Antenna (LISA) at AEI, an improved algorithm for Differential Wave Front (DWS) sensing is implemented, featuring higher robustness due to independent gain settings for ranging and DWS information. In addition, LTI pointing angles of the optical bench are used as a sensor to control satellite attitude, and the Scale-Factor Measurement System is included in the ICU as a major difference to the GRACE-C mission.
Here we present the ICU Engineering Model (ICU EM) design, its most important performance requirements, and first results from the test campaign, which aims to achieve a two times more ambitious ranging noise requirement by means of phase-tracking with a noise below 40nm/rtHz x NSF(f) and DWS of 5nrad/rtHz x NSF. These measurements require a stabilized 80MHz system clock referenced with less than 50psec/rtHz x NSF(f) to a 10MHz ultra stable oscillator of the spacecraft. The laser frequency is stabilized either to a cavity with an absolute laser frequency accuracy below 20 ppb or locking to the incoming laser frequency with 13MHz offset, depending on the satellite's role.
We specifically address the development and features of the FPGA firmware, which comprises, next to the digital signal processing pipelines for phase tracking, steering mirror, and laser control, also house-keeping and diagnostic functionalities. The first results from electrical and optical testing suggest that the ICU will meet the performance requirements and enable uninterrupted range measurements with sub-nanometer resolution, hence, continue the laser ranging dataset that has been initiated with the GRACE-FO mission.
How to cite: Schiefer, P., Bekal, P., Misfeld, M., Müller, V., Oberschulte, T., Sudha, R., Weberpals, M., and Heinzel, G.: Towards a European Instrument Control Unit for the Laser Interferometer aboard NGGM, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-19512, https://doi.org/10.5194/egusphere-egu26-19512, 2026.
Slow fault dislocation and viscoelastic deformation are detected by geodetic observations of earthquakes, but are processes that are largely absent from seismological records because they do not generate seismic waves detectable by conventional seismic networks. Detecting the aseismic component of fault slip is therefore essential for characterizing the complete rupture process and the associated stress drop.
In this study, we invert satellite-observed gravity-field variations to estimate fault dislocation on a fault plane defined by seismological observations. Earthquake-related gravity changes reflect the coseismic dislocation responsible for seismic wave generation, combined with contributions from possible slow fault deformation. Consequently, dislocation values inferred from gravity data in excess of those derived from seismology provide information on aseismic slip.
The 2025 Kamchatka earthquake (moment magnitude Mw=8.8), which occurred on 29 July 2025 in the southern Kamchatka Peninsula at the subduction interface between the Pacific and Okhotsk plates, produced a detectable gravity signal. GRACE-FO observations at monthly resolution show a peak-to-peak amplitude of nearly 20 µGal at the mission’s spatial resolution. Detecting such coseismic signals in GRACE-FO data is challenging due to the relatively high noise level. We show that earthquakes of comparable magnitude observed by future satellite gravity missions, such as the inclined-pair NGGM (Next Generation Gravity Mission) constellation and the MAGIC double-pair configuration (NGGM combined with the GRACE-C follower of GRACE-FO), would be detected with substantially reduced noise and significantly improved inverted dislocation. Moreover smaller sized tectonic events will be observable.
How to cite: Braitenberg, C., Maurizio, G., Javed, M. T., and Panet, I.: Kamchatka 2025 Earthquake fault dislocation from GRACE-FO and sensitivity with future gravity mission MAGIC/NGGM, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-15981, https://doi.org/10.5194/egusphere-egu26-15981, 2026.
The record of satellite gravity missions over more than two decades enables unique insights into global mass transport processes on Earth. Past and current missions, like GRACE and GRACE-FO contribute valuable information for climate research and to Essential Climate Variables (ECV), e.g., terrestrial water storage, sea-level, and ice sheets. To ensure continuous monitoring of these climate variables, GRACE-C is planned to be launched in 2028, followed by Next Generation Gravity Mission (NGGM) in 2032. The combination of NGGM and GRACE-C will provide enhanced spatial and temporal resolution.This study employs closed-loop numerical simulations to evaluate current and future mission concepts, as well as applying different temporal basis functions to optimize the gravity field retrieval for climate applications. The results are based on input models representing global changes over a period of 12 years (ESA ESM) as well as extended timeseries up to 100 years (CMIP6 climate model run from GDFL). The models represent continental hydrology, and cryosphere, while the simulation environment takes instrument errors and background models errors into account. For different mission concepts, namely in-line single-pair missions and a double-pair mission, the recoverability of a time variable mass signal is evaluated with different temporal resolutions and for different processing strategies.In a comparison of the retrieval performance, it is shown that the double pair observations contribute to a reduced noise-level in the time variable gravity field retrieval compared to single pair observations. Less strong impact than the improved observation system, but still visible further improvements can be archived with direct parameterization strategies. Here, spherical harmonic estimates can be improved in the low degrees by taking sub-monthly correlations in the trend estimates into account. Further individual basins, if they have a large signal to noise ratio, can benefit from higher spatial resolution estimates of the long-term trend.
How to cite: Schlaak, M. and Pail, R.: A simulation study on temporally tailored satellite gravity products for future missions , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-4923, https://doi.org/10.5194/egusphere-egu26-4923, 2026.
Satellite gravimetry missions allow to track mass transport on global scales. The main satellite constellations for the gravity recovery are the GRACE and GRACE Follow-On missions. Typically, they provide monthly gravity field solutions which at times is suffering from data gaps. The future MAGIC constellation shall continue the time series and improve especially the spatial sampling with a possible improvement of the temporal sampling to 5 days. For higher temporal resolutions, new mission concepts are required.
The SENSORIS constellation is being developed by the Institute of Aerospace Technology (IAT) of the City University of Applied Sciences Bremen, the Centre of Applied Space Technology and Microgravity (ZARM) of the University of Bremen and is supported by the DLR Institute for Satellite Geodesy and Inertial Sensing, Hanover. The purpose of the constellation is to measure the Earth's gravity field using a NewSpace approach for faster, cheaper and more flexible data acquisition for research, security and resource management. The advantage of SENSORIS lies in the ability to increase the capabilities by adding additional spacecraft at low costs; the more spacecraft make up the constellation, the more frequent data can be generated. This allows an adjustment of the size of the constellation to the prevailing economic conditions while guaranteeing that the areas of interest receive up-to-date data. It is also complementary to the MAGIC constellation as it tackles the prevailing problem of the background modelling by providing direct observations of daily mass variations, though initially at low spatial resolution.
For the initial proof of concept, two 3U CubeSats, which are an evolution of VIBES Pioneer, will be launched, demonstrating the operational functionality. The CubeSats will be equipped with GNSS-receivers allowing the derivation of the gravity field in the high-low satellite-to-satellite tracking mode. For a fully operational constellation, at least 16 spacecraft are expected to be launched allowing to derive gravity field solutions with low spatial (approx. degree 10-15) but with high temporal resolution, e.g. daily or half-daily. We will discuss the expected performance of such a constellation in terms of gravity field recovery. In the future and by implementing a GRACE follow-on-like laser ranging interferometer (LRI), changing to the low-low satellite-to-satellite tracking scheme is possible and, consequently, increasing the spatial resolution, for which the development of compact LRI instruments is required.
How to cite: Weigelt, M., Rohr, J. M., Reeder, J., Koch, A., Rievers, B., Gust, T., Garcia, A., von Stockhausen-Petersen, A., Bleckmann, M., Suttrop, H., Wieting, J., Herold, J., and Gaudissart, G.: SENSORIS – current status and first simulation results, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-18197, https://doi.org/10.5194/egusphere-egu26-18197, 2026.
Next-generation satellite gravity missions such as NGGM and MAGIC are expected to provide unprecedented observations of Earth’s time-variable gravity field, offering transformative opportunities for understanding mass transport processes in the global water cycle, solid Earth, cryosphere, and ocean systems. Fully exploiting the scientific potential of these missions requires an end‑to‑end workflow that ensures methodological consistency from raw sensor data to geophysically meaningful products. Addressing this need, we present a new integrated, open-source scientific platform developed in Python and publicly available on GitHub [1]. The platform consolidates processing steps across multiple levels of gravity field data, enabling researchers to seamlessly transition from Level‑1B observations to high‑level geophysical applications.
The platform is built upon a modular architecture that incorporates four core components.
(1) PyHawk provides a flexible and transparent environment for inverting GRACE/FO and future-mission Level‑1B measurements into time-variable gravity field solutions. It implements state-of-the-art dynamic orbit determination, variational inversion, and regularization strategies, designed to be easily extendable for upcoming mission concepts.
(2) SaGEA enables systematic post‑processing of Level‑2 spherical harmonic solutions, including filtering, destriping, stochastic error characterization, and advanced signal separation techniques to isolate hydrological, cryospheric, and oceanic mass variations.
(3) PyGLDA incorporates these gravity-derived Level‑3 products into a hydrological model through a global sequential data assimilation system capable of handling computational load at high resolution. This component provides improved estimates of terrestrial water storage anomalies and their subcomponents (soil moisture, groundwater, snow), offering new opportunities for hydrological analysis, drought monitoring, and water resource assessment.
(4) SaGEA‑Fluid computes a wide range of geophysical corrections driven by atmospheric, oceanic, hydrological, and cryospheric mass redistributions, including self‑attraction and loading (SAL), geocenter motion, and Earth orientation parameter (EOP) variations. These forward-model products ensure physically consistent comparisons between models and observations.
The integration of these modules into a single platform allows for a coherent and reproducible processing chain spanning mission‑level data to application‑ready geophysical outputs. Initial experiments demonstrate consistent agreement between satellite-derived mass variations and hydrological assimilation results, highlighting the platform’s potential for cross‑domain scientific studies. The system is under active development, with planned extensions including a fully customizable numerical mission simulator to support the design and performance assessment of next‑generation gravity missions. Overall, this platform offers a community-driven, open, and extensible foundation for advancing Earth system studies with current and future satellite gravimetry missions. It aims to enhance transparency, reproducibility, and scientific collaboration in preparation for the upcoming era of high-resolution, high-accuracy gravity field observations.
References
[1] https://github.com/NCSGgroup; https://github.com/AAUGeodesyGroup/PyGLDA
How to cite: Yang, F., Liu, S., Wu, Y., Zhang, W., Retegui-Schiettekatte, L., Schumacher, M., and Forootan, E.: GravityPython: An Open-Source Pipeline for Inversion, Analysis, Assimilation, and Earth System Applications, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-17836, https://doi.org/10.5194/egusphere-egu26-17836, 2026.
Many users of time-variable satellite gravimetry data from the GRACE and GRACE-FO missions employ gridded Level-3 data for various applications in, e.g., hydrology, glaciology, oceanography, and the climate sciences. Operational Level-3 data products are provided, for example, via GravIS (www.gravis.gfz.de) maintained by GFZ based on Level-2 spherical harmonic solutions, or by the three mascon producers JPL, CSR, and GSFC. Users of these products are, however, limited to the processing choices defined by the data providers.
In order to make GRACE/-FO data even more accessible, the open-source Python package geogravL3 enables users to generate Level-3 products from spherical harmonic coefficients using user-defined processing settings. The software supports the generation of domain-specific products for land (terrestrial water storage), oceans (ocean bottom pressure), and the Greenland and Antarctic ice sheets (ice mass change). Implemented processing steps include filtering of spherical harmonic coefficients (Gauss, DDK, and VDK), replacement of low-degree harmonics, and correction for glacial isostatic adjustment (GIA). For land and ocean applications, spherical harmonic coefficients are transformed into surface mass distributions using spherical harmonic synthesis under the thin-layer assumption. Ice mass changes over Greenland and Antarctica are estimated using a sensitivity-kernel approach, which is conceptually similar to a Level-2-based mascon method.
The geogravL3 package is openly available via GitLab (https://git.gfz.de/grace_l3/geogravl3) and can be installed through PyPI or conda-forge.
How to cite: Boergens, E., Charly, A., Dahle, C., Dill, R., Dobslaw, H., Horwath, M., Rabe, D., Scheffler, D., Shihora, L., and Wilms, J.: geogravL3 – An Open-Source Python Package for Level-3 Gravity Data Processing, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-3940, https://doi.org/10.5194/egusphere-egu26-3940, 2026.
The International Centre for Global Earth Models (ICGEM) is one of the five services coordinated by the International Gravity Field Service (IGFS) of the International Association of Geodesy. The ICGEM Service provides improved, quality assured, and well documented global gravity field models (GGMs) and related products to the international geosciences user community. In the framework of the currently running SAMDAT (Service and Archive for Mass Distribution And mass Transport data) project, we are going to expand the ICGEM service with additional model types, new datasets and representations that are citable, enriched with metadata, and provided in a sustainable and freely accessible research data infrastructure. Consequently, SAMDAT will improve the service performance and accommodate increasing user demands by enabling a broader range of geoscientific applications, thus strengthening its contribution to interdisciplinary research.
In this conference contribution, we present results of the recent SAMDAT activities of the ICGEM Service: (i) We introduced two new gravitational functionals, namely complete Bouguer and isostatic gravity anomalies in the interactive calculation service, (ii) We implemented a new service where altimetry derived gravity data and related products are published, and a new calculation service for Mean Dynamic Topography is provided, (iii) For the calculation service, we investigated the truncation error introduced by cutting global gravity field models in the spherical harmonic domain and compared it against cutting in the ellipsoidal harmonic domain to reduce the outcome error, (iv) For a sustainable data infrastructure, we developed an editor for metadata submission according to the new metadata scheme of GGMs and related products, (v) Finally, we implemented a new website designed to meet current scientific standards while remaining accessible to both scientific and non-scientific users.
ICGEM is a demand driven service and with the achievements of the SAMDAT project, it will translate into a modern, sustainable channel that serves the geoscientific community at a wider scale.
How to cite: Uz, M., Reissland, S., Niedermaier, J., Torkhov, A., Ince, E. S., Förste, C., Elger, K., and Gruber, T.: ICGEM Service Developments: New functionals, altimetry, new data representations and infrastructure, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-14094, https://doi.org/10.5194/egusphere-egu26-14094, 2026.
The ESA Swarm constellation’s dual‑frequency GPS observations provide high-low satellite‑to‑satellite tracking (hl‑SST) with sufficient fidelity to estimate monthly global gravity field variations at low degree and order (spatial half‑wavelength ≳1,500 km; SH degree ≈12–13). Since late 2013, these solutions have formed an uninterrupted time series that bridges the gap between GRACE and GRACE-FO, complementing the short interruptions in their records. Independent gravity inversions - Celestial Mechanics, Decorrelated Acceleration Approach, Short‑Arcs, and Improved Energy‑Balance - are generated by a consortium comprising AIUB (Switzerland), ASU (Czechia), TU Delft (the Netherlands), TU Graz (Austria), and Ohio State University (USA). The solutions are combined at the level of normal equations using Variance Component Estimation (COST‑G), yielding consolidated monthly products that are largely unbiased with respect to any single strategy.
We publish the models quarterly via ESA’s Swarm Data Access and ICGEM, ensuring traceable, community-ready datasets for geophysical applications. Cross-validation against GRACE/GRACE‑FO demonstrates that Swarm recovers large-scale hydrological and cryospheric mass changes, with typical basin-scale agreement characterised by temporal correlations around ~0.75 and trend consistency within ~1 cm/yr in Equivalent Water Height (EWH). Advances in kinematic orbits processing since early 2020 have tightened the nominal EWH accuracy from ~4 cm to ~3 cm. A persistent feature of the Swarm-derived fields is elevated noise over deep-ocean regions, which is 30–50% larger than over land.
These hl-SST models are estimated independently of ll-SST data, enabling the validation of those gravity field solutions, providing continuity during past and prospective gaps (including the GRACE-FO to GRACE-C/MAGIC transition), and supporting low-latency monitoring of large-scale mass transport. The robust Swarm platform’s health and refined GPS processing during periods of heightened solar activity ensure the sustained delivery of high-quality monthly time-variable gravity fields.
How to cite: Teixeira da Encarnacao, J., Arnold, D., Bezdek, A., Dahle, C., Guo, J., van den IJssel, J., Jaeggi, A., Klokocnik, J., Krauss, S., Mayer-Guerr, T., Meyer, U., Sebera, J., Shum, C., Visser, P., and Zhang, Y.: A decade of temporal gravity observed by the ESA Swarm satellites, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-19792, https://doi.org/10.5194/egusphere-egu26-19792, 2026.
In June 2025, the RL02.1 GRACE and GRACE-FO time-series of monthly gravity fields, combined from the monthly solutions of 11 (GRACE), resp. 8 (GRACE-FO) different Analysis Centers (ACs) by the Combination Service for Time-variable Gravity fields (COST-G) has been published. Compared to the COST-G RL02 combination, presented at EGU 2025, the contributions of HUST and Tongji to the GRACE combination have been updated, with only minor impact on the combination. Meanwhile, the Tongji GRACE-FO solutions have passed the COST-G quality control and are included in the operational GRACE-FO combination, starting from July 2025. One month later, a new AIUB GRACE-FO RL03 became available, replacing AIUB-RL02 in the GRACE-FO combination from August 2025 on. Both changes led to significant noise reductions of the combined GRACE-FO gravity fields. To ensure consistency of the atmosphere and ocean dealiasing (AOD) models applied in the GRACE-FO data analysis, the new time-series, which already use AOD1B-RL07, have to be transformed back to AOD1B-RL06 prior to combination. A new COST-G release, including a switch to AOD1B-RL07, is foreseen, as soon as the GRACE-FO SDS RL07 time-series are available. Due to the realistic noise models applied by an increasing number of ACs, a combination on the normal equation instead of solution level may become feasible for this future COST-G release.
How to cite: Meyer, U., Jaeggi, A., Lasser, M., Dahle, C., Flechtner, F., Oehlinger, F., Mayer-Guerr, T., Lemoine, J.-M., Koch, I., Zhou, H., Chen, Q., and Feng, W.: COST-G: Status and new developments, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-5369, https://doi.org/10.5194/egusphere-egu26-5369, 2026.
Since mid-2018, the satellite pair of the gravimetry satellite mission called Gravity Recovery And Climate Experiment Follow-on (GRACE-FO) has been providing observations to determine the time-variable Earth’s gravity field with high temporal and spatial resolution. However, some of the low-degree Earth’s gravity field coefficients can better be determined by using Satellite Laser Ranging (SLR) observations to spherical geodetic satellites. Consequently, individual Earth’s gravity field coefficients may be replaced in the GRACE-FO products, or alternatively, the parameter estimation of the Earth’s gravity field can be performed using multi-technique combinations.
The Variance Component Estimation (VCE) is a well-established and widely adopted technique in satellite geodesy. As an example, VCE is used for combining observations from different geodetic space techniques or even to or from individual satellites to estimate precise geodetic parameters, e.g., to derive an international terrestrial reference frame.
In this study, applications of the VCE method, implemented in a development version of the Bernese GNSS software, are assessed for improved and more automated gravity field parameter determination. The primary focus is on the use of the VCE method for data quality assessments and to strengthen the orbit parametrization. In GRACE-FO data processing, reduced-dynamic orbits, where the usual orbit parameter set is extended with regular Piece-Wise Accelerations (PCAs), are used. In case of SLR data, the strong correlation between the gravity field coefficients and some of the dynamic orbit parameters prevents certain orbit parameters from being estimated but to compensate for this, stochastic pulses are set up. Both PCAs and the stochastic pulses need to be constrained in a way, that they can account for mis-modelings but preserve the sensitivity to the gravity field signal. It is shown that these constraints can be computed directly from VCE rather than determined empirically.
How to cite: Geisser, L., Lasser, M., Meyer, U., Arnold, D., and Jäggi, A.: Applications of Variance Component Estimation in GRACE-FO and SLR Spherical Geodetic Satellite Data Processing for Gravity Field Determination, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-17243, https://doi.org/10.5194/egusphere-egu26-17243, 2026.
More than 24 years of time-variable gravity observations from the GRACE and GRACE-FO missions have greatly advanced our quantitative understanding of mass redistribution within the Earth system, including terrestrial hydrology, ocean mass variability, cryospheric change, solid Earth processes, and climate-driven signals. The GRACE and GRACE-FO datasets are currently undergoing RL07 reprocessing at the Center for Space Research (CSR) to further reduce noise and systematic errors, improve solution consistency, and establish a uniform long-term archival record that supports multi-decadal mass change analyses across the GRACE and GRACE Follow-On missions.
The RL07 reprocessing includes a complete reanalysis of Level-1B observations, updates to reference frames and background geophysical models, and a series of improvements to orbit determination and gravity field recovery. Key enhancements include improved treatment of GNSS and K-band ranging observations, refined instrument error calibration, and updated processing and stochastic modeling strategies. In parallel, a new generation of CSR mascon solutions is produced using methodologies fully consistent with the RL07 framework. This paper describes the major upgrades implemented in the CSR RL07 reprocessing of GRACE and GRACE-FO data and assesses their impact on solution stability, noise characteristics, and the fidelity of time-variable gravity signals. Relative to CSR RL06, the RL07 solutions exhibit more than a 35% reduction in noise, quantified as root-mean-square (RMS) variability over the oceans, which translates directly into a substantial improvement in the realized spatial resolution of GRACE and GRACE-FO mass change estimates.
How to cite: Save, H., Zhang, C., Tapley, B., Bettadpur, S., Childress, N., Tamisiea, M., Nagel, P., Pie, N., Krichman, B., Jacob, G., Kang, Z., Poole, S., and Ries, J.: GRACE/GRACE-FO RL07 Reprocessing at CSR: Algorithmic Updates, Performance Improvements and Results, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-16161, https://doi.org/10.5194/egusphere-egu26-16161, 2026.
The Gravity Recovery and Climate Experiment Follow-On (GRACE-FO) mission represents the state-of-the-art architecture for satellite gravimetry missions. GRACE-FO consists of a pair of twin low Earth orbiting (LEO) satellites flying in the same orbit with onboard tracking instruments. These instruments can be separated into two categories: low-low satellite-to-satellite tracking (ll-SST) and high-low satellite-to-satellite tracking (hl-SST). The ll-SST instruments consist of the K-band ranging (KBR) and laser ranging interferometer (LRI) which produce precise measurements of the range between the GRACE-FO satellites. The hl-SST refers to the onboard GNSS receivers used for satellite positioning, timing, and long-wavelength gravity field information.
In this presentation, we present initial results from a novel approach to processing GRACE-FO GPS observations. We use a digital filter to numerically differentiate the GPS phase observations to process phase-rate observations instead of processing code and phase range observations. These phase-rate observations are then used for dynamic precise orbit determination (POD) and gravity field estimation in conjunction with the ll-SST observations. We start with a review of previously presented simulation results that motivate this work. This is followed by a detailed description of the data processing, filtering, and observation modeling derivation. We conclude with the initial results from using the GPS phase-rate observations for POD and gravity field estimation. Future work includes detailed error budgeting for this observable as it pertains to POD and gravity recovery. We anticipate these results to be useful in the architecture and science data algorithms for next generation gravimetry missions.
How to cite: Saadat, N. and Bettadpur, S.: Orbit Determination and Gravity Recovery from GRACE-FO GPS Phase-Rate Data: Initial Results from a Novel Processing Scheme using Numerically Differentiated GPS Data, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-4057, https://doi.org/10.5194/egusphere-egu26-4057, 2026.
When determining monthly gravity fields, as commonly done for the operational ITSG solutions, an adequate stochastic model is crucial. By setting up a realistic stochastic model within the least-squares adjustment, the observations are weighted properly and consequently an optimal solution with reasonable formal errors can be obtained.
GRACE-FO carries two independent inter-satellite ranging systems: the K/Ka-band ranging instrument (KBR) and the laser ranging interferometer (LRI). The LRI, originally conceived as a technology demonstrator, exhibits significantly higher measurement precision and is particularly beneficial for the determination of high-degree spherical harmonic coefficients. However, the combined use of both ranging instruments enables the determination of the best achievable gravity field, provided that the stochastic modeling is properly taken into account.
The non-linearity of the functional model relating the observations to the estimated gravity field parameters entails that forward-modeled observations are subtracted from the actual measurements. Consequently, the reduced observations are contaminated not only by the noise of the ranging observables, but also by noise contributions from the accelerometer, the star camera, and uncertainties in the background models. This noise component is inherent to all observation types and induces correlations between the LRI and KBR measurements. To ensure proper stochastic modeling, this cross-correlation must be considered.
The stochastic modeling presented here is realized by determining each amplitude of the power spectrum via a frequency-wise variance component estimation. This procedure involves estimating the covariance function for each observation type and down-weighting flawed observation data. In addition, the common noise component can be separated from the instrument-specific noise of the KBR and LRI. The resulting formal errors of the gravity field solutions derived from the combined use of both ranging systems show good agreement with the empirical estimates, which is particularly important for subsequent combinations with other data types. This stochastic modeling approach was therefore also applied in the determination of the static gravity field model GOCO2025s, in which monthly GRACE-FO solutions were combined with GRACE, GOCE, kinematic orbit, and satellite laser ranging data.
How to cite: Öhlinger, F. and Mayer-Gürr, T.: Stochastic Modeling in GRACE-FO Gravity Field Estimation Using Two Types of Satellite-to-Satellite Tracking Observations, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-11198, https://doi.org/10.5194/egusphere-egu26-11198, 2026.
The GRACE/GRACE-FO mission has monitored monthly variations of Earth's gravity field for more than two decades. One source of error is attitude errors, that propagate to inter-satellite range observations through the antenna centre offset correction. This error is proportional to the nominal angle deviation. For GRACE-FO, the third additional camera on-board and the gyroscope made attitude errors negligible. However, with current coarse pointing mode to increase mission lifetime, the propagated attitude errors are enlarged. This work incorporates full covariances for the antenna centre correction to the stochastic model. For this purpose, in-house level-1A attitude data processing is conducted, including sensor fusion from the three star cameras and gyroscope data along with variance component estimation. The impact on the post-fit residuals and the quality of the gravity field recovered are analysed for the solutions of TU Graz Institute of Geodesy.
How to cite: Valles Valverde, G. and Mayer-Guerr, T.: Analysis of attitude noise for ITSG GRACE-FO processing, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-17554, https://doi.org/10.5194/egusphere-egu26-17554, 2026.
The use of background model information in GRACE/-FO gravity data processing is essential to mitigate temporal aliasing errors arising from mass variations in the Earth System that occur on time periods shorter than one month. Currently, tidal and non-tidal mass variations in atmosphere and ocean are considered in the official GRACE/-FO monthly gravity field products provided by JPL, CSR and GFZ. However, also sub-monthly continental water storage variations might propagate as aliasing errors into the monthly solutions.
In this contribution, we investigate the impact of introducing hydrological background model data into GRACE processing on the quality of the resulting monthly solutions. For the hydrological mass signal, we use sub-monthly terrestrial water storage output from the open-source global hydrological model OS LISFLOOD (Jensen et al., 2025) forced with meteorological data from the ERA5 atmospheric reanalysis, which we include into the ITSG-Grace2018 (Kvas et al., 2019) processing scheme. Furthermore, we assess if the additional consideration of background model uncertainty information is advantageous for the quality of monthly solutions. To derive consistent hydrological error information, we perform a small ensemble of three OS LISFLOOD runs under different atmospheric forcings, from which we infer both error time series as well as a variance-covariance matrix that are also tested in the ITSG-Grace2018 processing scheme.
How to cite: Jensen, L., Öhlinger, F., Dill, R., Mayer-Gürr, T., Shihora, L., and Dobslaw, H.: Impact of hydrological de-aliasing on monthly GRACE gravity field solutions, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-9891, https://doi.org/10.5194/egusphere-egu26-9891, 2026.
For more than two decades, CNES has been developing and distributing Level-2 time-variable gravity models for the international scientific community, notably through the International Center for Global Gravity Field Models (ICGEM) and the International Combination Service for Time-variable Gravity Fields (COST-G). Building on this expertise, in the framework of the National Data Hub FormaTerre of the Research Infrastructure Data Terra, the SAGSA (Service of Activities for Space Gravimetry and Applications) project, funded by CNES and led by Magellium, aims to establish a Space Gravimetry Data and Services Center. This center will be dedicated to monitoring temporal and spatial variations in Earth’s gravity field from GRACE and GRACE-FO observations, and to providing advanced gravity products for the scientific community. Within SAGSA, Magellium, in close collaboration with CNES, is responsible for the operational production of CNES Level-2 nominal and unconstrained gravity models, distributed both as spherical harmonics and gridded products. These models form the foundation for Level-3 ensemble models, generated by combining CNES solutions with those from other processing centers, thereby offering datasets tailored to the needs of the hydrology, oceanography, solid-earth deformations, and glaciology communities. Such models support investigations of large-scale geodynamic processes, including the global water cycle, continental ice mass loss, and sea-level rise. Furthermore, Level-4 products are being developed by integrating space gravimetry with complementary Earth observation data, such as satellite altimetry, to monitor essential climate variables including ocean heat content and Earth’s energy imbalance. To ensure long-term accessibility and usability, SAGSA will also implement a dedicated data and service infrastructure, guaranteeing the systematic identification, distribution, and documentation of all CNES gravity products, from Level-1B to Level-4.
How to cite: Boughanemi, A., Ablain, M., Blazquez, A., Boniface, C., Bouih, M., Bruinsma, S., Couhert, A., Dibarboure, G., Dorandeu, J., Garnier, J., Gaugain, S., Lavergne, E., Lecomte, H., Lemoine, J.-M., Meyssignac, B., Pellereau, E., Perosanz, F., Pfeffer, J., Reinquin, F., and Zawadski, L.: Developing Advanced Gravity Products and Services at CNES through the SAGSA Project, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-17857, https://doi.org/10.5194/egusphere-egu26-17857, 2026.
Since 2002, GRACE and GRACE-FO have provided pioneering observations of temporal variations in Earth’s gravity field, revealing an integrated measure of mass redistribution processes within the Earth system that supports a wide range of climate-related geophysical studies. Motivated by the need for consistent, high-resolution representations of mass redistribution, we present an innovative global mass concentration (mascon) solution based on an analytical point-mass formulation. The solution relates inter-satellite K-band ranging measurements observed by GRACE and GRACE-FO missions to surface mass changes and is implemented within the open-source software GROOPS.
The resulting mascon solution employs a globally distributed set of irregularly shaped mass elements with approximately equal areas. The spatial design of the mascons is guided by physical boundary information, such as coastlines, with the aim of reducing signal leakage. Each mascon is constructed from an underlying high-resolution equal-area grid, allowing the estimation to be performed at the fine-grid level while enforcing internal consistency within individual mascons through appropriate parameter constraints. To address the ill-posed nature of mascon-based gravity field inversion, we apply a regularization strategy independent of external prior information to stabilize the solution and mitigate temporal aliasing effects in the recovered mass change signals.
The performance of the TUM mascon solution is assessed using a comprehensive set of validation approaches. Comparisons with contemporary mascon solutions from other analysis centers, as well as with other independent data sets, are conducted to assess the consistency of mass change signals and relative noise characteristics at both global and regional scales, with regional analyses focusing on selected hydrological basins and arid regions.
How to cite: Wu, H., Schiller, S., Schlaak, M., and Pail, R.: TUM GRACE/GRACE-FO Mascon Solution: A Novel Parameter Framework, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-6372, https://doi.org/10.5194/egusphere-egu26-6372, 2026.
Satellite gravity missions provide a unique capability to observe mass transport processes within the Earth system. Within the framework of the ESA MPEF study, this contribution investigates alternative mascon-based gravity field parameterizations with the objective of developing a robust TUM mascon solution. Rather than treating regularization as a purely numerical post-processing step, it is considered an integral component of an optimized processing chain that jointly accounts for grid design, parameterization choice, and regularization strength. An automated simulation environment based on a GRACE-like mission geometry is employed to systematically analyze the interaction between grid design, mascon parameterization, and regularization strength on global and regional scales. This framework enables consistent gravity field recovery against reference models as well as targeted regional investigations, allowing the impact of different processing choices on solution stability and signal preservation to be assessed.
The results demonstrate how the different modeling choices interact and reveal which combinations of parameters the system is most sensitive to. In particular, while the type of basis function has a relatively minor effect, the interplay between grid complexity and the strength and implementation of regularization emerges as a key driver of solution stability and accuracy. The analysis shows that appropriate combinations enable robust global solutions with high signal recovery, while simultaneously enhancing the representation of regional mass variations. Deviations with respect to reference models, expressed in Equivalent Water Height, allow systematic assessment of remaining errors and their dependence on specific processing choices. Changes in the processing chain highlight which aspects of the solution are particularly sensitive, demonstrating both favorable and unfavorable strategies. Overall, the study tries to clarify the mechanisms through which parameter interactions shape the behavior of TUM-Mascon solutions within the ESA MPEF framework, offering guidance for optimized gravity field recovery strategies.
How to cite: Schiller, S., Wu, H., Schlaak, M., and Pail, R.: Interdependencies in the Mascon Processing Chain for Gravity Field Recovery, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-3353, https://doi.org/10.5194/egusphere-egu26-3353, 2026.
During on-orbit operations, star trackers (STRs) are vulnerable to thermal deformations caused by the space environment, which can lead to shifts in the interboresight angles (IBA), severely affecting attitude measurement accuracy and degrading the quality of gravity satellite observation data. To address the shortcomings of traditional attitude calibration methods that overlook thermal deformation effects, this study presents an on-orbit thermal deformation attitude reconstruction method based on multi-STR joint processing. By analyzing the correlation between STR noise characteristics and temperature, a three-axis noise distribution weighting matrix is developed, and a linear model is established for temperature-induced deviations in the interboresight angle. The weighted least-squares method is employed to combine multi-STR attitude data and compute the optimal attitude quaternion, enabling high-precision angular velocity reconstruction. Experimental results demonstrate that after thermal deformation correction, the average interboresight angle deviation of the STR is reduced to below 8.87 arcseconds, with a standard deviation (std) of less than 0.008 arcseconds. The three-axis angular velocity noise level decreases by approximately two orders of magnitude, with a total std improvement of 0.28 orders of magnitude. The accuracy of the Y-axis improves by a factor of about 6. Furthermore, the logarithmic quaternion Hermite hypersurface interpolation method ensures the continuity and smoothness of the attitude data. This study provides reliable technical support for high-precision attitude determination in satellite gravity missions, significantly enhancing angular velocity reconstruction accuracy, with consistent performance across all axes.
How to cite: Wu, Y., Hu, D., Zhang, Y., and Pang, Q.: On-Orbit Thermal Deformation Impact on Attitude Offset and Angular Velocity Reconstruction: Insights From Multisatellite Tracker Data Combination and Temperature Correction, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-2386, https://doi.org/10.5194/egusphere-egu26-2386, 2026.
The Gravity Recovery And Climate Experiment (GRACE) and its successor, the GRACE Follow-On (GRACE-FO), observe temporal variations in the Earth’s gravity field caused by mass redistribution. The primary observation is range and range rate (Level-1), which are processed to reach global maps of mass change (Level-3). Various background models are used in Level-1B processing; however, these are not perfect, and their uncertainties affect the gravity field solutions. Among the time-variable gravity signals, high-frequency atmospheric and non-tidal ocean variations, as well as ocean tides, are generally undersampled, resulting in short-period signals aliasing onto longer periods in the recovered gravity field, which becomes a major error component. In this study, we analyzed the impact of various ocean tide models on gravity field recovery in both spatial and spectral domains. Furthermore, we evaluated the differences in the ocean tide models in terms of tidal amplitudes and gravity potential, which is computed along the footprints of GRACE-A at the orbital pass-time scale. The derived inter-model differences from orbital simulations are used to compute uncertainty information that can be utilized later in the stochastic modeling of the gravity field. The results indicate that significant differences persist among ocean tide models in accurately resolving tidal signals, especially at higher degrees. Furthermore, we find that modelling aliasing error at monthly mean scale is providing a conservative estimate compared to modelling errors along the orbit while considering Ocean tides at the satellite pass-time. The error in the global geoid height ranges ±1.2 mm when considering orbit pass-time information, compared to ±0.12 for the case where we compute errors at monthly mean scale. The major differences were observed over polar regions, ice sheets, shallow waters, and coastal areas. Hence, we expect that modelling ocean tide de-aliasing errors at orbit pass-time scales instead of at monthly scales could reduce GRACE(-FO) uncertainties.
How to cite: v a, C. and Vishwakarma, B. D.: Understanding the errors in ocean tide models for improved GRACE gravity field recovery, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-412, https://doi.org/10.5194/egusphere-egu26-412, 2026.
The S2 tidal aliasing is a known issue and demands special attention when working with monthly mass variation data from GRACE and GRACE Follow-On. As the temporal resolution of the gravity field time series improves, the likelihood of tidal aliasing also increases, provided that the amplitude of these signals is significant. The period at which aliasing occurs depends on the specific frequency of the ocean tide component and the sampling characteristics of the satellites. In this contribution, we compute the aliasing periods for a set of less-studied ocean tide constituents for which, to a certain extent, no ocean tide solutions exist. We compute equivalent water height maps for the daily solutions from TU Graz, daily swath mascon solutions over the oceans from CSR, and the 10-day solutions from CNES/GRGS. Subsequently, we conduct a harmonic analysis to uncover aliased ocean tide signals in these alternative submonthly gravity field models, and discuss implications of ocean tide model errors for NGGM/MAGIC.
How to cite: Koch, I. and Flury, J.: Aliased ocean tide signal in submonthly gravity field products and implications for NGGM/MAGIC, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-21294, https://doi.org/10.5194/egusphere-egu26-21294, 2026.
The ESA Earth System Model (ESA ESM) provides a synthetic data set of the time-variable global gravity field that includes realistic mass variations in atmosphere, oceans, terrestrial water storage, continental ice sheets, and the solid Earth on a wide set of spatial and temporal frequencies. For more than 10 years already, it is widely applied as a source model in end-to-end simulation studies for future gravity missions, but has been also utilized to study novel gravity observing concepts on the ground. For those purposes, the ESM needs to include a wide range of signals even at very small spatial scales which might not yet have been reliably observed by any active satellite mission.
In this contribution, we present the details of the newly released version 3.0 of the ESA ESM as well as the first simulation studies based on the new model. The changes to the pervious ESA ESM version 2 include the utilization of a small ensemble of co- and post-seismic earthquake signals, an updated GIA model, additional mass balance signals from previously not considered Arctic glaciers, sub-monthly surface-mass balance changes and a more realistic representation of ice sheet dynamics. Extreme hydrometeorological events as well as climate-driven and anthropogenic impacts on continental water storage are represented through an update of the hydrological component. Additionally, the ESM separately includes ocean bottom pressure variations along the western slope of the Atlantic, representing variations in the meridional overturning circulation as a critically important component of the interactively coupled global climate system. ESA ESM 3.0 is available with 6-hour resolution from January 2007 until December 2020. It is augmented with synthetic error time series for atmosphere and ocean as well as hydrology to facilitate stochastical modelling of residual background model errors.
How to cite: Shihora, L., Schlaak, M., Klemann, V., Jensen, L., Dill, R., Tanaka, Y., Sasgen, I., Wouters, B., Han, S.-C., Sauber-Rosenberg, J., Braitenberg, C., Javed, M. T., Maurizio, G., Lecomte, H., and Dobslaw, H.: The updated ESA Earth System Model for Future Gravity Mission Simulation Studies: ESA ESM 3.0, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-9665, https://doi.org/10.5194/egusphere-egu26-9665, 2026.
Since 2002, GRACE and GRACE-FO have recorded valuable data on changes in the Earth mass distribution, indicating melting ice caps, a rising sea level and redistributions of groundwater. The continuation of this data collection is of high interest for climate research. Future gravity missions, such as NGGM, GRACE-C and TianQin-2 are currently under development and will use a Laser Ranging Instrument (LRI) to measure the main observable – distance variations between two satellites which are orbiting the Earth in a separation of 200 km.
To support studies for future gravity missions, we developed a novel LRI Level 1A data simulator that uses orbit files containing the satellite positions and velocities, as well as attitude datasets providing satellite orientations. Under consideration of physical principles and instrument characteristics of laser interferometers in space, the simulator derives LRI phase measurements and LRI inter-satellite pointing angles in a format similar to GRACE-FO level1a files. The data is further processed to level1b using the same software used for the processing of GRACE-FO LRI flight data. The simulator is already capable of deriving realistic LRI ranging data and led to improvements in our GRACE-FO LRI level1b processing chain.
In this poster presentation we provide an overview of which effects are already considered in the simulator, explain the data validation strategy, and present a tone-error analyses from different contributors.
How to cite: Müller, L., Müller, V., Misfeldt, M., and Heinzel, G.: Simulations of Laser Ranging Instrument Data in Future Gravity Missions, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-11538, https://doi.org/10.5194/egusphere-egu26-11538, 2026.
The space-wise approach is a methodology for processing data from satellite gravity missions with the aim of estimating the Earth gravity field. The core idea is to exploit the spatial variability and correlation of the gravity field, also considering its local inhomogeneities, to enhance the data filtering. This method fits very well with the computation of regional solutions, namely local spherical grids of some gravity field functionals using only (or mainly) the satellite observations collected over the study area. Of course, if this local estimation is systematically performed for many areas covering a whole reference sphere, a set of spherical harmonic coefficients can also be retrieved by patching the estimated local grids all together and then performing a straightforward spherical harmonic analysis.
Future satellite gravity missions, like NGGM/MAGIC or other ones based on quantum technology, are promising to provide data that will improve the accuracy and the spatial-temporal resolution of the current investigations on the time-variable part of the Earth gravity field. In the ESA-MPEF (Mission Performance Evaluation Framework) project, the space-wise approach is proposed as one of the possible strategies for the retrieval of both global and regional gravity field solutions from NGGM/MAGIC data. In this work, the processing scheme of the space-wise approach is outlined and some simulation results are shown. In particular, the focus of the simulated regional solutions is on the estimation of the total water storage anomaly for some hydrological basins of interest.
How to cite: Reguzzoni, M., Rossi, L., Eslami, A. M., and Migliaccio, F.: The space-wise approach for the computation of global and local gravity field solutions from NGGM/MAGIC simulated data, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-17543, https://doi.org/10.5194/egusphere-egu26-17543, 2026.
The NGGM-MAGIC missions are envisaged to advance the applications of satellite based gravity field information for tracking changes in the mass distribution and transport in ground water storages, ice sheets and oceans. The GOCE User Toolbox GUT was originally developed for the utilisation and analysis of GOCE products to support applications in Geodesy, Oceanography and Solid Earth Physics. GUT consists of a series of advanced computer routines that carry out the required computations without requiring expert knowledge of geodesy. Hence, with its advanced computer routines for handling the gravity field information rigorously, GUT may support the future gravity missions such as NGGM and MAGIC in developing Level-2 and Level-3 products.
Focusing on MAGIC mission goals on unprecedented recovery of ocean bottom pressures, a more flexible processing of the gravity field information may become essential. Furthermore, an integration of ocean bottom pressure changes with changes in the geostrophic surface currents may advance the analyses further. GUT facilitates such a flexible processing and, in addition, contains tools for the assessment of static gravity field models. In addition to computing Essential Geodetic Variable products associated with the Earth gravity field such as regional geoid models, free-air gravity anomalies, gravity disturbances, deflections of the vertical, GUT also facilitates computation of the dynamic ocean topography models and the associated geostrophic surface currents. This poster presents relevant examples of its functionality. Finally, workflows are proposed for GUT to analyse mass transport time series.
How to cite: Knudsen, P., Daras, I., Ambrozio, A., Restano, M., and Benveniste, J.: GUT supporting the future NGGM-MAGIC mission, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-4981, https://doi.org/10.5194/egusphere-egu26-4981, 2026.
In this study, we revisit Kaula’s orbit perturbation theory to evaluate the capability of satellite orbits to sense degree-1 gravitational signatures. We explicitly derive the Kaula-based expressions for the degree-1 potential terms and compute the corresponding inclination F1mp(i), and eccentricity functions G1mp(e), providing—for the first time—complete tables for degree-1.
As a study case, we applied this to the ESA's Genesis mission set to be launched in 2029. Genesis will be the first in orbit geodetic observatory carrying onboard the 4 co-located geodetic techniques (GNSS, SLR, DORIS and VLBI).
The dependence on orbital inclination of the expressions for the degree-1 potential coefficients V10 and V11 is examined. Our analysis shows that V10, associated with the geocenter’s z-component, scales with sin i, implying that polar orbits maximize sensitivity to vertical geocenter variations, while equatorial orbits remain largely insensitive to them. Conversely, the two-term structure of V11 enhances the detectability of the geocenter’s x- and y-components for equatorial or near-equatorial orbits, with reduced but non-negligible sensitivity in polar configurations.
This work demonstrates how Kaula’s theory can guide the design of future gravimetry missions by identifying orbital parameters that optimize degree-1 recovery, thereby improving geocenter estimation and strengthening the link between satellite gravimetry and terrestrial reference frame realization.
How to cite: López Rosson, G., Folgueira, M., Dehant, V., and Karatekin, Ö.: Kaula’s degree-1 gravitational potential, geocenter and application to Genesis mission., EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-20550, https://doi.org/10.5194/egusphere-egu26-20550, 2026.
We explore an alternative approach to future gravity missions: the potential of mega-constellations, such as Starlink, OneWeb, Telesat, etc., for time-variable gravity field recovery. These constellations consist of numerous satellites in various planes and across a range of elevation and inclination bands, including very low Earth orbit (VLEO). As a result, they provide increased spatial coverage, lower revisit times, and alternate geometries (near-polar or inclined). This enables better sampling with minimal spatio-temporal aliasing and lower latency, potentially providing daily or hourly solutions of the time-variable gravity field.
A reduced-scale closed-loop simulation approach, implemented using an in-house, under-development research tool in Julia, is used to simulate multiple scenarios. High-low satellite-to-satellite tracking (hl-sst) is used for gravity recovery and will later be modified to include inter-satellite communication links (ISL) for inter-satellite ranging. Such constellations are designed for high-speed internet connectivity or for earth observation, not specifically for gravity recovery. Therefore, understanding the impact of sensor noise characteristics is critical, evaluating the trade-off between an increased number of satellites but with slightly lower instrumentation quality (compared to a dedicated mission). In addition to this, other challenges include (i) investigating new approaches for time-aware parameterisation schemes, and (ii) exploring the idea of so-called “opportunistic mapping”, i.e. to map events like tsunamis or earthquakes as and when they occur. Future research will address these questions in more detail.
How to cite: Mhamane, A. and Sneeuw, N.: Viability of mega-constellations as an alternative to dedicated future gravity missions, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-18735, https://doi.org/10.5194/egusphere-egu26-18735, 2026.
GRACE/GRACE-FO data are commonly provided in the form of spherical harmonic solutions (SHCs) or mass concentration (mascon) solutions. Compared with SHCs, mascon solutions usually require simpler post-processing, exhibit higher signal-to-noise ratios, suffer less from leakage errors, and provide improved effective spatial representation; therefore, they are widely used in interdisciplinary studies such as hydrology and glaciology.
The mascon method approximates continuous surface mass changes by representing them as a series of discrete units with internally homogeneous mass, based on locally defined basis functions. Consequently, the size, shape, and positioning of these mascons have a significant impact on solution accuracy. In certain regions characterized by strong spatiotemporal heterogeneity of surface mass changes, such as the North China Plain, the Tibetan Plateau, and Greenland, differences among mascon solutions largely arise from variations in their parameterization and regularization strategies.
In this study, we use the unconstrained ITSG-Grace2018/ITSG-Grace operational monthly SHCs covering the period from April 2002 to December 2022, with a maximum degree and order of 96, incorporating the full noise covariance matrices. Based on the open-source ANGELS-Mascon software, variable-shaped mascons are customized, and weighted least-squares inversions with generalized Tikhonov regularization are performed over the Tibetan Plateau. By constructing various combinations of parameterization and regularization, we are comparing the performance of different mascon solutions in signal extraction, noise suppression, and spatial representation, with the aim of identifying a statistically optimal solution for the Tibetan Plateau.
This contribution mainly presents the processing workflow and preliminary analyses. A systematic comparison of different configurations is ongoing, and further analytical findings will be presented at the conference.
How to cite: Liu, S. and Pan, Y.: Estimating Terrestrial Water Storage Changes over the Tibetan Plateau from GRACE/GRACE-FO Monthly Solutions Using a Variable-shaped Mascon Method: Processing Workflow and Preliminary Analysis, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-18465, https://doi.org/10.5194/egusphere-egu26-18465, 2026.
As a leading indicator of global climate change, contemporary global mean sea level (GMSL) change is mainly driven by thermosteric (thermal expansion) and barystatic (ocean mass increase) contributions. GMSL change has been continuously measured by satellite altimetry since 1993, while thermosteric sea level change can be inferred from in-situ hydrographic measurements dating back to the 1970s. However, direct observations of barystatic sea level change were generally lacking until the launch of the Gravity Recovery and Climate Experiment (GRACE) in 2002. In the absence of GRACE, barystatic sea level estimation relies primarily on the so-called mass budget approach by summing individual surface mass change estimates (e.g. ice sheets, glaciers, and terrestrial water storage) obtained from different remote sensing or geophysical modelling techniques, providing an indirect observation due to the lack of global constraints. In this study, we use low-degree gravity fields obtained from satellite laser ranging (SLR), a traditional space geodetic technique over decades, to directly estimate barystatic sea level changes since 1993. To this end, we effectively address the issues of signal leakage and missing geocenter motion for SLR gravity fields using the forward modelling technique. Our SLR-based barystatic sea level estimates allow the direct observation-based assessment of the GMSL budget over the satellite altimetry era, and also provide an independent dataset for cross-validation and gap-filling between GRACE and its successor GRACE-FO. Using reprocessed altimetry data from NASA's Goddard Space Flight Center and updated thermosteric sea level ensembles, we reconcile the GMSL rise budget from 1993 to 2022. Our results show that the sum of thermosteric and SLR-based barystatic contributions (3.16 ± 0.64 mm/yr) agrees well with the altimetry-observed GMSL rate (3.22 ± 0.28 mm/yr), suggesting that the GMSL budget can be closed within uncertainties over the last three decades. Nevertheless, we observe increased budget residuals when using different altimetry datasets, especially in recent years, highlighting the ongoing challenges in accurately observing GMSL change and robustly closing the GMSL budget.
How to cite: Nie, Y., Chen, J., Xu, G., and Löcher, A.: Observing Long-term Barystatic Sea Level Change with Satellite Gravimetry, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-16071, https://doi.org/10.5194/egusphere-egu26-16071, 2026.
From both GRACE missions we get time variable information from the Earth’s gravity field since 2002. The monthly time series obtained from science centers can be represented as a surface water layer. By sampling the oceans we obtain a mass against time signal which is the barystatic component of the sea level rise signal. Hereby we need to correct for the effect of glacial isostatic adjustment which is also observed by the GRACE missions. The GIA correction determines for a part the implementation of the geocenter correction that is used during the GRACE data processing. Depending on the processing choice to represent ocean mass and the GIA correction that is required we find barystatic sea level rates varying between 1.9 and 2.4 mm/yr whereby we remark that the uncertainty is larger than previously expected.
How to cite: Schrama, E. and van der Wal, W.: Glacial isostatic adjustment modelling affecting global ocean mass estimates, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-9739, https://doi.org/10.5194/egusphere-egu26-9739, 2026.
