We look forward to contributions that:
1. Utilize geodetic data from diverse geodetic satellites, including altimetry, gravimetry (CHAMP, GRACE, GOCE, and GRACE-FO, SWOT), navigation satellite systems (GNSS and DORIS) or remote sensing techniques that are based on both passive (i.e., optical and hyperspectral) and active (i.e., SAR, Sentinel, NISAR) instruments.
2. Cover a wide variety of applications of geodetic measurements and their combination to observe and model Earth system signals in hydrological, ocean, atmospheric, climate, and cryospheric sciences.
3. Show a new approach or method for separating and interpreting the variety of geophysical signals in our Earth system and combining various observations to improve spatio-temporal resolution of Earth observation products.
4. Work on simulations of future satellite missions (such as MAGIC and NGMM) that may advance climate sciences.
5. Work towards any of the goals of the Inter-Commission Committee on "Geodesy for Climate Research" (ICCC) of the International Association of Geodesy (IAG).
We are committed to promoting gender balance and ECS in our session. With the author consent, highlights from this session will be shared on social media with a dedicated hashtag during the conference in order to increase the impact of the session.
Orals: Tue, 5 May, 14:00–15:45 | Room K1
Coastal zones face increased risks from the combined effects of climate-driven sea-level rise and vertical land motion (VLM), which together determine rates of relative sea-level (RSL) change. While oceanic contributions to RSL are increasingly well monitored and projected, land subsidence (i.e., negative VLM) remains one of the least systematically observed and most spatially heterogeneous components of RSL, despite its potential to locally exceed climate-driven ocean rise by an order of magnitude. This observational gap is especially pronounced in rapidly urbanizing and data-limited regions, where sparse tide-gauge and GNSS networks hinder the identification of subsidence hotspots and their evolving impacts on coastal risks.
In this talk, I present a framework that leverages satellite geodesy as a climate observing system to resolve the spatiotemporal dynamics of land subsidence and quantify its contribution to present and future relative sea-level change, using Java Island, Indonesia, as a regional-scale case study. We generated high-spatial resolution (75 m) contemporary VLM fields from using multi-geometry Sentinel-1 interferometric synthetic aperture radar (InSAR), revealing widespread and temporally evolving subsidence patterns with rates exceeding 1 cm per year across multiple coastal and inland urban centers. While Jakarta has dominated the subsidence narrative in Indonesia, we find that several other coastal cities, including Cirebon, Pekalongan, Tegal, and Semarang, are sinking two to three times faster, with localized rates approaching 10 cm per year.
To disentangle the dominant drivers of deformation, we applied unsupervised machine-learning spatiotemporal clustering to InSAR time series, guided by geological and land-use information. This analysis reveals nonlinear and spatially heterogeneous subsidence behaviors primarily associated with groundwater extraction in urban, industrial, and agricultural regions, alongside localized deformation linked to natural processes such as volcanism. Finally, we constructed synthetic tide-gauge records at 5-km spacing along the 1,500 km northern coastline by integrating InSAR-derived VLM with satellite altimetry and probabilistic sea-level projections. These virtual gauges show that neglecting land subsidence leads to systematic underestimation of RSL change by more than 90% in some locations and that subsidence will remain the dominant contributor to RSL rise across much of the coastline through 2050.
This work illustrates how geodetic observing systems can fill critical observational gaps in coastal climate research, enabling spatially explicit, process-informed RSL estimates and providing a transferable framework for improving sea-level risk assessments in vulnerable, data-sparse regions worldwide.
How to cite: Ohenhen, L.: Resolving land subsidence contribution to present and future relative sea level change using satellite geodesy, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-8826, https://doi.org/10.5194/egusphere-egu26-8826, 2026.
Variations in sea level are a globally comprehensively measurable indicator of the effect of climate change on the Earth system. Satellite geodesy provides data with global coverage to analyze sea level changes in space and time, but also to investigate the individual contributions to sea level from the subsystems oceans, continental hydrology, glaciers, ice sheets, and the solid Earth. Particularly valuable for this purpose are time-variable satellite gravity, realized by the GRACE and GRACE-FO missions, and satellite altimetry over the oceans, realized, e.g., by the Jason-1/-2/-3 and Sentinel-6 reference missions. However, previous studies show that the uncertainty of the estimated Antarctic Ice Sheet’s contribution to sea level remains large, primarily due to errors in the glacial isostatic adjustment (GIA) correction. We use a global fingerprint inversion method that evaluates GRACE and ocean altimetry data in a globally consistent framework and enables the quantification of individual contributions to sea level on a monthly basis on global grids. The inversion is additionally supplemented by observations from Argo floats. The parametrization of the contributions from steric effects, ice sheets, glaciers, hydrology, and GIA are realized by time-invariant sea-level fingerprints obtained from a priori information. This includes, e.g., the locations of mass changes or statistically obtained information from geophysical model simulations. In a methodological advancement of the inversion method, we have implemented a new parametrization of the ice mass changes (IMC) of the Antarctic ice sheet. Previously, IMC and corresponding sea level change has been estimated only on basin level for 27 large ice catchment areas, so-called drainage basins. However, this coarse parametrization of IMC prevents the inversion method from better resolving errors in the GIA correction in upcoming inversion implementations. We have therefore introduced a high-resolution parametrization based on individual grid points with a resolution of up to 50 km, resulting in up to 4755 Antarctic mass balance parameters to be estimated in a globally consistent way. In order to solve this inverse problem, we introduced altimetry over ice sheets as an additional observation at a 10 km spatial and a monthly temporal resolution. We present and discuss results from different variants of parametrization of IMC and different variants of implementation of ice altimetry observations. This methodological advancement presented here is a necessary step towards minimizing GIA-related errors when determining the sea level budget utilizing this global framework in the future.
How to cite: Willen, M. O., Uebbing, B., Horwath, M., and Kusche, J.: A global inversion for sea-level contributions from satellite data: towards improving Antarctica's representation, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-10826, https://doi.org/10.5194/egusphere-egu26-10826, 2026.
The Gravity Recovery And Climate Experiment (GRACE) and its follow-on mission, GRACE-FO, have observed global mass changes and transports, expressed as total water storage anomalies (TWSA), for over two decades. However, for climate change attribution and other applications, multi-decadal TWSA time series are required. This need has prompted several studies on reconstructing TWSA using regression or machine learning techniques, aided by predictor variables such as rainfall and sea surface temperature. However, the training period is limited to a couple of years, making it hard to capture interannual signals accurately. Furthermore, learned relationships between climate variables and water storage cannot be transferred straightforwardly to the past. To overcome the limitation and provide a more long-term, consistent dataset, we derive a preliminary reconstruction and combine it with large-scale time-variable pre-GRACE gravity information from geodetic satellite laser ranging (SLR) and Doppler Orbitography by Radiopositioning Integrated on Satellite (DORIS) tracking from Löcher et al. (2025). We reconstruct GRACE-like TWSA for the global land, excluding Greenland and Antarctica, from 1984 onward. We find that the seasonal cycle of our new reconstruction is consistent with that of previously published purely climate-data-based reconstructions. Moreover, in many regions, TWSA trends were markedly different in the pre-GRACE timeframe, and we thus suggest caution when interpolating GRACE-derived trends.
How to cite: Hacker, C., Gutknecht, B. D., Löcher, A., and Kusche, J.: Reconstructing terrestrial water storage anomalies based on climate data and pre-GRACE satellite observations, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-16439, https://doi.org/10.5194/egusphere-egu26-16439, 2026.
The Gravity Recovery and Climate Experiment (GRACE) and its successor GRACE-FO provide unique observations of Earth’s time-variable gravity field, enabling direct monitoring of mass redistribution expressed as equivalent water height (EWH). While gridded Level-2B products are widely used across hydrology, glaciology, and solid-Earth studies, uncertainty information remains fragmented or inaccessible to end users. In practice, this has led to the widespread use of empirical or ad hoc uncertainty estimates, limiting data assimilation and other geophysical applications that require spatially and temporally resolved observational error information.
We present TUD-L2B-EWH_UNC-GRACE, a globally gridded Level-2B GRACE(-FO) EWH data product that provides a comprehensive and transparent characterisation of uncertainty alongside the mass anomaly fields. Unlike conventional approaches that rely on propagation of full normal matrices or impose assumptions on error correlations, TUD-L2B-EWH_UNC combines ensemble statistics from multiple independently processed Level-2 solutions to quantify pre-processing uncertainties. These include contributions from ocean tide model differences, parametrisation strategies, and uncertainty in the Atmosphere and Ocean De-aliasing (AOD1B) background model.
Post-processing uncertainties associated with filtering, leakage, and Glacial Isostatic Adjustment (GIA) are quantified separately. Filtering-related uncertainty is evaluated using a known-pair approach, while GIA uncertainty is assessed using an ensemble of 56 published GIA models. Error fields are provided for a suite of anisotropic filtering strategies (DDK(2–7)), enabling systematic assessment of filtering choices, leakage effects, and model dependence on the total uncertainty budget.
TUD-L2B-EWH_UNC is the first Level-2B EWH dataset to deliver end-to-end, spatially and temporally resolved uncertainty fields in a user-ready gridded format. This design supports consistent uncertainty handling across hydrological, glaciological, and solid-Earth applications. Ancillary tidal corrections and climatological fits of signal and leakage-related errors are distributed separately through the companion products TUD-L2B-EWH_CLIM-GRACE and TUD-L2B-EWH_CLIM_LEAKAGE-GRACE. All datasets are publicly available (DOI: doi.org/10.4121/4fc748e8-01c7-4f06-87da-653937b078f7) via the TU Delft GRACE Portal (https://grace-cube.lr.tudelft.nl/).
How to cite: Cuadrat-Grzybowski, M. and de Teixeira da Encarnacao, J. G.: TUD-L2B-EWH_UNC: A Monthly Global Level-2B GRACE(-FO) EWH Uncertainty Product, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-11806, https://doi.org/10.5194/egusphere-egu26-11806, 2026.
Under the assumption that a warming climate leads to an intensification of the global water cycle, it is hypothesized that also the occurrence frequency and severity of extreme events such as droughts and floods will increase in the upcoming decades. GRACE/-FO observations of terrestrial water storage (TWS) have been used in the past to identify and analyse extreme events both on a global and regional scale. However, these analyses are restricted by the limited spatial and temporal resolution of current satellite gravimetry observations. Especially, flooding events tend to occur very locally and with short temporal (sub-monthly) extent, thus capturing them is challenging. Future satellite gravimetry missions, particularly the double-pair constellation MAGIC, are expected to significantly enhance the spatial and temporal resolution. In this study, we globally investigate the benefit MAGIC can achieve to detect wet extreme events using long-term (50 years) end-to-end simulations of GRACE-C and MAGIC.
The simulation environment is based on the acceleration approach and considers tidal and non-tidal background model errors as well as instrument noise of the acceleration and ranging instruments following the current MAGIC mission design studies. As input and reference, we use the daily output of a climate model (GFDL-CM4) from the CMIP6 archive that has been identified as a realistic representation of water storage evolution in previous studies. To explore the improved temporal and spatial resolution expected from the MAGIC constellation, we (i) compare extreme values derived from 5-daily gravity field simulations to those from monthly fields, and (ii) show how the weaker spatial filtering required for MAGIC has a positive influence on the detectability of extremes.
For the analysis two different approaches are exploited: One method focuses solely on the stochastic characteristics of the time series in terms of extreme value theory, evaluating the magnitude-frequency relationship of large TWS values by calculating expected return levels of wet extremes. The other approach builds on the fact that a 50-years simulation time series allows to derive statistically meaningful conclusions from directly comparing reference and simulation output on a time series level. We evaluate the time of occurrence of wet extremes on the basis of classification scores assessing correctly and incorrectly identified extreme events.
How to cite: Middendorf, K., Jensen, L., Schlaak, M., Haas, J., Dobslaw, H., Pail, R., Güntner, A., and Eicker, A.: Benefits of future satellite gravimetry missions for characterizing extreme wet events in terrestrial water storage, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-10722, https://doi.org/10.5194/egusphere-egu26-10722, 2026.
Abstract:
Climate change has been proven to exacerbate the ongoing deformations of the Earth's surface in Germany. Also, human activities such as mining, fluid extraction, and reservoir-induced seismicity cause local surface deformations. Therefore, long-term forecasts of Earth's surface movements are needed for infrastructure planning, hazard mitigation, and the sustainable management of natural resources in Germany. By applying Machine Learning (ML) and statistical analyses, we develop scientific scenarios of climate change to forecast surface movements in Germany over the next two decades. Together with Global Navigation Satellite Systems (GNSS), data from five interdisciplinary fields, including the Sun and Moon ephemerides, polar motions, surface loadings, gravity variations, and meteorology, are utilized as features for training ML-based forecast models. Our results indicate that the accuracy of regression ML models reaches millimeter levels, and the decadal forecast models produce fewer than 2% extreme values in the total predictions per year. Based on climate change scenarios, the findings reveal that the average intra-plate motions in Germany will accelerate from ~1.2 mm/yr to ~1.5mm/yr over the next two decades. The annual variations across the 346 GNSS monitoring stations are predicted to increase from 4.7mm to 5.1mm. Surface deformations will be more severe in the southeastern regions and river basins such as the Elbe, Weser, Ems, and Rhine. Significant extensions are expected in the Eifel volcanic region, while notable compressions may occur along the Upper Rhine Graben and the Saxony region in the next twenty years. Additionally, experimental functions showing the statistical distribution of Earth's surface deformation trends in Germany over the next two decades have been proposed. Potentially, the methodology in this study can also be adapted to forecast surface movements related to climate change in polar regions.
Keywords:
Climate change, Surface deformation, Movement forecast, Machine learning, GNSS
How to cite: Le, N., Kłos, A. K., Pham, T. T. T., Luong, T. T., Nguyen, C., and Thomas, M.: Scientific Scenarios of Climate Change for Decadal Forecasts of Earth’s Surface Movements in Germany , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-9263, https://doi.org/10.5194/egusphere-egu26-9263, 2026.
In existing GNSS-based terrestrial water storage (TWS) inversion studies, the PREM model is commonly adopted, and crustal structural heterogeneity is often neglected. Here, we conduct a comprehensive assessment of how different Earth models affect inversion results using both checkerboard-model experiments and continuous smooth-model experiments. The results show that, under realistic hydrological loading conditions within the study region (100°E–115°E, 25°N–40°N), inversion differences among global 1-D reference Earth models are below 2%, whereas the differences between global 1-D reference models and regional crustal models are ~11%; meanwhile, discrepancies between the two regional crustal models remain below 4%. Application to observed GNSS coordinate time series in Yunnan indicates that the spatial pattern of the annual equivalent water height (EWH) amplitude derived from GNSS is broadly consistent with that from the GLDAS hydrological model; however, the choice of Earth model can still substantially alter the magnitude of the inferred amplitude and its spatial distribution. Correlation analyses further suggest that Earth-model dependence is weak for large-scale inversions, but becomes non-negligible at smaller spatial scales. For a representative small-scale subregion (101.75°E–102°E, 22.75°N–23°N), we therefore recommend using the AK135F model to construct Green’s functions. Overall, our findings demonstrate that Earth-model selection is a key source of uncertainty in GNSS-based TWS inversion, and provide practical guidance for choosing appropriate Earth models to improve inversion accuracy.
How to cite: He, J. and Li, Z.: Impact of Earth Model Selection on Terrestrial Water Storage Inversion from GNSS Vertical Displacements, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-17088, https://doi.org/10.5194/egusphere-egu26-17088, 2026.
Monitoring essential climate variables such as Sea level rise, Earth’s Energy Imbalance, and ice-mass changes relies critically on space-geodetic observations of surface deformation and variations of the gravity field.
In particular, satellite geodesy provides decades-long, globally consistent records that are fundamental for quantifying climate-driven surface mass redistribution. However, these observations integrate both mass changes from the oceans, atmosphere, cryosphere and continental hydrology and the associated solid Earth response. Isolating climate variables from geodetic data therefore requires models that reflect the solid Earth response across timescales relevant to contemporary variability.
Yet, a critical assumption underlies much of current space-geodetic standard processing: the solid Earth response to surface mass variations is treated as purely elastic, i.e. instantaneous and fully recoverable. However, there is a growing body of evidence from laboratory rock mechanics experiments and geophysical observations suggesting that the Earth’s mantle exhibits a time-dependent, recoverable anelastic response across intermediate timescales that could significantly affect geodetic at decadal to centennial timescales.
Here, we exploit several decades of Satellite Laser Ranging (SLR) observations towards passive spherical satellites to constrain key parameters governing the time-dependent mantle anelasticity. Owing to long-term measurements and sensitivity to low-degree gravity field variations, including solid Earth tides (C20, C30) and the pole tide (C21/S21), SLR observations are particularly well suited to probing deep Earth mantle rheology over decadal timescales.
We combine analytical orbit perturbation theory with the Hill-Clohessy-Wiltshire equations to quantify the sensitivity of the SLR observables to rheology and to choose an optimal parametrization. We then numerically estimate the solid Earth transient rheological properties from the SLR time series using an anelasticity framework consistent with seismic attenuation theory. Our results are compared with independent rheological constraints and yield a new set of frequency-dependent Love numbers that capture the Earth’s mantle transient rheology across decadal timescales.
We further show that accounting for this transient rheology by incorporating the corresponding frequency-dependent Love numbers into the modeling of solid Earth tides, pole tide and surface loading-induced deformation, introduces systematic differences in climate-relevant geodetic time-series, including satellite altimetry sea level rise estimates and ocean mass trends derived from satellite gravimetry.
More broadly, our results show that as space geodetic records become longer, data processing cannot rely solely on an elastic solid Earth assumption. Instead, it must account for solid Earth transient rheology and the fact that geodetic observables will increasingly depend on the cumulative loading history, strengthening the need for interdisciplinary geodetic, geophysical and climate studies.
How to cite: Rousselet, M., Couhert, A., Chanard, K., Exertier, P., and Fleitout, L.: Constraining transient solid Earth rheology using satellite orbit perturbations to assess the dynamics of climate change, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-18067, https://doi.org/10.5194/egusphere-egu26-18067, 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, ocean tide, dealiasing and toning 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-like (single polar pair), NGGM (single inclined pair), and MAGIC (double pair).
The synthetic gravity observations have first been used to assess the closure of the sea level budget. With historical GRACE, altimetry, and Argo data, global sea level budget closure is achieved with an accuracy of 0.3–0.4 mm/yr (2003–2015). Using VADER-filtered simulations, all three configurations contribute <0.1 mm/yr to the global mean sea level error. NGGM and MAGIC maintain this accuracy even without filtering, unlike GRACE-C. At regional scales, NGGM and MAGIC notably improve significantly the sea level budget closure, especially at seasonal and interannual timescales, though gains for decadal trends remain modest.
The synthetic gravity observations were also used to assess the closure of the global energy budget. Historical gravimetry, altimetry, and Argo data yield global mean ocean heat uptake (GOHU) accuracy of 0.2–0.3 W/m² (2003-2015). With VADER-filtered simulations, GRACE-C-like missions contribute up to 0.19 W/m² uncertainty, while NGGM and MAGIC improve this by 30–40%, achieving ~0.12–0.13 W/m² accuracy. They also enhance the stability and temporal consistency of GOHU retrievals. Regionally, NGGM and MAGIC outperform GRACE-C by up to 80% in recovering ocean heat content changes at mid-latitudes (30–60° N/S). Slightly better results are obtained with NGGM due to the use of mission error covariance information in the VADER filter. NGGM and MAGIC recover mean and temporal variations in ocean heat uptake at regional scales with up to 50% higher accuracy than GRACE-C.
The NGGM and MAGIC missions will substantially enhance the accuracy, spatial and temporal resolution of gravity-based observations of sea level changes and its drivers. These improvements strengthen global climate assessments, support the evaluation of mitigation policies, and improve climate model validation. In particular, sustained and redundant monitoring of ocean heat uptake would provide an early and robust indicator of changes in radiative forcing, preceding detectable stabilization of global temperatures by several decades. Improved characterization of regional heat-uptake pathways also enhances projections of sea level rise, marine heat extremes, and ocean circulation changes, supporting climate risk management across coastal, marine, and ecosystem applications.
How to cite: Ferrari, R., Pfeffer, J., Bouih, M., Meyssignac, B., Blazquez, A., and Daras, I.: Impact of NGGM and MAGIC on Sea Level and Energy Budgets Closure, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-18337, https://doi.org/10.5194/egusphere-egu26-18337, 2026.
Posters on site: Tue, 5 May, 10:45–12:30 | Hall X1
The interplay between the length of day (LOD) and the El Niño–Southern Oscillation (ENSO) has been investigated in geophysical research since the 1980s. LOD, defined as the negative time derivative of UT1-UTC, is intrinsically linked to the Earth Rotation Angle (ERA), a fundamental Earth Orientation Parameter (EOP).
ENSO, a dominant climate mode in the tropical eastern Pacific, substantially influences tropical and subtropical regions. Extreme ENSO episodes are associated with significant hydroclimatic anomalies across multiple regions, including severe droughts and floods. These events evolve over extended incubation periods, during which interannual fluctuations in LOD and the angular momentum of the atmosphere (AAM), ocean (OAM), and lithosphere/hydrogeosphere (HAM) are modulated by complex ocean–atmosphere interactions.
Key manifestations of ongoing climate change, such as rising global temperatures and sea levels, are strongly modulated by ENSO. Interannual variability in global mean sea surface temperature (GMST) and global mean sea level (GMSL) further reflects Earth's rotational dynamics changes.
This study aims to elucidate the interannual (2–8 years) couplings between LOD, AAM, OAM, HAM, and selected climate indices, including the Southern Oscillation Index (SOI), Oceanic Niño Index (ONI), GMST, and GMSL. The influence of these climate signals on LOD from 1976 to 2024 will be assessed using advanced semblance analysis, exploring multiple methodological variants based on the continuous wavelet transform to capture correlations across both temporal and spectral domains.
A detailed understanding of these interactions enhances our knowledge of Earth’s dynamic system, informs geophysical modeling efforts, and improves the precision of applications that rely on accurate timekeeping and measurements of Earth’s rotational behaviour.
How to cite: Staniszewska, D. and Wińska, M.: Length of Day Variability and Climate Indicators: Insights from ENSO Events , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-631, https://doi.org/10.5194/egusphere-egu26-631, 2026.
Variations in terrestrial water storage (TWS), as observed by the GRACE/GRACE-FO missions, provide unique insights into large-scale hydrological processes. However, translating these satellite observations into transport parameters such as surface diffusivity, lateral water fluxes, and groundwater recharge remains challenging. In this study, we propose using a surface diffusion-advection model coupled with a WGHM data assimilation framework of gridded GRACE solutions to estimate subsurface diffusivity and systematic precipitation–evapotranspiration biases simultaneously. The global kinematic hydrology model represents the lateral and vertical transport of water by diffusion, while GRACE observations represent the total water storage. In the steepest descent 4D Var-like procedure, the parameter gradients of the objective function are computed using the hydrological model's adjoint. Errors on derived diffusivities are also computed. The optimised parameters enable us to diagnose effective surface diffusivity and lateral water fluxes, as well as net groundwater recharge. This framework provides a physically consistent interpretation of GRACE-observed mass redistribution and offers new perspectives on large-scale hydrological transferts.
How to cite: Ramillien, G., Darrozes, J., and Seoane, L.: Estimation of surface hydrological diffusivity and atmospheric flux bias using GRACE satellite data, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-4049, https://doi.org/10.5194/egusphere-egu26-4049, 2026.
More than 90% of the excess energy entering the Earth system due to increased greenhouse gas concentrations is stored in the ocean within just a few years. This ocean heat storage has helped limit surface warming and modulate Earth’s radiative response, thereby influencing the global energy budget. Understanding Ocean Heat Content (OHC), including its temporal and spatial variations, is crucial for grasping global energy dynamics and constraining climate change projections.
Geodetic observations from satellite gravimetry (GRACE and GRACE-FO) and satellite altimetry enable to estimate OHC through thermal expansion, derived from sea level rise corrected for changes in ocean mass. This geodetic approach provides broad coverage and high resolution but faces challenges in resolving interannual variability. In particular, it cannot determine the depth at which heat is stored, introducing ambiguity when converting thermal expansion into OHC anomalies.
This work introduces a new OHC product that, for the first time, combines in-situ, altimetric, and gravimetric data using an inverse method. The inclusion of in-situ ARGO data helps constrain the vertical distribution of heat down to 2000 m, addressing ambiguities in the geodetic approach. By optimizing the residuals between in-situ and geodetic OHC and applying objective mapping techniques, the method produces consistent OHC fields along with associated uncertainty estimates.
The new product is validated against existing in-situ datasets. Its derivative—Ocean Heat Uptake (OHU)—is compared with CERES radiation budget data to assess the closure of the Earth’s energy balance over the ocean. The comparison shows that the ocean energy budget is closed from the top of the atmosphere (TOA) to 2000 m depth on an annual basis, with a residual of approximately 0.3 W/m² (1σ). This implies that energy anomalies greater than 0.3 W/m² can be tracked within the ocean system between TOA and 2000 m depth thanks to their signature on the Earth deformation.
How to cite: Blazquez, A., Meyssagnac, B., Fourest, S., and Duvignac, T.: Satellite gravimetry and altimetry combined with in-situ ocean temperature profiles enable to close the Earth energy budget and track yearly global energy anomalies from top of the atmosphere to the ocean, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-6539, https://doi.org/10.5194/egusphere-egu26-6539, 2026.
Permanent stations of the Global Positioning System (GPS) enable the registration of elastic deformations of the Earth’s surface that occur in response to variations in hydrological mass loads over continental areas. Analysis of long-term changes in displacements observed by a set of GPS permanent stations allows for the identification of deformations induced by long-term changes of the Terrestrial Water Storage (TWS). Densely distributed GPS stations provide adequate spatial coverage for regional scale analysis and their exact spatio-temporal analysis. We use a set of vertical displacements for the period 2010-2020 observed by 493 GPS permanent stations situated in Poland and neighboring regions, whose observations were processed by the Nevada Geodetic Laboratory (NGL). 213 of these stations exhibit more than 80% of temporal coverage with Gravity Recovery and Climate Experiment (GRACE) and GRACE Follow-On satellite missions. We use these vertical displacements and invert them using elastic Earth theory and load Love numbers to infer trends of TWS in Poland. The obtained results were compared with independent estimates of TWS trends derived from the GRACE and GRACE Follow-On missions, and other external datasets. The analysis demonstrates that GPS-observed vertical displacements provide a reliable source of information for the assessment of TWS trends in Poland.
How to cite: Kłos, K., Klos, A., and Lenczuk, A.: A study of the potential for using trends of GPS displacements to determine TWS trends in Poland, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-9761, https://doi.org/10.5194/egusphere-egu26-9761, 2026.
Accurate estimation of vertical land motion in Antarctica is crucial for understanding glacial isostatic adjustment (GIA), ice mass change, and sea-level rise. However, Global Navigation Satellite System (GNSS) position time series are affected by non-tidal loading (NTL), which can obscure geophysical signals and bias trend estimates. In this study, we evaluate the performance of 11 NTL model combinations from EOST (École & Observatoire des Sciences de la Terre, Strasbourg) and ESMGFZ (Earth System Modelling Group, GFZ Potsdam) in correcting vertical GNSS time series at three East Antarctic stations in Dronning Maud Land. We analyse five GNSS solutions processed with different strategies, including precise point positioning (PPP), double-difference (DD) network solutions, and a combined product.
Our results show that NTL corrections improve time series quality in PPP-based solutions, reducing root mean square (RMS), coloured noise, and seasonal amplitudes by more than 20 % at some sites. In contrast, network-based and combined solutions exhibit limited improvements, and in some cases, corrections introduced additional variability. Among loading components, non-tidal atmospheric loading (NTAL) consistently produces the largest reductions, while additional non-tidal oceanic (NTOL) and hydrological loading (HYDL) contributions are beneficial mainly in specific GFZ model combinations applied to PPP datasets.
Our findings demonstrate that both GNSS processing strategy and NTL model choice can affect inferred vertical trends, and in some cases even change their sign. Our evaluation provides a regional assessment of widely used NTL products under Antarctic conditions, with direct implications for GIA modelling and reference frame realisation, and supports the development of more robust correction strategies for future Antarctic GNSS studies.
How to cite: Schulz, A., Ejigu, Y. G., Näränen, J., and Nordman, M.: Impact of non-tidal loading corrections and processing strategy on Antarctic GNSS vertical time series, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-10838, https://doi.org/10.5194/egusphere-egu26-10838, 2026.
Our analysis presents 10-day water mass solutions estimated from both GRACE and GRACE-FO KBR Range (KBRR) residuals for continental hydrology using GINS software developed by the CNES/GRGS group. The inter-satellite velocity residuals have been converted into along-track differences of gravity potential using the energy balance approach. Maps of Equivalent Water Height (EWH) are obtained by inversion of these potential differences onto juxtaposed surface elements over the region of interest or time coefficients of designed orthogonal Slepian functions. This latter band-limited representation offers the advantage of reducing drastically the number of parameters to be fitted and the computation time. We also used another type of orthogonal basis functions, as well as decomposition using anisotropic wavelets. These functions require larger computing resources but have the advantage of being adapted to the shape of the studied watersheds for improving hydrology variation survey locally. All of these regional solutions are compared to spherical harmonics and mascons series of existing Level-2 solutions for validation. The patterns shown in the proposed regional solutions reveal dominant seasonal cycles of water mass in the large tropical basins (e.g. Amazon, Nil and Congo), as well as extreme events such as floods and droughts.
How to cite: Seoane, L., Ramillien, G., and Darrozes, J.: Multi-year regional water mass solutions by inversion of hydrology-related GRACE(-FO) KBRR residuals, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-10903, https://doi.org/10.5194/egusphere-egu26-10903, 2026.
The upcoming MAGIC (Mass Change and Geoscience International Constellation) mission aims to extend the current record of mass change observations with higher spatiotemporal resolution data. This study evaluates the potential of terrestrial water storage (TWS) observations from MAGIC in improving our understanding of the coupled water, energy, and carbon cycles.
Using a synthetic data assimilation experiment, we integrate simulated MAGIC TWS data into a high-resolution (3 km) land surface model over two European study areas. These regions are selected for their strong land-atmosphere coupling, providing suitable test cases for investigating whether and how improvements in soil moisture profiles and snow cover from TWS assimilation translate to improved estimates in energy and carbon cycle variables. Our research addresses two primary objectives: (i) quantifying the added benefit of assimilating TWS changes in constraining model states, such as land surface temperature and vegetation growth, relative to a known reference, and (ii) investigating how the increased resolution of MAGIC supports an improved representation of land-atmosphere coupling, particularly during extreme drought events, using ecosystem-scale water use efficiency (the ratio of gross primary productivity to evapotranspiration) as a diagnostic of vegetation response.
How to cite: Nitschke, A., Kusche, J., and Hendricks Franssen, H.-J.: Improving the representation of water, energy and carbon cycles in land surface modelling: Assimilation of MAGIC TWSA data, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-12466, https://doi.org/10.5194/egusphere-egu26-12466, 2026.
The Svalbard Archipelago, located in the Arctic region of Norway, is extremely vulnerable to the climate change. With a current increase of 3 at 5°C in average air temperature and a change in precipitation with an increasing proportion of rain, certain negative consequences for the environment and ecosystem are inevitable. One of the most obvious signs of climate change in this region is the melting of ice, which is causing the Earth’s crust to deform. But there are other consequences, such as the loss of sea ice cover, changes in how sediment is transported and also changes in biodiversity.
These phenomena are widely studied in this region. For example, deformation of the Earth’s crust is determined using 3D positioning data acquired by GNSS across Svalbard, particularly in Ny-Alesund. Since 2000, daily positioning time series show a strong upward component, with an average vertical velocity of between 8 to 13 mm/yr. This velocity is the Earth’s response to various episodes of glaciation and deglaciation in the past like the last glacial maximum or the Little Ice Age, and to the current melting of ice. This current melting has also been studied a lot at Ny-Alesund station, where glaciers are monitored to measure changes in ice height from one year to the next and calculate the glacier’s surface mass balance. This is the case for the Austre Lovenbreen, for which data has been available since 2007, showing record melting over the last ten years. The same is true for the study of the prodeltas evolution since 2009, which shows a stabilisation of almost all prodeltas since 2016.
All these phenomena are largely studied separately, but our analysis consists of interpreting all this data in order to study the possible correlation between these observations which share the same cause: climate change. In our study, we ask how we can link measurements taken at the glacier or in the underwater sediment, along with space geodesy data, to better understand the ongoing geophysical processes that mark the transition between a glacial environment and paraglacial environment.
How to cite: Tafflet, A., Nicolas, J., Baltzer, A., Verdun, J., Tolle, F., Bernard, E., and Friedt, J.-M.: Study of changes induced by global warming in Svalbard based on spatial geodetic data and in situ geophysical measurements, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-12707, https://doi.org/10.5194/egusphere-egu26-12707, 2026.
The Gravity Recovery and Climate Experiment (GRACE) and its follow-on mission (GRACE-FO) have been providing spaceborne observations of terrestrial water storage (TWS) changes since 2002. These observations help to understand how water fluxes change in an intensifying water cycle at watershed scales. However, the accuracy of the derived TWS anomalies depends on the choice of spatial and spectral filtering methods, which can attenuate their amplitude.
In this poster, we present our filter-free inversion scheme that estimates TWS anomalies at watershed scales from Level-2 Stokes coefficients together with their associated full error covariance matrices. We apply the scheme to the watersheds in the Greater Horn of Africa and compare the obtained TWS anomalies with the accumulated watershed-wide precipitation and evapotranspiration fluxes from the ERA5 atmospheric reanalysis, and the accumulated river discharge from GLOFAS and GEOGLOWS products. We further assess the consistency between the temporal derivatives of TWS anomalies and the corresponding water fluxes. Additionally, we quantify mass deficits and surpluses in TWS anomalies and investigate the relative contributions of atmospheric net flux (i.e., precipitation minus evapotranspiration) and river discharge to the magnitude of TWS anomalies during drought and flood events.
How to cite: Karimi, S., Rietbroek, R., Penning de Vries, M., and van der Tol, C.: Quantifying mass signatures of drought and flood events using water fluxes and terrestrial water storage anomalies, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-12852, https://doi.org/10.5194/egusphere-egu26-12852, 2026.
Antarctica plays a central role in Earth's global climate system and stores most of the planet's freshwater. However, due to the continent's remoteness and extreme conditions, reliable in situ observations of snow accumulation remain rare. This gap in measurements makes it difficult to constrain ice sheet models and accurately project Antarctica's contribution to global sea level rise. In particular, regions such as the Totten Glacier in East Antarctica are of interest due to the significant mass loss since the 1990s, dominated by changes in coastal ice dynamics. In the context of Antarctica, GNSS Interferometric Reflectometry (GNSS-IR) presents an efficient and sustainable approach to monitor changes in snow accumulation with the potential to offer insights into regional surface mass balance models.
This contribution investigates a unique in situ dataset of six GNSS stations deployed on the Totten Glacier, operated seasonally between November 2016 and January 2019. These stations were originally designed to track ice motion, but they also capture reflections from the snow surface. By applying GNSS-IR, time series of snow accumulation are generated – once with the traditional retrieval approach using the gnssrefl software, and once by testing a novel machine learning-based retrieval framework. The derived snow accumulation time series are cross-referenced with outputs from regional surface mass balance models. The results provide insights into the spatio-temporal patterns of snow accumulation over the Totten Glacier and showcase the potential of GNSS-IR for environmental sensing.
How to cite: Crocetti, L., Watson, C., Schartner, M., and King, M.: Snow Accumulation Monitoring using GNSS-Interferometric Reflectometry for Antarctica, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-15089, https://doi.org/10.5194/egusphere-egu26-15089, 2026.
Satellite gravimetry has revolutionized the observation of shifts in terrestrial water storage (TWS) in reponse to climate and human activities. Robust detection and attribution of these changes remain a challenge because TWS exhibits strong seasonal variability and is traditionally observed at coarse spatial and temporal resolution. Recent studies have shown that direct regression of Level-1B observations (inter-satellite range data) from the Gravity Recovery and Climate Experiment (GRACE) and its Follow-On mission (GRACE-FO) can substantially improve effective spatial resolution of regression terms, compared to popular monthly mascon products. Applying this framework, we demonstrate that stacked Level-1B regression yields spatially refined estimates of both long-term TWS trends and seasonal amplitude, improving the ability to identify regions where human land and water use alter local freshwater availability. For trend analysis, the enhanced resolution strengthens attribution of storage change to anthropogenic drivers such as irrigation, groundwater extraction, reservoir operations, and land-use change at sub-basin scales. For seasonal characterization, we show that assuming simplified representations of the annual cycle, such as stationary, symmetric, or unimodal seasonality, can enable robust recovery of mean annual TWS amplitude with substantially reduced signal attenuation and leakage. Such refinements are particularly important for applications that depend on accurate annual water budgets, including water-balance-based evapotranspiration estimation and assessments of interannual hydroclimatic variability. The spatial scale at which GRACE satellites can independently observe water resources will continue to improve as additional years of measurements become available.
How to cite: O'Neill, M. M., Rodell, M., and Loomis, B.: Spatially refined global terrestrial water storage trends and annual cycles from GRACE and GRACE-FO, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-16019, https://doi.org/10.5194/egusphere-egu26-16019, 2026.
Since 1992, surface elevation change estimates of the Antarctic Ice Sheet (AIS) have been derived from satellite radar altimetry. However, large uncertainties remain due to local topography and the time-variable signal penetration into snow and firn. The unprecedented accuracy of measurements from the ICESat-2 satellite laser altimetry mission, launched in 2018, now enables inter-comparison with radar altimetry results. The primary goal of this study is to improve understanding of the uncertainties in AIS volume and mass balance estimates by quantifying how results from ICESat-2 and the CryoSat-2 radar altimetry mission diverge under different processing regimes. To do so, we analyse coincident ICESat-2 and CryoSat-2 measurements over the 6.9 million km² area of the relatively flat and large AIS interior, where topography-related errors are small. We apply a suite of state-of-the-art correction methods to the CryoSat-2 measurements, including multiple retracking algorithms and empirical corrections for the time-variable surface and volume scattering of the radar signal. From April 2019 to October 2024, ICESat-2 observations show a thickening of 97 ± 4 km3 yr−1, coincident with excess snowfall in this period. CryoSat-2 solutions indicate systematically lower thickening rates than ICESat-2. The smallest bias (0.6 ± 1.0 cm yr−1 or 42 km3 yr−1) between the results from the two missions is found when using the AWI-ICENet1 convolutional neural network retracker. One of our hypotheses is that the systematic radar-laser differences might be due to residual errors related to the time-variable radar penetration, particularly affected by the heavy snowfall events in recent years. While further work is needed to test this hypothesis, our study demonstrates both the challenges of resolving subtle, long-term surface mass balance trends using radar altimetry and the value of joint laser-radar analyses for improving AIS volume and mass balance estimates.
How to cite: Kappelsberger, M. T., Nilsson, J., Horwath, M., Helm, V., Gardner, A. S., and Willen, M. O.: Uncertainties in Antarctic elevation change estimates by comparing radar and laser altimetry, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-18146, https://doi.org/10.5194/egusphere-egu26-18146, 2026.
The closure of the Sea Level Budget (SLB) is a key challenge for modern physical oceanography. First, it is essential that we ensure the proper identification and quantification of each significant contributor to sea level change through this closure. Second, it provides an efficient means to closely monitor and cross-validate the performance of intricate global observation systems, such as the satellite altimetry constellation, satellite gravimetry missions (GRACE/GRACE-FO), and the Argo in-situ network. Third, this closure reveals to be a beneficial approach for assessing how well the observed climate variables, such as sea level, barystatic sea level, temperature and salinity, land ice melt, and changes in land water storage, comply with conservation laws, in particular those related to mass and energy.
In this presentation, we will discuss the state of knowledge of global mean and regional sea level budget with up-to-date observations, encompassing 1) an up-to-date assessment of the budget components and residuals, along with their corresponding uncertainties, spanning from 1993 to 2023 in global mean and throughout the GRACE and Argo era for spatial variations; 2) the identification of the periods and areas where the budget is not closed, i.e. where the residuals are significant; 3) advancements in the analysis and understanding of the spatial patterns of the budget residuals.
To investigate the sea level budget (SLB) misclosure, we developed an objective solution that closes the SLB globally. This approach is based on an inverse method that optimally combines the contributions to sea level, weighted by their estimated instrumental uncertainties, and draws from publications such as those by Rodell et al. (2015) and L’Ecuyer et al. (2015).
This objective method allows us to precisely identify the dates when the SLB misclosure falls outside the uncertainty estimates, as well as the contributor most likely responsible for the discrepancy. The results of this analysis will be detailed during the presentation.
A focus will be made on the North Atlantic Ocean where the residuals are significantly high. We investigate the potential errors causing non-closure in each of the components (e.g., in situ data sampling for the thermosteric component, geocenter correction in the gravimetric data processing) as well as potential inconsistencies in their processing that may impact large-scale patterns (e.g., centre of reference and atmosphere corrections).
This work is performed within the framework of the Sea Level Budget Closure Climate Change Initiative (SLBC_cci+) programme of the European Space Agency (https://climate.esa.int/en/projects/sea-level-budget-closure/). This project was initiated by the International Space Science Institute Workshop on Integrative Study of Sea Level Budget (https://www.issibern.ch/workshops/sealevelbudget/).
How to cite: Bouih, M., Fraudeau, R., Pfeffer, J., Ferrari, R., Ablain, M., Cazenave, A., Meyssignac, B., Blazquez, A., Horwath, M., Bamber, J., Bonaduce, A., Raj, R., Leroux, S., Kolodziejczyk, N., Llovel, W., Spada, G., Storto, A., Yang, C., and Oulhen, E. and the ESA SLBC CCI+ team: How is the global and regional sea level budget closed from the latest observations? , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-18774, https://doi.org/10.5194/egusphere-egu26-18774, 2026.
