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 23 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 C and approaching the Critical Design Review in May 2025. Prospects for achieving gap-free continuity between GRACE-FO and GRACE-C will be presented.
How to cite: Flechtner, F., Wiese, D., Landerer, F., Gross, M., 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 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-6720, https://doi.org/10.5194/egusphere-egu25-6720, 2025.
The RL07 series of GRACE gravity field products generated at JPL is a reprocessing of updated Level 1 data for the entire mission duration. Some aspects of the Level 2 processing have been updated from the RL06 series, in an effort to improve solution quality and uncertainty quantification.
Level 2 processing improvements include the co-estimation and use of full observation covariance matrices for both GPS and inter-satellite ranging KBR observations, and the use of an updated background field (GOCO06s) and other models. The updates ensure consistency and continuity with the GRACE-FO data record, which is processed using the same standards.
We present time series and analysis of these new fields, and compare them to the previously released JPL RL06 series of gravity field solutions, showing higher fidelity in formal errors, and improvements in solution noise levels.
How to cite: Ellmer, M., Wiese, D., Kuang, D., Landerer, F., Blackwooed, C., McCullough, C., Yuan, D.-N., Fahnestock, E., and Peidou, A.: GRACE and GRACE-FO Level 2 RL07 data processing at JPL, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-7105, https://doi.org/10.5194/egusphere-egu25-7105, 2025.
The central hypothesis of the Research Unit (RU) New Refined Observations of Climate Change from Spaceborne Gravity Missions (NEROGRAV), funded for the second three-year phase by the German Research Foundation DFG, reads: only by concurrently improving and better understanding of sensor data, background models, and processing strategies of satellite gravimetry, the resolution, accuracy, and long-term consistency of mass transport series from satellite gravimetry can be significantly increased; and only in that case, the potential of future technological sensor developments can be fully exploited.
In continuation of the first RU phase, the individual project Improved Stochastic Modeling in GRACE/GRACE-FO Real Data Processing (ISTORE-2) aims to complete the optimized stochastic modeling for GRACE and GRACE-FO gravity field determination. This includes stochastic modeling of the non-tidal atmospheric and oceanic dealiasing (AOD) models which were recently implemented into the GRACE/GRACE-FO Level-2 processing at the GFZ Helmholtz Centre for Geosciences. In this context, we co-estimate AOD model coefficients using AOD error variance-covariance matrices in terms of constraint matrices.
This presentation provides an overview of the main processing steps together with AOD error analyses. In particular, we investigate the impact of taking into account not only static but also temporal correlations of the AOD models with different maximum temporal correlation lengths. Results are presented in terms of gravity field solutions in the spectral and spatial domain.
How to cite: Murböck, M., Dahle, C., Panafidina, N., Hauk, M., Wilms, J., Neumayer, K. H., and Flechtner, F.: Stochastic modeling of non-tidal atmospheric and oceanic dealiasing models for GFZ GRACE/GRACE-FO Level-2 processing, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-16562, https://doi.org/10.5194/egusphere-egu25-16562, 2025.
We present an innovative global mass concentration (mascon) solution, "GCL-Mascon2024", derived using the short-arc approach to estimate spatially enhanced mass variations on the Earth's surface. This monthly solution is based on K-/Ka-band ranging (KBR) satellite-to-satellite tracking data from the Gravity Recovery and Climate Experiment (GRACE) mission. Compared to contemporary GRACE mascon solution computations, we introduce three key advancements: (1) a frequency-dependent data weighting strategy to mitigate low-frequency noise in the satellite observations; (2) a variable-shaped mascon geometry incorporating physical constraints such as coastlines and river basin boundaries to reduce signal leakage and better capture temporal gravity variations; and (3) a regularization scheme integrating climate factors and cryospheric elevation models to address the ill-posed nature of mascon estimation. Temporal signals from GCL-Mascon2024 show 7% to 20% lower residuals over continental regions compared to Release-06 (RL06) mascon solutions from GSFC, CSR, and JPL. For various river basins, GCL-Mascon2024 solutions reduce random noise over non-humid river basins by 37% relative to contemporary mascon products. In desert regions, residual analyses after removing climatological components reveal that GCL-Mascon2024 and JPL RL06 solutions are roughly equivalent in accuracy, with a 28% noise reduction compared to GSFC and CSR RL06 solutions. This study underscores the potential of GCL-Mascon2024 to enhance the accuracy of gravity field solutions, offering valuable insights into global mass variations, which is of importance for various geoscience applications.
How to cite: Yan, Z., Ran, J., and Ditmar, P.: Computation of a global mascon solution from satellite gravimetry data, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-5502, https://doi.org/10.5194/egusphere-egu25-5502, 2025.
Global models of the Earth's static gravity field are crucial for geophysical and geodetic applications such as oceanography, tectonics, and global reference systems. The combined global gravity field model GOCO2025 is the latest release of the GOCO* series and is derived solely from satellite observations. Data from the dedicated satellite gravimetry missions GRACE, GRACE-FO, and GOCE as well as satellite laser ranging observations and kinematic orbits of geodetic satellites are used to determine a static gravity field together with a regularized trend, an annual and a semi-annual oscillation. Starting with GRACE in 2002 the time series spans more than 20 years of data from satellite missions with complementary observation principles, which allows for the determination of a high-accuracy gravity field model with the best possible spatial resolution.
The unique instrumentation on GRACE-FO with two independent inter-satellite ranging systems (laser ranging interferometer (LRI) and K/Ka band ranging instrument (KBR)) that operate simultaneously allows for the determination of a stochastic model taking the cross-correlation between the instruments into account by using variance component estimation. This modeling approach results in formal errors of the spherical harmonic coefficients that align well with empirical estimates which is crucial for a combination with other data types and uncertainty propagation. The significantly higher measurement precision of the LRI compared to the KBR is especially beneficial for determining high-degree spherical harmonics. Proper stochastic modeling of all the input data results in realistic accuracy information for the derived combined gravity field solution (represented by a full variance-covariance matrix) that is crucial for further combination with, for example, terrestrial gravity data.
Consistent and up-to-date background models are used in the combination process of the different satellite data sets. A combined ocean tide model (GOT5.6 + FES2022 + TIME22) and additional corrections to this model, estimated over the entire GRACE/GRACE-FO time series, are employed and uncertainty information of the Atmosphere and Ocean De-Aliasing Level-1B product (AOD1BRL07) is incorporated in the estimation of short time gravity variations within the least-squares adjustment.
How to cite: Öhlinger, F., Mayer-Gürr, T., Krauss, S., Dumitraschkewitz, P., Strasser, A., Süsser-Rechberger, B., and Tieber-Hubmann, C.: Towards a new release of the combined global gravity field model GOCO: Preliminary results, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-5676, https://doi.org/10.5194/egusphere-egu25-5676, 2025.
Some of the most prominent anomalies and open questions concerning the measurements of the ultrasensitive accelerometers on both GRACE FO spacecraft are related to the activation of attitude thrusters. As a consequence, measurements around thruster activations are replaced by modeled data for the GFO1 accelerometer, while the complete measurements are replaced by modeled or hybrid data for GFO2. Motivated by this unsatisfactory situation, we present results of a detailed study on the characterization of the accelerometer response to thruster impulses, for both the GFO1 and GFO2 instruments. The study describes the impulse response in angular accelerations (for the first time), in linear accelerations as well as in the six electrode control voltages of each instrument. For GFO1, we find a realistic impulse response for some thruster pairs. For other pairs, parts of the impulse response are obscured by switch effects. For GFO2, we see similar features as for GFO1, which are, however, superimposed by heavy jumps and drifts that are triggered by the activation. We demonstrate how the stacking of measurements from many events allows to distinguish relevant details in the impulse response and their changes over time. We expect that the results will help to constrain the sources of the anomalies and lead to a better understanding of the motion and control of the accelerometer test masses.
How to cite: Flury, J., Koch, I., and Frye, M.: Towards understanding the measurements of the GRACE FO electrostatic accelerometers, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-10128, https://doi.org/10.5194/egusphere-egu25-10128, 2025.
To investigate the influence of K-Band microwave ranging (KBR) and Laser Ranging Interferometer (LRI) inter-satellite range-rates from the GRACE-FO mission on the recovery of gravity fields, we explores two distinct methods for accelerometer scale estimation, namely diagonal matrix parameterization and full matrix parameterization. Integrating both KBR and LRI data from GRACE-FO into gravity field recovery, we have derived six new time series of monthly gravity field solutions based on two different accelerometer calibration approaches, entitled KBRLRI_Com (incorporating both KBR and LRI data), KBR_Only (using pure KBR data), LRI_Only (solely utilizing LRI data) truncate to degree and order 60 over the period from January 2019 to June 2022. Analyses of KBRLRI_Com, KBR_Only, and LRI_Only reveal the following findings: (1) LRI demonstrates significant advantages over KBR in both diagonal and full scale matrix scenarios, across the time and frequency domains, which shows lower root mean square (RMS) values of the post-fit residuals in the time domain and substantially lower noise at higher frequencies; (2) the comparison between KBRLRI_Com, KBR_Only, and LRI_Only in terms of geoid degree error suggests that KBRLRI_Com agrees well with KBR_Only and LRI_Only at the low degrees (below degree 30), while effectively reducing the high-frequency noise, especially when the diagonal scale matrices are employed; the benefit of KBRLRI_Com solution is mainly attributed to the enhanced quantity of ranging observations. (3) by analyzing the signal and noise over the globe, ocean, Australian continent, and Amazon and Ganges river basins, we find that KBRLRI_Com is highly consistent with KBR_Only and LRI_Only in terms of spatial signals, while KBRLRI_Com exhibits less spatial noise; when employing diagonal and full matrices, the noise of gravity field solutions derived by incorporating LRI data is mitigated by 8.8% and 3.9% over the global ocean compared to KBR_Only, as well as 7.6% and 3.2% in the Australian continent; especially in the diagonal matrix case, the incorporation of LRI measurements for calculating monthly gravity fields results in a more pronounced decrease of spatial noise. (4) in the oceanic region, KBR_Only and LRI_Only have average RMS values of 11.3 cm and 11.6 cm in diagonal matrices, respectively, and 10.2cm and 11.6cm in the full matrix, indicating a generally comparable level of accuracy between the two models.
How to cite: Shen, Z., Chen, Q., Nie, Y., Shen, Y., and Zhang, X.: Contribution Analysis of the Addition of Laser Ranging Interferometry on GRACE-FO Gravity Field Estimation under Different Accelerometer Calibration Schemes, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-2488, https://doi.org/10.5194/egusphere-egu25-2488, 2025.
Gravity Recovery and Climate Experiment Follow-on (GRACE-FO) is a gravity field retrieval mission consisting of two identical satellites orbiting the Earth since 2018. Each satellite is equipped with a Global Positioning System (GPS) receiver, a microwave ranging system, and an accelerometer (ACC) to measure non-gravitational accelerations. The data from these instruments, alongside the estimations of gravitational force models, are used to determine the satellites' orbits. Soon after launching, one of the satellite’s ACC degraded, and its data was replaced with ACC data transplant, a synthetic data derived from simulations and the other twin satellite’s ACC data. The default data used for orbit determination of GRACE-FO satellites includes Clouds and Earth's Radiant Energy Systems (CERES) climatology for ACC data transplant and Vienna Mapping Function 3 (VMF3) for tropospheric error correction in GPS observation processing. In this study, we propose a novel approach that uses the Open Integrated Forecasting System (OpenIFS) weather model to account for both ACC transplant and tropospheric delay correction, and in the end, assessed the accuracy of GRACE-FO satellites’ orbits. Orbit determination for GPS satellites was conducted with tropospheric slant delays derived from OpenIFS, using data from 256 stations. Then, the precise orbits of GRACE-FO satellites were estimated using the GPS precise orbits as well as the gravitational and non-gravitational forces acting on the satellites. The ACC transplant was performed by the Technical University of Graz, using the OpenIFS-derived simulated non-gravitational accelerations. This method demonstrates an overall 4 cm improvement in orbit accuracy compared to the traditional method, as it offers a more realistic ACC simulation by explaining the rapid changes of atmosphere affecting the GRACE-FO orbit. OpenIFS provides a greater temporal resolution compared to VMF3 and compensates for the asymmetric atmosphere; thus, the GPS orbit is more precise. The largest accuracy improvement occurred in the along-track direction. This is likely due to a more accurate representation of the radiative effects caused by the satellite entering and exiting Earth's shadow, which typically has the most significant effect on along-track accelerations and, consequently, on the satellite's orbit in this direction.
How to cite: Motlaghzadeh, S., Öhlinger, F., Navarro Trastoy, A., Mayer-Gürr, T., and Järvinen, H.: Enhancing GRACE-FO Orbit Accuracy Using OpenIFS Weather Model through Accelerometer Transplant and Tropospheric Delay Correction, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-3947, https://doi.org/10.5194/egusphere-egu25-3947, 2025.
Dual-frequency GNSS data from onboard Precise Orbit Determination (POD) antennas has emerged as a promising tool for investigating the time-variable components of Earth's gravity field. Over the past two decades, POD antennas onboard Low Earth Orbit (LEO) satellites have significantly advanced the study of the long-wavelength components of Earth's gravity field. CubeSats, a commonly used class of nanosatellites, now support a wide range of geodetic and non-geodetic applications while maintaining minimal costs, mass, and power requirements. In this context, the Spire CubeSats constellation, comprising over 100 CubeSats, offers potential contributions to the study of Earth’s long-wavelength gravity field components. This study uses precise orbit solutions of Spire GNSS-RO CubeSats, determined via the raw observation approach, to derive Earth's gravity field solutions using the short-arc approach for 2020. While this technique has been previously applied to scientific LEO satellite missions, this marks its first application to commercial CubeSats. Monthly gravity field solutions are calculated for each Flight Module (FM) using consistent parametrization. On average, geoid height differences between the individual gravity field solutions and the GOCO06s model are within ±2 cm. The individual Spire gravity solutions from each FM are further combined using the Variance Component Estimation (VCE) approach at the normal equation (NEQ) level. The quality of both individual and combined Spire GNSS-RO-based monthly gravity field solutions is compared with the ITSG-GRACE gravity field model.
How to cite: Shafiei, P. and Tabibi, S.: Can the Spire GNSS-RO CubeSats Constellation Observe Earth's Gravity Field?, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-6797, https://doi.org/10.5194/egusphere-egu25-6797, 2025.
Agriculture is vital in the Indian economy as it contributes approximately 17 percent to the total Gross Domestic Product (GDP). Wells and tubewells supply more than 61 percent of India's net irrigated land. The rapidly expanding population, increasing the demand for drinking, irrigation purposes, and industrial applications, leads to over-exploitation of groundwater and a rapid decline in groundwater levels. Due to the apparent relevance of groundwater, it is necessary to monitor it continuously. Monitoring the dynamics of groundwater as a valuable natural resource is difficult, whereas insufficient and uneven observation wells are a problem. Therefore, groundwater fluctuation for time and space is considered for planning for the sustainable management of water resources. The present study assesses the terrestrial water storage (TWS) changes across the region of India using Gravity Recovery and Climate Experiment (GRACE) measurements. By obtaining information on soil moisture and surface water, it is possible to derive groundwater storage changes using TWS anomalies. Groundwater storage anomalies are calculated for the entire Indian region from GRACE TWS data using surface water and soil moisture data simulated by the Global Land Data Assimilation System (GLDAS) model. GRACE data is a valuable tool for assessing regional groundwater storage anomalies. The study found that the negative GWS anomalies are associated with drought, and positive anomalies are associated with flooding events. Also the regionalization of GRACE data for modeling GW using in situ measurements, as precipitation & observed GW data. The comparisons of GWS anomalies with monthly groundwater levels and correlation with the rainfall data from the IMD (2003-2015) indicated that reasonable GWS estimates using the GRACE satellite followed the observed pattern closely, showing the potential for the GRACE mission for groundwater monitoring.
Keywords: Groundwater, GRACE, Land surface model, Groundwater anomalies, GLDAS, Soil Moisture.
How to cite: Soni, A., Narasimhan, B., and Srinivasan, V.: Assessing Groundwater Storage Anomalies using GRACE Measurements: Implications for Sustainable Water Resource Management , EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-11627, https://doi.org/10.5194/egusphere-egu25-11627, 2025.
The temporal gaps in the GRACE and GRACE-FO satellite missions present significant challenges for analyzing Terrestrial Water Storage (TWS) anomalies. This study employs Convolutional-Long Short-Term Memory (CNN-LSTM) neural networks to bridge these gaps, enabling effective drought characterization in major Indian river basins. This approach integrates GRACE-TWS data with meteorological and climatic factors such as precipitation, temperature, runoff, evapotranspiration, and vegetation to generate reconstructed TWS anomalies. The reconstructed groundwater storage anomalies (GWSA) were validated using 4,431 in-situ observation wells, with Pearson’s correlation coefficient (PR) and Normalized Root Mean Square Error (NRMSE) as metrics. Non-perennial river basins like the Mahanadi, Godavari, and Krishna exhibited the best validation results (PR = 0.6–0.86; NRMSE = 0.1–0.2) compared to the perennial basins such as Ganga, Brahmaputra, and Indus demonstrated relatively weaker validation performance (PR = 0.2–0.7; NRMSE = 0.1–0.5). Further, the reconstructed GRACE-GWS helped in identifying new drought events alongside previously documented occurrences, corroborating findings from existing literature. Notably, new hydrological droughts were detected during the gap period between GRACE and GRACE-FO (2017–2018) in the Krishna, Cauvery, and Pennar basins, influencing drought characteristics such as severity and frequency. The gap period droughts are of D0 to D2 category based on United States Drought Monitor (USDM), and occurrences can be justified by decline of NE monsoon. Overall, the reconstructed TWS dataset provided continuous data, particularly for the gap periods, significantly enhancing the identification and analysis of drought occurrences.
How to cite: Gangumalla, S. R., Dutta, S., and Yadav, M.: Reconstructing GRACE-Terrestrial Water Storage Anomalies Using CNN-LSTM Neural Networks for Effective Drought Characterization in Major Indian River Basins, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-6356, https://doi.org/10.5194/egusphere-egu25-6356, 2025.
Fourteen months post the Ukrainian-Russian war outbreak, the Kakhovka Dam collapsed, leading to weeks of catastrophic flooding. Yet, scant details exist regarding the reservoir draining process. By using a new technique for processing gravimetric satellite orbital observations, this study succeeded in recovering continuous changes in reservoir mass with a temporal resolution of 2–5 days. By integrating these variations with satellite imagery and altimetry data into a hydrodynamic model, we derived the effective width and length of the breach and the subsequent 30-day evolution of the reservoir discharge. Our model reveals that the initial volumetric flow rate is (5.7±0.8)×104 m3/s, approximately 28 times the average flow of the Dnipro River. After 30 days, the water level in the reservoir had dropped by 12.6±1.1 m and its water volume was almost completely depleted by 20.4±1.4 km3. In addition, this event provides a rare opportunity to examine the discharge coefficient—a key modelling parameter—of giant reservoirs, which we find to be 0.8–1.0, significantly larger than the ~0.6 value previously measured in the laboratory, indicating that this parameter may be related to the reservoir scale. This study demonstrates a paradigm of utilizing multiple remote sensing techniques to address observational challenges posed by extreme hydrological events.
How to cite: Yi, S., Li, H., Han, S.-C., Nico, S., Yuan, C., Song, C., Yeo, I.-Y., and McCullough, C. M.: Quantification of the flood discharge following the 2023 Kakhovka Dam breach using satellite remote sensing, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-15017, https://doi.org/10.5194/egusphere-egu25-15017, 2025.
We propose an enhanced Slepian method to estimate mass variations of the Greenland Ice Sheet (GrIS) using GRACE monthly spherical harmonic coefficient (SHC) solutions. This approach incorporates the full error covariance matrices of the monthly SHC solutions and employs a novel regularization matrix constructed based on the satellite altimeter data. The monthly Slepian coefficients are estimated through a least-squares inversion process and subsequently converted into monthly GrIS mass variations. The mass balance (MB), derived from surface mass balance (SMB) and ice discharge data, was utilized to determine the statistically optimal parameter range for the improved Slepian method. Using these optimized parameters, we estimated mass anomalies over six individual drainage systems and the entire GrIS. The method demonstrated its highest performance at the monthly scale, achieving reductions in discrepancies between the improved Slepian solutions and MB by 36% to 71%, depending on the drainage system, compared to the original Slepian approach. Additionally, we evaluated discrepancies between mass anomalies derived from three Mascon RL06 solutions (JPL, CSR, GSFC) and MB. The results indicate that the improved Slepian method exhibits comparable performance to Mascon products, further validating its efficacy in GrIS mass variation estimation.
How to cite: Gong, Z., Ran, J., and Yan, Z.: Recovery of Greenland Ice Sheet mass variation from GRACE using improved Slepian function, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-15188, https://doi.org/10.5194/egusphere-egu25-15188, 2025.
This study is concerned with the total rate of mass change in the oceans as seen by the GRACE and GRACE-FO missions between Mar-2002 extending to beyond 2023 into the GRACE-FO observation window. We use the same monthly source data in the form of level-2 spherical harmonic coefficients and find that the selected glacial isostatic adjustment models, ocean mask definitions, and other de-aliasing corrections have a significant effect on the outcome of the barystatic ocean mass rates. In addition to the ICE6G models, and GIA models by Caron and Ivins we also implement GIA models derived from a 3D model forced by ICE-7G ice history. In the end we find barystatic ocean mass rates of change varying between 1.5 to 2.4 mm/yr. The relevance of this result is that the mass component of the sea level change has a larger uncertainty than that we earlier expected. Our conclusion is that it is more difficult to close the sea level budget which involves ocean volume estimates from satellite altimetry, density estimates from Argo profiling float data and the mass component of sea level changes observed by satellite gravimetry.
How to cite: Schrama, E. and van der Wal, W.: Global ocean mass estimates from GRACE and GRACE-FO, evolution and error analysis., EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-5998, https://doi.org/10.5194/egusphere-egu25-5998, 2025.
This study aims to provide valuable scientific insights into various estimation techniques for Geocenter Motion (GCM) from the perspectives of signal analysis and seasonal variation driving factors, thereby enhancing GRACE users' understanding and application of GCM. Initially, it utilizes the Satellite Laser Ranging (SLR) technique with the network shift approach to estimate over 30 years of weekly GCM time series from 1994 to 2024. Subsequently, we employ two approaches to estimate three types of monthly GCM time series spanning more than 20 years from 2002 to 2023: combining GRACE data with an Ocean Bottom Pressure model (GRACE-OBP approach), the Fingerprint Approach (FPA), and the Fingerprint Approach with satellite altimetry data (FPA-SA, up to 2022). The former is referred to as SLR-based GCM estimates, while the latter, based on GRACE Earth gravity field models, is termed GRACE-based GCM estimates. Furthermore, this study pioneers the use of Multichannel Singular Spectrum Analysis (MSSA) for GCM analysis to unveil GRACE-based estimation techniques, especially focusing on the latest GRACE-based GCM estimates from the GRACE-OBP and FPA/FPA-SA approaches. MSSA is used to explore how variations in terrestrial water storage (TWS) and atmosphere-ocean (AO) drive GCM and contribute to seasonal variations through the analysis of correlations and lags between GCM and seasonal driving factors. The results indicate that the 160-day periodic signal detected in GRACE-based GCM estimates, linked to half the GRACE draconitic period, originates from systematic errors in higher-degree spherical harmonic coefficients of the Earth gravity field models, but is absent in SLR-based GCM estimates. Additionally, the study provides the first geophysical explanation linking the 120-day signal in GCM to global precipitation changes.
How to cite: Yu, H., Zhang, Y., and Sun, Y.: Study of GRACE-based Estimation Techniques and Seasonal Drivers of Geocenter Motion Using Multichannel Singular Spectrum Analysis, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-16044, https://doi.org/10.5194/egusphere-egu25-16044, 2025.
Unconstrained monthly gravity field solutions of the Gravity Recovery and Climate Experiment (GRACE) and GRACE Follow-On (GRACE-FO) are predominantly influenced by correlated and high-frequency noise. To mitigate the effect of this noise, this paper proposes a signal-to-noise ratio (SNR) filter (SF) that incorporates the spectral characteristics of a priori monthly gravity field signals and varying observation conditions throughout the entire GRACE period. The performance of the SF filter was evaluated through a comparative analysis with the DDK filter and a combination filter of Gaussian and P4M6 (Gauss+P4M6). Compared to DDK3 and Gauss+P4M6 filters, the SF filter exhibits an improved SNR in mass change estimation under observation conditions characterized by poor data quality, repeat ground track, and normal observation periods. In global scale analysis, SF filtering exhibits a noise reduction of 51% and 81%, while retaining stronger amplitude and trend signals than DDK3 and Gauss+P4M6 filtering. Especially in surrounding regions such as the Greenland, Central Africa, and Amazon River Basin, higher SNR is achieved by the proposed SF filtering method. In small-scale regions like Greenland Sub Basins and other river basins worldwide, mass changes estimated using SF filtering demonstrate a better agreement with those from CSR Mascon solutions or GLDAS models. For extended analysis, the SF filter was further applied to GRACE-FO monthly solutions including CSR RL06.2, ITSG-Grace_op, and COST-G Grace-FO RL02, consistently achieving improved SNR in mass change estimation with respect to the other two filters.
How to cite: Xuan, J., Chen, Q., Zhang, X., and Shen, Y.: A Signal-to-Noise Ratio Filter by Incorporating Spectral Characteristics of Temporal Gravity Field Signals and Varying GRACE Observation Conditions, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-2442, https://doi.org/10.5194/egusphere-egu25-2442, 2025.
The mass change maps derived from GRACE spherical harmonic data come with inherent striping noise, which needs to be filtered during post-processing. Filtering of data leads to signal attenuation and leakage. Several leakage correction methods are available to restore the filtered signal, majorly based on hydrological models or data-driven approaches. In the data-driven correction approach, the primary focus is to account for attenuation and leakage without the aid of external hydrological models. The data-driven methods either use a scaling approach in which the filtered values are scaled after applying a leakage correction, or they use a deviation approach in which the filtered values are corrected by a deviation term and a leakage term. This study concerns the derivation of the deviation term. In deriving the deviation term, the choice of the extent of the catchment average and the deviation field has an impact on the final correction terms. If the deviation term is taken as a global field, then a scaling term appears in addition to the deviation term. Our preliminary investigation shows that there are significant differences between deviation-only and deviation-cum-scaling approaches. We perform our investigation over the GRDC basins as well as the HydroSHEDS level 5 dataset.
How to cite: Komali, B. N. R. and Devaraju, B.: Revisiting the data-driven deviation approach for leakage correction in GRACE data processing, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-15578, https://doi.org/10.5194/egusphere-egu25-15578, 2025.
Ocean bottom pressure (pb) variations from high-resolution climate model simulations under
the CMIP6 (Coupled Model Intercomparison Project Phase 6) HighResMIP protocol are a
potentially useful input for future gravity mission simulation studies, but the overall signal content
and accuracy of these pb estimates has hitherto not been assessed. Here we compute monthly
pb fields from five CMIP6 HighResMIP models at1/4° grid spacing over both historical and future
time spans and compare these data, in terms of temporal variance, against observation-based
pb estimates from a 1/4° downscaled GRACE (Gravity Recovery and Climate Experiment)
product and 23 bottom pressure recorders, mostly in the Pacific. The model results are
qualitatively and quantitatively similar to the GRACE-based pb estimates, featuring—aside
from eddy imprints—elevated amplitudes on continental shelves and in major abyssal plains of
the Southern Ocean. Modeled pb variance in these regions is ~10–80% higher and thus
overestimated relative to GRACE, whereas underestimation (~30%) prevails in more quiescent
deep-ocean regions. Comparisons with the bottom pressure recorders tend to confirm this
picture. We also form variance ratios of detrended pb signals over 2030–2049 under a high-
emission scenario relative to a baseline period of 1980–1999 for three selected models and find
evidence for a statistically significant strengthening of future pb variance by 30–50% across
the Arctic and in eddy-rich regions of the South Atlantic. Together, our results suggest that pb
estimates from CMIP6 HighResMIP models can inform satellite gravimetry simulations and that
climate-driven changes in pb variance should be considered in such efforts.
How to cite: Liu, L., Schindelegger, M., Börger, L., and Gou, J.: Are ocean bottom pressure variations from CMIP6 HighResMIP useful for future gravity mission simulations?, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-18373, https://doi.org/10.5194/egusphere-egu25-18373, 2025.
The ESA Earth System Model (ESA ESM; Dobslaw et al., 2015) is widely applied as a source model in end-to-end simulation studies for future gravity missions but has been also utilised to study novel gravity observing concepts on the ground. The model provides a synthetic time-variable global gravity field that includes realistic mass variations in the atmosphere, oceans, terrestrial water storage, continental ice sheets and the solid Earth for a variety of spatial and temporal frequencies. With the continuous development of the next gravity missions such as GRACE-C and NGGM / MAGIC, the ESM should provide a wide range of signals at spatial scales which might not have been reliably observed by currently active missions.
In this contribution, we present the first steps towards version 3.0 of the ESA ESM. The projected changes include an update of the atmosphere and ocean components, a small ensemble of co- and post-seismic earthquake signals, an updated GIA model, and additional mass balance signals from previously not considered Arctic glaciers. Extreme hydrometeorological events as well as climate-driven and anthropogenic impacts on continental water storage will be represented through an update of the hydrological component. Additionally, the ESM will separately include ocean bottom pressure variations along the western slope of the Atlantic, representing variations in the meridional overturning circulation. ESA ESM 3.0 will be available with 6 hourly resolution from January 2007 until December 2020. It will be also augmented with synthetic error time-series to facilitate stochastical modelling of residual background model errors.
Dobslaw, H., Bergmann-Wolf, I., Dill, R., Forootan, E., Klemann, V., Kusche, J., & Sasgen, I. (2015). The updated ESA Earth System Model for future gravity mission simulation studies. Journal of Geodesy, 89(5), 505–513. https://doi.org/10.1007/s00190-014-0787-8
How to cite: Shihora, L., Klemann, V., Jensen, L., Dill, R., Stumpe, L., Tanaka, Y., Sasgen, I., Wouters, B., and Dobslaw, H.: Updating the ESA Earth System Model for Future Gravity Mission Simulation Studies: ESA ESM 3.0, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-5691, https://doi.org/10.5194/egusphere-egu25-5691, 2025.
Since the launch of the ESA Swarm satellites in 2014, GPS data has been used to monitor the monthly changes in Earth’s gravity field at a spatial resolution larger than 1,500 km (half-wavelength). We have chosen processing strategies that do not rely on assumptions of temporal and spatial correlations, producing models that are independent of GRACE and GRACE-FO data. We are a team composed of the Astronomical Institute of the University of Bern, the Astronomical Institute of the Czech Academy of Sciences, the Delft University of Technology, the Institute of Geodesy of the Graz University of Technology, and the School of Earth Sciences of the Ohio State University. We are supported by the European Space Agency and the Swarm Data, Innovation, and Science Cluster. Given the good health of the Swarm satellites, we will continue to produce high-accuracy hl-SST gravity field solutions in the foreseeable future.
We produce individual gravity field models following independent gravity field inversion strategies. The International Combination Service for Time-variable Gravity Fields (COST-G) combines these individual models using weights derived with Variance Component Estimation, with the main objective of keeping the combined model unbiased to any individual solution. The models are published quarterly, pending the successful processing of kinematic orbits in the increasingly challenging environment resulting from the increased solar activity. The models are accessible at ESA’s Swarm Data Access server (https://swarm-diss.eo.esa.int) as well as at the International Centre for Global Earth Models (https://icgem.gfz.de/sp/02_COST-G_/Swarm).
These data monitor geophysical processes in parallel to the ll-SST technique, offering the opportunity to validate the ll-SST models, act as an alternative in the event of gaps in their data records or to bridge the potential gap between the GRACE-FO and GRACE-C/MAGIC mission period.
We show that the signal variability over the oceans of our models is a reliable measure of their accuracy by comparing it with the differences over land between Swarm and the GRACE and GRACE-FO solutions. Despite GRACE/GRACE-FO’s higher spatial resolution, we demonstrate that our Swarm models are able to resolve large-scale hydrological signals. Finally, we show that our effort has mitigated the challenges of estimating gravity field models derived from GPS data during the occurrence of high solar activities, which degraded the GPS signals.
How to cite: 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.: Temporal gravity observed by the ESA Swarm satellites during the past decade, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-11903, https://doi.org/10.5194/egusphere-egu25-11903, 2025.
The Combination Service for Time-variable Gravity fields (COST-G) of the IAG looks back at an eventful and very successful year. The operational combination of the monthly GRACE-FO gravity fields now comprises eight analysis centers, providing high-quality solutions with short latency on a regular basis. When the new release 06.3 of the GRACE-FO Science Data System (SDS) time-series became available in September 2024, COST-G generated test combinations and could confirm the quality gain compared to the former release 06.2. Meanwhile, release 06.3 is routinely incorporated in the operational combination.
The number of analysis centers providing complete time-series of monthly gravity fields of the GRACE mission to COST-G has more than doubled compared to the original COST-G GRACE RL01, published in 2019. The current COST-G GRACE RL02 is a
weighted combination of 11 time-series, where the weighting scheme was adapted to be consistent with the operational GRACE-FO combination. The quality gain of the new combination is most pronounced during the early and late GRACE mission period, when data quality issues and environmental conditions were challenging.
How to cite: Meyer, U., Jäggi, A., Lasser, M., Dahle, C., Flechtner, F., Boergens, E., Foerste, C., Öhlinger, F., Mayer-Gürr, T., Lemoine, J.-M., Bourgogne, S., Döhne, T., Zhou, H., Ran, J., Chen, Q., Wan, C., and Feng, W.: COST-G: Status and new developments, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-15499, https://doi.org/10.5194/egusphere-egu25-15499, 2025.
How to cite: Pagiatakis, S. and Tzamali, M.: Exploring thermospheric disturbance patterns: A weighted accelerometer 1B dataset of GRACE C, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-12949, https://doi.org/10.5194/egusphere-egu25-12949, 2025.
The sub-daily high-frequency Earth gravity signal, dominated by atmospheric and oceanic mass change, is essential for understanding weather and climate change. It also serves as a fundamental data set for almost all existing terrestrial or space-borne geodetic observations, enabling the separation of desired signals. In particular, it provides unique input for satellite gravimetry such as GRACE, and GRACE-FO, to prevent the aliasing error, which is deemed the largest error source of existing missions and future next-generation gravity missions as well. Therefore, it is also called a de-aliasing product.
However, since establishing a global observation network to monitor/capture the high-frequency gravity signal is impractical, ongoing efforts are made to simulate such signals by driving the atmosphere/oceanic numerical model with a specific climate forcing field and assimilating observational data. By using the recently released CRA-40 (the 40-year global reanalysis dataset released by China Meteorological Administration) as the forcing field, we managed to drive the in-house 3-D atmospheric integration model and the LASG/IAP Climate System Ocean Model 3.0 (LICOM3.0) to reproduce a new high-frequency atmospheric and oceanic gravity de-aliasing product, called CRA-LICOM. It has a resolution of 6-hourly@50 km and covers the global domain from 2002 to 2024.
Due to the new data source and numerical models, CRA-LICOM can be deemed completely independent from the official product for GRACE, which helps in understanding the realistic uncertainty of high-frequency gravity signals. The atmospheric tidal and non-tidal components from CRA-LICOM show high consistency with the GFZ product, and ocean bottom pressure biases are minimal in most global ocean regions, with notable exceptions in the marginal seas near continental shelves. Furthermore, CRA-LICOM demonstrates a high correlation (>0.8) in Stokes coefficients with the GFZ official product until degree 20. Temporal gravity field recovery from GRACE using CRA-LICOM also aligns well with GRACE official products. Scientific applications that aim to understand the fast-changing global water cycle, as well as mission design of future satellite gravimetry that seeks accurate gravity de-aliasing, would benefit from our product. The data will be freely available at https://data.tpdc.ac.cn/.
How to cite: Bai, J., Yang, F., Liu, H., and Zhang, W.: CRA-LICOM: A global high-frequency atmospheric and oceanic temporal gravity field product (2002-2024), EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-9565, https://doi.org/10.5194/egusphere-egu25-9565, 2025.
The uncertainty characterisation in temporal gravity field recovery plays a crucial role for providing consistent and reliable information on mass change. We study gravity field determination from GRACE Follow-On satellite-to-satellite tracking data using the inter-satellite link of the K-Band Ranging System
and kinematic positions of the satellites as observations and pseudo-observations, respectively. We compute our solutions in a Least-Squares Adjustment with the Celestial Mechanics Approach, where - next to orbit, accelerometer and gravity field parameters - a set of nuisance parameters, i.e., constrained piece-wise constant accelerations, are estimated to account for any kind of unknown deficiencies. In addition, an empirical observation noise model is derived from post-fit residuals and applied as observation data weighting.
In this contribution, we extend the noise modelling by introducing another set of nuisance parameters, which are constrained according to uncertainty information about the atmospheric and oceanic de-aliasing (AOD), where we make use of the AOe07 variance-covariance information from Shihora et al. (2023)*.
We validate the new solutions by comparing them with models from the operational GRACE Follow-On processing at the Astronomical Institute of the University of Bern (AIUB), by examining the stochastic behaviour of respective post-fit residuals and by inspecting areas where a low noise is expected. Last but not least, we investigate the influence of AOD uncertainties in a combination of monthly gravity fields based on other approaches as it is done by the Combination Service for Time-variable Gravity fields (COST-G) and make use of noise and signal assessment applying the quality control tools routinely used in the frame of COST-G.
*Shihora, L., Balidakis, K., Dill, R. and Dobslaw, H.: AOe07 Variance-Covariance Matrix. V. 2.0. GFZ Data Services.
doi:10.5880/nerograv.2023.00
How to cite: Lasser, M., Meyer, U., Arnold, D., and Jäggi, A.: Integrating AOD uncertainties into the GRACE Follow-On processing at the AIUB, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-15666, https://doi.org/10.5194/egusphere-egu25-15666, 2025.
As part of the Science Data System, the GFZ Helmholtz Centre for Geosciences is one of the official GRACE/GRACE-FO Level-2 processing centers which routinely provide monthly gravity field models. These models are used by a wide range of geoscientists to infer mass changes at the Earth’s surface to study climate-related phenomena. Currently, GFZ´s operationally processed monthly gravity fields are still based on release 6 (RL06) standards. The distribution of a reprocessed and improved RL07 time series is planned for fall 2025. Most of the improvements have been developed within the Research Unit “New Refined Observations of Climate Change from Spaceborne Gravity Missions” (NEROGRAV) funded by the German Research Foundation DFG.
The main focus of the new release is on optimized stochastic modeling during the Level-2 processing. This includes the extension of the stochastic instrument error models, the optimization of the combination of the different observations, and the inclusion of tidal and temporally changing non-tidal background model error variance-covariance matrices in the adjustment process.
We present an overview of the expected performance of our upcoming RL07 gravity field time series compared to the current RL06 time series. Improvements stemming from the applied advanced processing strategy become visible in terms of a reduced noise level, as well as more realistic formal errors.
How to cite: Dahle, C., Hauk, M., Murböck, M., Panafidina, N., Wilms, J., Neumayer, K. H., and Flechtner, F.: Current status of the planned GFZ RL07 GRACE/GRACE-FO Level-2 time series, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-15267, https://doi.org/10.5194/egusphere-egu25-15267, 2025.
The satellite missions GRACE (Gravity Recovery And Climate Experiment) and GRACE-Follow-on (GRACE-FO) measure gravity field variations with homogeneous global coverage. Standard GRACE/GRACE-FO solutions are usually provided by different analysis centers as monthly mean gravity fields. An increase in the temporal resolution reduces the accuracy of the solutions so that it is not possible to compute daily solutions without taking into account additional information about the temporal correlations between the subsequent solutions. The assessment of this correlation is based on the knowledge of the stochastic properties of the underlying geophysical processes governing the variations of the gravity field on sub-monthly time scales. This method is known as Kalman filter approach.
In the frame of the Research Unit (RU) New Refined Observations of Climate Change from Spaceborne Gravity Missions (NEROGRAV), we investigate the possibility of obtaining Kalman daily gravity field solutions using refined stochastic information about two main geophysical processes causing high-frequency variations in the gravity field: non-tidal atmospheric and oceanic variations and hydrology. We present the first results for two test years, 2007 and 2020. To validate the obtained daily solutions, comparisons between our daily gravity fields and different flood events which took place during these test years were performed.
How to cite: Panafidina, N., Murböck, M., Dahle, C., Hauk, M., Wilms, J., Neumayer, K.-H., and Flechtner, F.: GFZ daily GRACE/GRACE-FO Kalman filter solutions, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-17708, https://doi.org/10.5194/egusphere-egu25-17708, 2025.
The GRACE-FO mission, which will conclude its seven-year orbital mission in May 2025, has significantly advanced the scientific legacy of the original GRACE mission, launched in 2002. By delivering continuous, highly accurate gravity field measurements, GRACE-FO has expanded our knowledge of key Earth system processes, supporting essential research in areas such as climate change, hydrology, oceanography, the cryosphere, and solid Earth science.
Both GRACE and GRACE-FO mission data is currently undergoing reprocessing for the upcoming RL07 release. The reprocessing is expected to enhance data quality through improvements in both L1 and L2 processing. This paper presents preliminary findings from the latest GRACE(-FO) mascon solutions developed by The Center for Space Research (CSR) at The University of Texas at Austin, using the reprocessed L1 data along with refinements in L2 processing. The RL07 mascon approach builds on the success of the CSR RL06 solutions and incorporating total variation (TV) regularization to reduce signal leakage between adjacent basins. The study assesses the quality of these new mascon gravity field solutions, comparing them against independent datasets and model predictions to evaluate their accuracy in the geo-spatial domain.
How to cite: Save, H., Jacob, G., Tamisiea, M., and Pie, N.: GRACE/GRACE-FO RL07 Mascon solutions from CSR, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-15005, https://doi.org/10.5194/egusphere-egu25-15005, 2025.
Since 2002, GRACE and GRACE-FO have provided pioneering observations of temporal variations in Earth’s gravity field. Mass flux estimation for GRACE/GRACE-FO typically parameterizes as a spherical harmonic series. Alternatively, mass concentration (mascon) solutions divide the Earth's surface into discrete blocks, allowing for the direct estimation of mass anomalies. The mascon approach, which employs locally defined basis functions rather than global ones, facilitates the incorporation of a-priori information to reduce aliasing effects and other modeling errors.
This study presents preliminary results of a newly developed mascon processing chain to retrieve mascon solutions for GRACE/GRACE-FO data. The solutions are derived from least squares inversions with Tikhonov regularization using the open-source software GROOPS. The processing scheme employs the point-mass mascon approach, and explicitly links inter-satellite range rate measurements to an analytical mascon formulation. The resulting mascon solutions are based on globally distributed, equal area blocks approximating 3° resolution at the equator. By incorporating tailored geographic information into the regularization process, the scheme mitigates the noise in the solutions and permits the geophysical signals to be detected. This approach eliminates the need for post-processing filters to remove north-south stripes and achieves a balance between signal recovery magnitude and error reduction.
This contribution displays preliminary results and discusses the processing chain for a point-mass mascon approach while comparing the preliminary mascon solutions with postprocessed spherical harmonic solutions in both spatial and spectral domains.
How to cite: Wu, H., Schlaak, M., and Pail, R.: GRACE/GRACE-FO Monthly Mascon Gravity Field Solutions: Processing Chain and Preliminary Results, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-15621, https://doi.org/10.5194/egusphere-egu25-15621, 2025.
Satellite gravity missions are unique observation systems to directly observe mass transport processes in the Earth system. This study investigates innovative approaches for resolving Earth's gravitational field using mass concentration models (mascons) as an alternative to spherical harmonic synthesis. The primary objective is to systematically evaluate strategies and concepts to optimize temporal and spatial gravity field recovery.
This contribution investigates the theoretical foundations of mascon approaches, with detailed analysis of their mathematical and geometric properties. Functional and stochastic models are derived, focusing on three main approaches: Lumped Spherical Harmonics, point masses, and spherical cap mascons (primarily considered conceptually). This selection enables a comparative evaluation of different geometric structures, showcasing the advantages of discrete methods over continuous ones.
A key feature of this study is an automated simulation algorithm integrating spherical harmonic synthesis and mascon models. The algorithm executes a four-step process: orbit dynamics computation, observation simulation, noise handling, and adjustment. This enables global solution computation validated against a reference model, as well as precise subpixel analyses for targeted regional investigations. Results demonstrate the advantages of mascon approaches for regional resolution, including enhanced coastal densification to address leakage effects and detailed studies of regions like the Amazon basin.
Simulations based on a de-aliasing model and the observational geometry of a GRACE-like single-pair mission indicate that mascon approaches achieve near-complete signal recovery with high stability and accuracy. Deviations, expressed in millimeters of Equivalent Water Height (EWH), allow attribution to specific gravity field components. Global equiareal models exhibit minimal deviations (~15 mm), surpassing spherical harmonics in stability due to the combination of basis functions and regularization. Regional analyses reproduce structures with method-dependent deviations up to 40 mm, while highlighting challenges related to subpixel analyses. Incorporating additional grids and constraints to enhance signal recovery increases model complexity. The point mass approach proves especially robust, whereas Lumped Spherical Harmonics show quality declines in specific cases. The results meet current standards of conventional mascon models and reveal significant optimization potential. Future research should focus on refining regularization methods, expanding the data foundation, and integrating additional basis functions to further improve simulation accuracy and application outcomes.
How to cite: Schiller, S., Schlaak, M., Wu, H., and Pail, R.: Evaluation and Tuning of Mascon Approach for Temporal Gravity Field Recovery, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-4169, https://doi.org/10.5194/egusphere-egu25-4169, 2025.
The estimation of ice mass variations using GRACE data is highly sensitive to evaluation parameters and processing options. Factors that contribute significantly to the variability of the results include the selection of spherical harmonic solutions, corrections for the geocentre motion, adjustments for inaccuracies in low-degree coefficients, application of auxiliary models to mitigate geophysical signal contamination, and the processing method. Döhne et al. (2023) propose sensitivity kernels as a robust representation of the processing method of surface mass changes, regardless of the general processing approach and the input data set. Sensitivity kernels allow the direct calculation of integrated surface mass changes within a given region and can directly be tailored to effectively account for inherent solution errors and leakage effects. In addition, they provide a consistent and reliable foundation for the evaluation. In this work, we apply this methodology to analyse surface mass changes in the Svalbard region. We test various input parameters, including spherical harmonic solutions or geocentre motion datasets, to determine whether the method produces consistent results regardless of the inputs. We also examine whether using a time-variable GRACE error covariance matrix to account for inherent solution errors yields different results compared to using its approximate representation. Our results highlight the applicability of tailored sensitivity kernels in regional studies and underline their potential to improve the consistency of GRACE-based assessments across different glaciated regions.
How to cite: Korekáčová, B., Wouters, B., and Döhne, T.: Application of Sensitivity Kernels for Accurate Surface Mass Change Estimation in the Svalbard Region Using GRACE Data, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-16267, https://doi.org/10.5194/egusphere-egu25-16267, 2025.
Monthly estimates of the Earth’s gravity field based on the GRACE/-FO missions have enabled decisive progress in the quantification and understanding of mass transfers in the Earth system. However, raw level 2 GRACE/-FO solutions are affected by large errors in the form of North-South stripes. Several filtering methods have been developed to isolate the gravity signal from these errors, based on either spatial covariance models of the signal and errors (gaussian filters, DDK filters), or on statistical decomposition techniques (PCA, ICA, SSA, M-SSA). This presentation introduces a new filtering method that relies on both the temporal and spatial structures of the signal and errors.
In the temporal domain, a spectral analysis of the GRACE/-FO Stokes coefficient time series suggests that they may be modeled as the sum of:
- linear trends,
- seasonal (annual and semi-annual) variations,
- ~160-day periodic variations,
- temporally uncorrelated aperiodic variations (white noise),
- temporally correlated aperiodic variations that may be described by a power-law stochastic process.
Assuming that the linear trends, seasonal variations, and time-correlated aperiodic variations reflect gravity signal, that this signal is spatially isotropic, while the ~160-day variations and white noise are errors, we construct a spatio-temporal Wiener filter of the GRACE/-FO level 2 solutions. We then compare the results of this Wiener filter with those from the DDK5 filter and Gauer et al. (2023)’s M-SSA filter. The advantages, drawbacks and prospects for improvement of the Wiener filter are finally discussed.
How to cite: Rebischung, P., Gobron, K., Bourlon, G., Gauer, L.-M., and Chanard, K.: Spatio-temporal Wiener filtering of GRACE/-FO solutions, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-11578, https://doi.org/10.5194/egusphere-egu25-11578, 2025.
The 2017-2027 Decadal Survey for Earth Science and Applications from Space has identified the Targeted Mass Change Observable as one of 5 Designated Mission. In Europe, the development of the ESA Next Generation Gravity Mission is on progress, with the start of the Phase B in 2024.
These missions will continue the observation provided by GRACE and GRACE-FO. In these missions and the future concepts, the accelerometer provides either the gravity signal in a gradiometer configuration (GOCE type mission), or the non-gravitational acceleration to be suppressed to the ranging measurement between two satellites (GRACE-type mission).
In the frame of NGGM activities with ESA, Onera is developing the new accelerometer MicroSTAR, a high accuracy accelerometer with 3 sensitive linear acceleration measurements as well as 3 angular acceleration measurements for the attitude control or reconstruction. PDR of the accelerometer chain has been done at the end of year 2024 and CDR of the accelerometer sensor head will be held in May 2025.
ONERA have procured the accelerometer for all the previous gravity missions (GRACE, GOCE, GRACE-FO). In parallel, ONERA work to improve the scientific return of the instruments for the future missions:
- a miniaturized version of MicroSTAR, the CubeSTAR accelerometer, is developed with internal funding. CubeSTAR is adapted for constellation or nanosat,
- An other way is to improve the low-frequency noise of the accelerometer, by hybridization of electrostatic accelerometer with cold atom interferometer.
The presentation will present the status of the MicroSTAR development, and will detail the development of future instruments.
How to cite: Maquaire, K., Ait-Mehdi, A., Boulanger, D., Chhun, R., Christophe, B., Dalin, M., Hervieux, T., Lebat, V., Liorzou, F., Portier, N., Rodrigues, M., and Rodriguez-Beignet, M.: ONERA accelerometers for NGGM and for future gravity missions., EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-11963, https://doi.org/10.5194/egusphere-egu25-11963, 2025.
The existing observation record of satellite gravity missions spans more than two decades and is already closing in on the minimum time series of 30 years needed to decouple natural and anthropogenic forcing mechanisms according to the Global Climate Observing System (GCOS). The next generation of gravity field missions (GRACE-C, NGGM) are expected to be launched within this decade. These missions as well as their combination (MAGIC) are setting high anticipation for an enhanced monitoring capability that will improve the spatial and temporal resolutions of gravity observations significantly. They will allow an evaluation of long-term trends in the Terrestrial Water Storage (TWS) signal.
This contribution shows numerical closed-loop simulation results of a GRACE-type in-line single-pair missions and MAGIC double-pair missions with realistic noise assumptions for the key payload, tidal and non-tidal background model errors. To enable the analysis of multi-decadal observations, the reduced scale simulation following the acceleration approach are performed. The gravity signal in the simulations is based on modeled mass transport time series of components of the TWS, obtained from future climate projections until the year 2100 following the shared socio-economic pathway scenario 5-8.5 (SSP5-8.5). It evaluates different parameter models, among them the recoverability of long-term climate trends, annual amplitude, and phase of the TWS employing closed-loop numerical simulations of the different constellations. Special emphasis shall be given on the robustness of the estimated TWS long-term-trend for different parameter models applied in different simulation scenarios, systematic changes, as well as on the methodology of the simulation themselves.
How to cite: Schlaak, M. and Pail, R.: Parameter Model Comparison using Closed-loop Simulations of Current and Future Satellite Gravity Missions, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-4096, https://doi.org/10.5194/egusphere-egu25-4096, 2025.
This research investigates the synergy of utilizing sea surface height (SSH) measurements from the non-dedicated Surface Water and Ocean Topography (SWOT) altimetry mission in conjunction with hydrodynamic models and in-situ measurements. The SSH and geoid are linked through dynamic topography (DT), which can be obtained from hydrodynamic models. The method considers satellite altimetry and modelled data to be reasonably accurate so that the static geometric marine geoid surface can be derived (i.e., geoid = SSH - DT). The application of this method not only enhances existing geometric geoid models but also has the potential to assist in deriving new ones in regions where current geoid models are inaccurate and of lower quality due to gravity data deficiencies. The proposed method is tested in the Baltic Sea, where accurate geoid models are available, as well as in areas near and inside the Russian sea border, where the lack of in-situ gravity measurements causes inaccuracies in gravimetric geoid modelling.
A critical aspect of the proposed approach is in the validation phase, where the SWOT-derived geoidal heights are compared with (i) marine geoid models of the Baltic Sea (e.g., NKG2015, BSCD2000), (ii) geoidal heights obtained from precise airborne laser scanning, and (iii) shipborne GNSS measurements.
The results demonstrate that by utilizing KaRIn data (L2_LR_SSH, Basic, 2×2 km grid), it is possible to identify and quantify errors in areas lacking gravity data, revealing discrepancies of a few decimeters in existing geoid models. In summary, SWOT-derived geometric geoid has the potential to compete with existing Baltic Sea marine geoid models that have an accuracy of around 3 cm. The results indicate that KaRIn altimeter data can help determine the marine geoid surface with sufficient accuracy of 5 cm or even better. The methodology explored with the synergy of datasets paves the way for novel opportunities for geometric geoid determination for other sea areas globally. This is especially useful for maritime activities, climate research, and navigation opportunities.
How to cite: Kupavoh, A., Ellmann, A., Delpeche-Ellmann, N., and Varbla, S.: SWOT-Derived Geometric Marine Geoid Surface complements Gravimetric Geoid Modelling approaches, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-10957, https://doi.org/10.5194/egusphere-egu25-10957, 2025.
The Surface Water and Ocean Topography (SWOT) mission, with its short repeat period, is more sensitive to dynamic sea surface variations and more prone to introducing spurious signals. Therefore, considering time-varying effects is crucial when constructing a stable gravity field from SWOT data. This study explores the impact of these effects using model correction and stacking methods. The results show that incorporating time-varying effects enhances deflection of the vertical (DOV) by approximately 40% in high time-varying areas and improves gravity anomalies by 0.26 mGal (~9%). Furthermore, a single model-corrected cycle outperforms the accumulation of a year’s data in high-variability regions. In contrast, the stacking method introduces more outliers at the edges and nadir, making it less effective than the model correction method. Finally, the analysis of a 40°×40° region in the eastern Pacific highlights the need for corrections in regions where the standard deviation of the sea level anomaly exceeds 20 cm. This study demonstrates that accounting for time-varying effects can significantly improve the precision of DOV and gravity anomaly fields in high-variability areas, contributing to a more accurate marine gravity field.
How to cite: Heyuan, S., Yongjin, T., and Jiancheng, L.: The Influence of Changing Sea Surface on the Gravity Field Derived from SWOT., EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-2414, https://doi.org/10.5194/egusphere-egu25-2414, 2025.
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 MAGIC mission in developing Level-2 and Level-3 products.
In this presentation examples of GUT applications using recent models are presented. Various quantities associated with the gravity field are computed and inter-compared to assess the models and describe their capabilities. In addition, GUT tools for the computation of the dynamic ocean topography and the associated geostrophic surface currents are applied.
How to cite: Knudsen, P., Ambrozio, A., and Restano, M.: Evaluating static gravity field models using GUT, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-6275, https://doi.org/10.5194/egusphere-egu25-6275, 2025.
The Nash Creek area in Northern New Brunswick, Canada, is home to a blind Zinc Lead Silver sulphide deposit hosted within a complex Ordovician-Devonian rift system. Extensive exploration of the area over several decades has resulted in a varied set of data at multiple scales, including – but not limited to – magnetic, radiometric, and high resolution LIDAR DEM data at the regional scale and TEM, resistivity, and high resolution terrestrial gravity data at the local scale. Additionally, approximately 400 boreholes have been drilled and logged over and around the known extents of the mineral deposit. This has also resulted in a comprehensive petrophysical database, including the densities of different rock units. Despite this wealth of data, many questions about the geology of the area remain unresolved, and the deposit is poorly constrained. This is in large part due to a thick layer of overburden blanketing the region, rendering existing geological maps ambiguous. Moreover, the gravity data has been difficult to incorporate as it shows a steep gradient over the region.
In order to best characterize this gradient, large scale regional gravity data must be analysed. Unfortunately, geodetic control stations (GCSs) are sparse within the region. Thus, we turn to a satellite derived global gravity model (GGM) to get a picture of the regional gravitational field. Using the GGM, we see that a large positive gravity anomaly of approximately 20 mGal lies directly to the west of the study area, and a similarly sized negative anomaly lies just to the east. Over the study area itself, the regional field changes at a rate of roughly 1.62 mGal/km. The primary goal of this study is to investigate the optimal method to remove this gravity gradient from our high resolution dataset. We characterize the regional field by combining the GCS data with the GGM, and then use this regional field approximation to isolate the residual field in our high-resolution gravity dataset. We then compare the results to those attained using other methods, such as the upward continuation method of regional field approximation.
Another goal of this study is to study the source(s) of this distinctive gravitational feature. We do this by using mass excess/deficiency calculations, and by incorporating regional magnetic, radiometric, and geologic data into our interpretation. We also compare this feature to other similar large scale gravity anomalies. Studying the cause of the gravity anomaly at Nash Creek can help to achieve a better understanding of the regional geologic history, and potentially help to identify the most promising approaches for geophysical exploration in this complex geological setting.
How to cite: Kahn, D., Milkereit, B., Bank, C.-G., and Ugalde, H.: In the Shadow of Large Gravity Anomalies - Recovering Useful Gravity Data for Geologic Exploration, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-5253, https://doi.org/10.5194/egusphere-egu25-5253, 2025.
