Search Results (39)

Determining long-term changes in global ice and water storage from satellite gravimetry remains challenging due to the limited temporal coverage of high-resolution missions. Here, we combine Satellite Laser Ranging (SLR) and Gravity Recovery and Climate Experiment (GRACE) data to reconstruct large-scale, non-linear mass variations from 1995 to 2024, extending gravity-based observations into the pre-GRACE era while preserving spatial detail through backward extrapolation. The combined model reveals widespread and statistically significant accelerations in global water and ice mass changes and enables the identification of key turning points in their temporal evolution. Results indicate that in Svalbard, a non-linear transition in ice mass balance occurred in late 2004, followed by a pronounced acceleration of mass loss due to climate warming. Glaciers in the Gulf of Alaska exhibit persistent mass loss with a marked intensification after 2012, while in the Antarctic Peninsula, ice mass loss substantially slowed and a potential trend reversal emerged around 2021. The reconstructed mass anomalies show strong consistency with independent satellite altimetry and climate indicators, including a clear response to the 1997/1998 El Niño event prior to the GRACE mission. These findings demonstrate that integrating SLR with GRACE enables robust detection of non-linear, climate-driven mass redistribution on a global scale and provides a physically consistent extension of satellite gravimetry records beyond the GRACE era. Full article

Monitoring groundwater dynamics and basin-scale water budget closure is critical for sustainable water resource management, especially in regions facing climate stress and overexploitation. This study examines the temporal variability of total water storage and groundwater trends in Türkiye’s Kızılırmak River Basin by integrating GRACE/GRACE-FO satellite gravimetry, GLDAS-Noah land surface model outputs, ERA5-Land reanalysis products, and local meteorological observations. Groundwater storage anomalies (GWSAs) were derived from the difference between GRACE-based total water storage anomalies (TWSAs) and GLDAS-modeled surface storage components, revealing a long-term groundwater depletion trend of −9.55 ± 2.6 cm between 2002 and 2024. To investigate the hydrological drivers of these changes, lagged correlation analyses were performed between GRACE TWSA and ERA5-Land variables (precipitation, evapotranspiration, runoff, soil moisture, and temperature), showing time-shifted responses from −3 to +3 months. The strongest correlations were found with soil moisture (CC = 0.82 at lag −1), temperature (CC = −0.70 at lag −3), and runoff (CC = 0.71 at lag 0). A moderate correlation between GRACE TWSA and ERA5-based water storage closure (CC = 0.54) indicates partial alignment. These findings underscore the value of satellite gravimetry in tracking subsurface water changes and support its role in basin-scale hydrological assessments. Full article

Groundwater is a critical yet understudied resource in Peru, where surface water has traditionally dominated national assessments. This study provides the first country-scale analysis of groundwater storage (GWS) variability in Peru from 2003 to 2023 using satellite gravimetry data from the Gravity Recovery and Climate Experiment (GRACE) and GRACE Follow-On (GRACE-FO) missions. We used the GRACE Data Assimilation-Data Mass Modeling (GRACE-DA-DM GLV3.0) dataset at 0.25° resolution to estimate annual GWS trends and evaluated the influence of El Niño–Southern Oscillation (ENSO) events and anthropogenic extraction, supported by in situ well data from six major aquifers. Results show a sustained GWS decline of 30–40% in coastal and Andean regions, especially in Lima, Ica, Arequipa, and Tacna, while the Amazon basin remained stable. Strong correlation (r = 0.95) between GRACE data and well records validate the findings. Annual precipitation analysis from 2003 to 2023, disaggregated by climatic zone, revealed nearly stable trends. Coastal El Niño events (2017 and 2023) triggered episodic recharge in the northern and central coastal regions, yet these were insufficient to reverse the sustained groundwater depletion. This research provides significant contributions to understanding the spatiotemporal dynamics of groundwater in Peru through the use of satellite gravimetry data with unprecedented spatial resolution. The findings reveal a sustained decline in GWS across key regions and underscore the urgent need to implement integrated water management strategies—such as artificial recharge, optimized irrigation, and satellite-based early warning systems—aimed at preserving the sustainability of the country’s groundwater resources. Full article

To address the limited inversion accuracy caused by low-fidelity data in satellite gravimetry, this study proposes a data preprocessing framework based on iterative residual correction. Utilizing Level-1B observations from the Gravity Recovery and Climate Experiment Follow-On (GRACE-FO) satellite (January 2020), outliers were systematically detected and removed, while data gaps were compensated through spline interpolation. Experimental results demonstrate that the proposed method effectively mitigates data discontinuities and anomalous perturbations, achieving a significant improvement in data quality. Furthermore, a 60-order Earth gravity field model derived via the energy balance approach was validated against contemporaneous models published by the University of Texas Center for Space Research (CSR), German Research Centre for Geosciences (GFZ), and Jet Propulsion Laboratory (JPL). The results reveal a two-order-of-magnitude enhancement in inversion precision, with model accuracy improving from 10⁻⁶–10⁻⁷ to 10⁻⁸–10⁻⁹. This method provides a robust solution for enhancing the reliability of gravity field recovery in satellite-based geodetic missions. Full article

There are serious ecological and environmental risks associated with groundwater level decline, particularly in areas with little in situ monitoring. In order to monitor and assess the resilience and dependability of groundwater storage, this paper proposes a solid methodology that combines data from land surface models and satellite gravimetry. In particular, the GRACE Groundwater Drought Index (GGDI) is used to analyze the estimated groundwater storage anomalies (GWSA) from the Gravity Recovery and Climate Experiment (GRACE) and the Global Land Data Assimilation System (GLDAS). Aquifer resilience, or the likelihood of recovery after stress, and aquifer reliability, or the long-term probability of remaining in a satisfactory state, are calculated using the core method. The two main components of the methodology are (a) calculating GWSA by subtracting the surface and soil moisture components from GLDAS, total water storage from GRACE, and comparing the results to in situ groundwater level data; and (b) standardizing GWSA time series to calculate GGDI and then estimating aquifer resilience and reliability based on predetermined threshold criteria. Using this framework, we validate GRACE-derived GWSA with in situ observations in eight sub-basins of the Chao Phraya River (CPR) basin, obtaining Pearson correlation coefficients greater than 0.82. With all sub-basins displaying values below 35%, the results raise significant questions about resilience and dependability. This method offers a framework that can be applied to assessments of groundwater sustainability worldwide. Full article

The Earth’s time-variable gravity field holds significant research and application value. However, satellite gravimetry missions such as GRACE and GRACE-FO face limitations in spatial resolution when detecting monthly gravity fields, while traditional radar altimeters lack the observational efficiency needed for monthly gravity anomaly inversion. These limitations hinder further exploration and application of the Earth’s time-variable gravity field. Leveraging its advantages, such as rapid global coverage, high revisit frequency, and low cost for constellation formation, spaceborne GNSS-R technology holds the potential to address the observational efficiency gaps of traditional radar altimeters. This study presents the first assessment of the capability of spaceborne GNSS-R interferometric altimetry for high spatial resolution monthly marine gravity anomaly inversion through simulations. The results indicate that under the PARIS Operational scenario of a single GNSS-R satellite (a spaceborne GNSS-R interferometric altimetry scenario proposed by Martin-Neira), a 30′ grid resolution marine gravity anomaly can be inverted with an accuracy of 4.93 mGal using one month of simulated data. For a dual-satellite constellation, the grid resolution improves to 20′, achieving an accuracy of 4.82 mGal. These findings underscore the promise of spaceborne GNSS-R interferometric altimetry technology for high spatial resolution monthly marine gravity anomaly inversion. Full article

Permafrost thawing is potentially a crucial but poorly investigated factor that influences vegetation dynamics in the Arctic. We studied the permafrost thaw rate beyond the Polar Circle in Siberia. We analyzed its influence on the larch (Larix spp.) growth and Arctic vegetation (sparse larch forests, tundra, and forest–tundra communities) productivity (NPP). We checked the following hypotheses: (1) satellite gravimetry is valid for permafrost thawing analysis; (2) meltwater runoff stimulated trees’ growth and NPP. We used satellite (GRACE, Terra/MODIS) and field data, and larch tree radial growth index measurements. We found a continuous negative trend in the terrestrial water content (r² = 0.67) caused by permafrost thawing beyond the Polar Circle. Runoff is maximal in West and Mid Siberia (9.7 ± 2.9 kg/m²/y) and decreases in the eastward direction with minimal values in the Chukotka Peninsula sector (−2.9 ± 3.2 kg/m²/y). We found that the growth increment of larch trees positively correlated with meltwater runoff (0.5…0.6), whereas the correlation with soil water content was negative (−0.55…−0.85). Permafrost thawing leads to an increase in the Arctic vegetation productivity. We found a positive trend in NPP throughout the Siberian Arctic (r² = 0.30). NPP negatively correlated with soil water content (r = −0.55) and positively with meltwater runoff (West Siberia, r = 0.7). An increase in VPD (vapor pressure deficit) and air and soil temperatures stimulated the larch growth and vegetation NPP (r = 0.5…0.9 and r = 0.6…0.9, respectively). Generally, permafrost degradation leads to improved hydrothermal conditions for trees and vegetation growth and contributes to the preservation of the Arctic as a carbon sink despite the increase in burning rate. Full article

We use data from the Gravity Recovery and Climate Experiment and its Follow-On mission (GRACE/GRACE-FO) from April 2002 to December 2022 to analyze interannual glacial mass changes in High Mountain Asia (HMA) and its subregions and their driving factors. Glacial mass changes in the HMA subregions show clear regional characteristics. Interannual glacial mass changes in the HMA region are closely related to interannual oscillations of precipitation and temperature, and are also correlated with El Niño–Southern Oscillation (ENSO). Glacial mass changes in the regions (R1–R6) are dominated by precipitation, and ENSO affects interannual glacial mass changes mainly by affecting precipitation. In region (R7) and region (R8), the glacial mass changes are mainly controlled by temperature. ENSO also affects the interannual glacial mass changes by affecting interannual changes in temperature. The interannual glacial mass changes in regions (R9–R11) are jointly dominated by temperature and precipitation, and also related to ENSO. Another interesting finding of this study is that glacial mass changes in the western part of HMA (R1–R6) show a clear 6–7-year oscillation, strongly correlated with a similar oscillation in precipitation, while in the eastern part (R9–R11), a 2–3-year oscillation was found in both glacial mass change and precipitation, as well as temperature. These results verify the response of interannual HMA glacial mass changes to climate processes, crucial for understanding regional climate dynamics and sustainable water resource management. Full article

The conventional average acceleration approach relies on K-band range observation, containing an unknown bias, which leads to possible degradation of the precision of Earth’s gravity field modelling. It also suffers from correlated errors caused by three-point numerical differentiation. In this study, an improved approach is proposed that makes use of K-band range-rate observations instead and overcoming the influence of correlated errors by introducing a whitening filter. GRACE-Follow On data spanning the period from January 2019 to December 2022 were processed by the proposed approach and a series of time-varying gravity field models was derived, referred to as SSM-AAA-GFO in this paper. This model series is compared comprehensively with three official model series. Results demonstrate that all model series are highly coincident below degree 30 and reflect similar time-varying gravity field signals in both large and small basins. After filtering, SSM-AAA-GFO shows uncertainty, in the form of equivalent water height below 2.5 cm, which is comparable with three official model series. The comparison results confirm the effectiveness of the proposed approach for precisely modelling a time-varying gravity field based on K-band range-rate observations. Full article

The monitoring of Poyang Lake water area and storage changes using remote sensing and satellite gravimetry techniques is valuable for maintaining regional water resource security and addressing the challenges of global climate change. In this study, remote sensing datasets from Landsat images (Landsat 5, 7, 8 and 9) and three Gravity Recovery and Climate Experiment (GRACE) and Gravity Follow-on (GRACE-FO) mascon solutions were jointly used to evaluate the water area and storage changes in response to global and regional climate changes. The results showed that seasonal characteristics existed in the terrestrial water storage (TWS) and water area changes of Poyang Lake, with nearly no significant long-term trend, for the period from April 2002 to December 2022. Poyang Lake exhibited the largest water area in June and July every year and then demonstrated a downward trend, with relatively smaller water areas in January and November, confirmed by the estimated TWS changes. For the flood (August 2010) and drought (September 2022) events, the water area changes are 3032 km² and 813.18 km², with those estimated TWS changes 17.37 cm and −17.46 cm, respectively. The maximum and minimum Poyang Lake area differences exceeded 2700 km². The estimated terrestrial water storage changes in Poyang Lake derived from the three GRACE/GRACE-FO mascon solutions agreed well, with all correlation coefficients higher than 0.92. There was a significant positive correlation higher than 0.75 between the area and TWS changes derived from the two independent monitoring techniques. Therefore, it is reasonable to conclude that combined remote sensing with satellite gravimetric techniques can better interpret the response of Poyang Lake to climate change from the aspects of water area and TWS changes more efficiently. Full article

Dynamic topography (DT) refers to the time-varying component of the sea surface height influenced by factors like ocean currents, temperature, and salinity gradients. Accurate estimation of DT is crucial for comprehending oceanic circulation patterns and their impact on climate. This study introduces two approaches to estimating DT: (1) utilizing satellite altimetry to directly observe sea surface height and (2) considering the steric and non-steric components of sea level anomalies. The steric term is calculated using salinity and temperature data obtained from local buoy data, Argo observations, and the World Ocean Atlas model. The non-steric term is calculated using GRACE Satellite gravimetry data. To estimate the assimilated DT, four methods are utilized, including variance component estimation (VCE), Bayesian theory, Kalman filter, and 3D variational (3DVAR). These methods assimilate the two aforementioned schemes. The validity of the estimated DT is assessed by comparing the calculated sea surface current, derived from the obtained DT, with observations from local current meter stations. The results indicate that the VCE method outperforms other methods in determining the final DT. Furthermore, incorporating the steric and non-steric terms of sea level in determining DT in coastal areas enhances the accuracy of estimating sea surface currents. Full article

During gravity field modeling, the conventional acceleration approach rarely incorporates KBR inter-satellite range rate data from the GRACE mission. To propose an improved acceleration method, this study introduces initial orbital position and velocity vectors to be estimated along with a combination of Cowell, KSG, and Adams integrators. In addition to achieving a full-rank design matrix regarding orbit corrections when constructing observation equations, the proposed method is capable of utilizing range rate observations for gravity field estimation. To verify the reliability of this approach, GRACE data from April 2002 to December 2016 was used to calculate a time series of monthly gravity solutions up to a degree and order of 96, referred to as Tongji-Acc RL06 in this paper. The computed time series are compared with the official models (i.e., CSR RL06, GFZ RL06, and JPL RL06) in terms of geoid degree variances, signal contents over distinct areas, and noise levels in desert regions. The investigations lead to the following conclusions: (a) the geoid degree variances indicate that Tongji-Acc RL06 exhibits comparable signal levels (approximately below 20 degrees) to the other three models while demonstrating lower noise at higher degrees (above 40 degrees); (b) the analysis over the globe, typical river basins, and land–ice regions illustrates that the solutions derived using the proposed acceleration method agree well with the official models based on the dynamic approach; (c) especially over the two large-scale river basins (i.e., Amazon and Zambezi) and another two small-scale river basins (i.e., Tennessee and Irrawaddy), Tongji-Acc RL06 significantly improves the SNR values; and (d) in the cases of the Sahara and Karakum deserts, Tongji-Acc RL06 achieves noise reductions of over 55.8% and 61.5% relative to CSR RL06, respectively. In general, the signal and noise analyses demonstrate that the proposed acceleration-based approach can effectively extract gravity field signals from KBR inter-satellite range rate observations with improved SNR, while significantly reducing the high-frequency noise. Full article

Earthquakes at depths of ≥300 km are generally called deep-focus earthquakes. Only two deep-focus earthquakes with Mw 8.0 or more have occurred in this century—the 2013 Okhotsk earthquake (Mw 8.3) and the 2018 Fiji earthquake (Mw 8.2) on 19 August 2018. However, the 2018 Fiji earthquake was only reported on seismographs, and the related crustal deformations were not observed by the Global Navigation Satellite System because the observation network did not exist around the epicenter. This study analyzed the time series of gravity data observed by the Gravity Recovery And Climate Experiment (GRACE) and its successor, GRACE Follow-On, and detected the spatial distribution of coseismic gravity changes mainly due to crustal deformation by the 2018 Fiji earthquake. The results in this study were not consistent with the numerical calculation of gravity changes when using the fault parameters estimated by the data of seismic waves. Thus, numerical calculations were used to construct a uniform slip rectangle fault model to explain coseismic gravity changes and provide a spatial distribution map of crustal deformation. However, this fault model is only based on gravity changes; thus, new research combining satellite gravimetry and seismic wave data will be necessary in the future. Full article

Gravimetry measurements from the GRACE and GRACE-Follow-On satellites provide observations of ocean bottom pressure (OBP), which can be differenced between basin boundaries to infer mass transport variability at a given level in the deep ocean. However, GRACE data products are limited in spatial resolution, and conflate signals from many depth levels along steep continental slopes. To improve estimates of OBP variability near steep bathymetry, ocean bottom pressure observations from a JPL GRACE mascon product are downscaled using an objective analysis procedure, with OBP covariance information from an ocean model with horizontal grid spacing of ∼18 km. In addition, a depth-based adjustment was applied to enhance correlations at similar depths. Downscaled GRACE OBP shows realistic representations of sharp OBP gradients across bathymetry contours and strong currents, albeit with biases in the shallow ocean. In validations at intraannual (3–12 month) timescales, correlations of downscaled GRACE data (with depth adjustment) and in situ bottom pressure recorder time series were improved in ∼79% of sites, compared to correlations that did not involve downscaled GRACE. Correlations tend to be higher at sites where the amplitude of the OBP signal is larger, while locations where surface eddy kinetic energy is high (e.g., Gulf Stream extension) are more likely to have no improvement from the downscaling procedure. The downscaling procedure also increases the amplitude (standard deviation) of OBP variability compared to the non-downscaled GRACE at most sites, resulting in standard deviations that are closer to in situ values. A comparison of hydrography-based transport from RAPID with estimates based on downscaled GRACE data suggests substantial improvement from the downscaling at intraannual timescales, though this improvement does not extend to longer interannual timescales. Possible efforts to improve the downscaling technique through process studies and analysis of alongtrack GRACE/GRACE-FO observations are discussed. Full article

During its science phase from 2002–2017, the low-low satellite-to-satellite tracking mission Gravity Field Recovery And Climate Experiment (GRACE) provided an insight into Earth’s time-variable gravity (TVG). The unprecedented quality of gravity field solutions from GRACE sensor data improved the understanding of mass changes in Earth’s system considerably. Monthly gravity field solutions as the main products of the GRACE mission, published by several analysis centers (ACs) from Europe, USA and China, became indispensable products for quantifying terrestrial water storage, ice sheet mass balance and sea level change. The successor mission GRACE Follow-On (GRACE-FO) was launched in May 2018 and proceeds observing Earth’s TVG. The Institute of Geodesy (IfE) at Leibniz University Hannover (LUH) is one of the most recent ACs. The purpose of this article is to give a detailed insight into the gravity field recovery processing strategy applied at LUH; to compare the obtained gravity field results to the gravity field solutions of other established ACs; and to compare the GRACE-FO performance to that of the preceding GRACE mission in terms of post-fit residuals. We use the in-house-developed MATLAB-based GRACE-SIGMA software to compute unconstrained solutions based on the generalized orbit determination of 3 h arcs. K-band range-rates (KBRR) and kinematic orbits are used as (pseudo)-observations. A comparison of the obtained solutions to the results of the GRACE-FO Science Data System (SDS) and Combination Service for Time-variable Gravity Fields (COST-G) ACs, reveals a competitive quality of our solutions. While the spectral and spatial noise levels slightly differ, the signal content of the solutions is similar among all ACs. The carried out comparison of GRACE and GRACE-FO KBRR post-fit residuals highlights an improvement of the GRACE-FO K-band ranging system performance. The overall amplitude of GRACE-FO post-fit residuals is about three times smaller, compared to GRACE. GRACE-FO post-fit residuals show less systematics, compared to GRACE. Nevertheless, the power spectral density of GRACE-FO and GRACE post-fit residuals is dominated by similar spikes located at multiples of the orbital and daily frequencies. To our knowledge, the detailed origin of these spikes and their influence on the gravity field recovery quality were not addressed in any study so far and therefore deserve further attention in the future. Presented results are based on 29 monthly gravity field solutions from June 2018 until December 2020. The regularly updated LUH-GRACE-FO-2020 time series of monthly gravity field solutions can be found on the website of the International Centre for Global Earth Models (ICGEM) and in LUH’s research data repository. These operationally published products complement the time series of the already established ACs and allow for a continuous and independent assessment of mass changes in Earth’s system. Full article