Gravity Recovery Research Articles

A novel Slepian approach for determining mass-term sea level from GRACE over the South China Sea

Treatment of land-to-ocean leakage is crucial in modeling the mass-term sea level (MSL) using the Gravity Recovery and Climate Experiment (GRACE) satellite gravity measurements. In this study, we utilized the Spherical Slepian functions (SSFs) to determine MSL variations in the South China Sea. A sensitivity simulation in terms of trend, annual amplitude, and phase revealed that the SSF solution with a 1° coastal buffer zone provides a better land-to-ocean leakage correction than traditionally used Spherical Harmonics (SH). It was also found that an additional smoothing procedure for SSF with low concentrating energy could significantly reduce the high-frequency noise in GRACE (e.g., the north–south strips). The spatiotemporal characteristics of the true MSL were further compared among GRACE SH and Mascon solutions, model-predicted ocean bottom pressure, and steric-corrected altimetric data (i.e., satellite-altimetric sea level minus steric effect). Results revealed that despite the SSF-inverted regional MSL solution being generally similar to other results, this technique notably recovered the realistic magnitude of detailed features. The apparent MSL signal was, for instance, precisely recovered in the central part of the Gulf of Thailand and the Sunda Shelf by the SSF, while the SH significantly underestimated it due to smoothing. In addition to the seasonality, the interannual signal decomposed from the SSF-inverted residual MSL (by removing the trend and periodic signals) was the strongest and well cross-correlated with the Southern Oscillation Index. With more detailed spatial patterns revealed by MSL from GRACE SSF, our findings demonstrate that SSF is more suitable for regional-scale studies.

Assessing GNSS hydrological monitoring capability across different climatic settings in China

Vertical position changes of ground-based Global Navigation Satellite System (GNSS) stations have been used to study regional terrestrial water storage (TWS) changes. However, the feasibility is still unclear in many areas due to diverse local effects. This study aims to evaluate the capability of GNSS vertical displacements in monitoring hydrological variations in four climate settings over Chinese mainland. The spatial and temporal variations of hydrological load-induced (HYDL) vertical displacements at 208 GNSS sites during 2011–2020 were analyzed by comparing with Gravity Recovery and Climate Experiment (GRACE)/GRACE Follow-On (GFO) and Global Land Data Assimilation System (GLDAS) derived TWS changes. The results indicate that GNSS vertical positions show different capabilities in capturing seasonal and non-seasonal hydrological dynamics in different climate regions. Among the four climatic settings, the subtropical monsoon climate (SMC) region, with the largest deformation fluctuation (the regional mean root mean square (RMS) is 7.97 mm), has the highest regional mean HYDL-GRACE and HYDL-GLDAS anti-correlation coefficients (CCs) of −0.47 and −0.45 at the seasonal scale, respectively. For the individual GNSS site, the number of the sites with CC <−0.40 between HYDL and GRACE/GLDAS-derived TWS changes accounts for 55.1% and 55.1% (SMC), 13.0% and 7.4% (temperate monsoon climate, TMC), 6.7% and 13.3% (temperate continental climate, TCC), 32.3% and 38.7% (plateau climate, PC), respectively. For the non-seasonal term, although the proportion with CC <−0.40 in each climate type decreases mainly due to the influence of local geodynamic and human activities, especially in the SMC and PC regions, GNSS site vertical deformations still show good capability in monitoring hydrological extremes. The results provide valuable information for better application of GNSS to hydrology.

Assessing terrestrial water storage variations in Afghanistan using GRACE and FLDAS-Central Asia data

Study regionAfghanistan, Central Asia. Study focusIn this study, we evaluated the terrestrial water storage dynamics in Afghanistan and its five major river basins using the terrestrial water storage anomalies (TWSA) from three Gravity Recovery and Climate Experiment (GRACE) mascons observations from JPL, CSR, and GSFC processing centers, and the Famine Early Warning Systems Network (FEWS NET) Land Data Assimilation System – Central Asia (FLDAS-CA) simulation. New hydrological insights for the regionsSince 2008, due to intense and prolonged drought conditions and groundwater overexploitation, TWS in Afghanistan has been decreasing at an alarming rate. The average slopes of the TWSA trend in Afghanistan for the GRACE period (2003–2016) of the three products range between − 3.6 to − 4.8 mm/year. The decrease in TWS is further exacerbated during the GRACE-FO period (2019–2022), ranging between − 20.4 to − 30 mm/year. Because groundwater is heavily relied on in the country but human-induced change (i.e., groundwater extraction) is not simulated in FLDAS-CA, a significant difference could be observed between GRACE observations and FLDAS-CA results, especially following after each severe drought event (e.g., 2008, 2018) when substantial groundwater extraction occurred. The assimilation of GRACE observations into the FLDAS-CA framework will undoubtedly have a positive impact for decision-makers and local stakeholders in preparing and mitigating the impacts of drought and groundwater overexploitation in Afghanistan and Central Asia.

Effect of Polar Cap Patches on the High‐Latitude Upper Thermospheric Winds

AbstractThis study focuses on the poorly known effect of polar cap patches (PCPs) on the ion‐neutral coupling in the F‐region. The PCPs were identified by total electron content measurements from the Global Navigation Satellite System (GNSS) and the ionospheric parameters from the Defense Meteorological Satellite Program spacecraft. The EISCAT incoherent scatter radars on Svalbard and at Tromsø, Norway observed that PCPs entered the nightside auroral oval from the polar cap and became plasma blobs. The ionospheric convection further transported the plasma blobs to the duskside. Simultaneously, long‐lasting strong upper thermospheric winds were detected in the duskside auroral oval by a Fabry‐Perot Interferometer (FPI) at Tromsø and in the polar cap by the Gravity Recovery and Climate Experiment satellite. Using EISCAT ion velocities and plasma parameters as well as FPI winds, the ion drag acting on neutrals and the time constant for the ion drag could be estimated. Due to the arrival of PCPs/blobs and the accompanied increase in the F‐region electron densities, the ion drag is enhanced between about 220 and 500 km altitudes. At the F peak altitudes near 300 km, the median ion drag acceleration affecting neutrals more than doubled and the associated median e‐folding time decreased from 4.4 to 2 hr. The strong neutral wind was found to be driven primarily by the ion drag force due to large‐scale ionospheric convection. Our results provide a new insight into ionosphere‐thermosphere coupling in the presence of PCPs/blobs.

Climatic teleconnection of the future trend of meteorological, GRACE-DSI, and vegetation-conditioned-based drought analysis in the Ganga Basin

ABSTRACT This study assesses drought in the Ganga River Basin using standard precipitation index (SPI), Gravity Recovery and Climate Experiment Drought Severity Index (GRACE-DSI), and vegetation condition index (VCI) via geographic information system (GIS) and non-parametric tests. Future SPI trends show increasing drought severity from 1986 to 2020. GRACE-DSI analysis (2002–2020) indicates a potential rise in drought conditions. VCI computations reveal vegetation health dynamics. Findings suggest an impending severe drought in the Ganga Basin, necessitating urgent water resource management. Drought causes are linked to precipitation changes and resource over-exploitation in changing climate conditions. The study emphasizes implementing measures like water conservation, sustainable land use, and groundwater recharge strategies to mitigate drought impacts.

Spatial downscaling of GRACE-derived groundwater storage changes across diverse climates and human interventions with Random Forests

The Gravity Recovery and Climate Experiment (GRACE) satellites launched in 2002, which were followed by the GRACE Follow-On mission in 2018, represented a significant advancement in global groundwater storage monitoring. However, the inherent limitation of a relatively low spatial resolution confines its applicability primarily to large river basins and aquifers. This study introduces a novel statistical downscaling approach using Random Forests (RF) to enhance the spatial resolution from 3° × 3° to 0.25° × 0.25° for GRACE-derived groundwater storage (GWS) changes. Focusing on sub-Saharan Africa, the Middle East, and South Asia across diverse climates and human interventions, the analysis spans from February 2003 to December 2022. Predictors encompass hydrological fluxes and their accumulation, including IMERG precipitation, GLEAM evapotranspiration, and GLDAS runoff, alongside GLDAS soil moisture and MODIS NDVI. RF models show robust performance across 114 aquifers, with a Pearson’s correlation coefficient (CC) exceeding 0.92 for training sets and 0.85 for validation sets. Validation against in-situ groundwater level observations from wells in India reveals satisfactory performance, with positive Spearman’s CC values between in-situ groundwater levels and downscaled terrestrial water storage anomaly (TWSA) for a majority of dug and bore wells. This study concludes with the generation of monthly downscaled GWS changes (0.25° × 0.25°) spanning from February 2003 to December 2022. These datasets serve as a foundation for facilitating finer-scale hydrological studies and formulating local groundwater management strategies.

HUST-Grace2024: a new GRACE-only gravity field time series based on more than 20 years of satellite geodesy data and a hybrid processing chain

Abstract. To improve the accuracy of monthly temporal gravity field models for the Gravity Recovery and Climate Experiment (GRACE) and the GRACE Follow-On (GRACE-FO) missions, a new series named HUST-Grace2024 is determined based on the updated L1B datasets (GRACE L1B RL03 and GRACE-FO L1B RL04) and the newest atmosphere and ocean de-aliasing product (AOD1B RL07). Compared to the previous HUST temporal gravity field model releases, we have made the following improvements related to updating the background models and the processing chain: (1) during the satellite onboard events, the inter-satellite pointing angles are calculated to pinpoint outliers in the K-band ranging (KBR) range-rate and accelerometer observations. To exclude outliers, the advisable threshold is 50 mrad for KBR range rates and 20 mrad for accelerations. (2) To relieve the impacts of KBR range-rate noise at different frequencies, a hybrid data-weighting method is proposed. Kinematic empirical parameters are used to reduce the low-frequency noise, while a stochastic model is designed to relieve the impacts of random noise above 10 mHz. (3) A fully populated scale factor matrix is used to improve the quality of accelerometer calibration. Analyses in the spectral and spatial domains are then implemented, which demonstrate that HUST-Grace2024 yields a noticeable reduction of 10 % to 30 % in noise level and retains consistent amplitudes of signal content over 48 river basins compared with the official GRACE and GRACE-FO solutions. These evaluations confirm that our aforementioned efforts lead to a better temporal gravity field series. This data set is identified with the following DOI: https://doi.org/10.5880/ICGEM.2024.001 (Zhou et al., 2024).

Toolkit for assessing water accounting in data-scarce river basins using global databases

This study develops a toolkit for implementing the WA + framework, integrating observational data and global databases to enhance data collection for water accounting assessment. By addressing data gaps, updating processes, and coverage issues through automated systems, it compiles key variables like precipitation, evapotranspiration, and groundwater fluctuations, leveraging GLDAS (Global Land Data Assimilation System), GLEAM (Global Land Evaporation Amsterdam Model), and GRACE (Gravity Recovery and Climate Experiment) datasets. The toolkit, named NWBWAS (National Web Based Water Accounting System), automates water accounting components' calculation, providing comprehensive reports and indicators. Using the Tashk-Bakhtegan watershed as a case study, NWBWAS demonstrated significant advancements, offering a robust, efficient solution for rapid, cost-effective initial water accounting assessments, marking a substantial improvement over previous approaches.

Future challenges of terrestrial water storage over the arid regions of Central Asia

Since the arid regions of Central Asia (ACA) are located in the interior of Eurasia, water resources play a vital role in the stability of its ecosystem and economic development. Based on the terrestrial water storage anomaly (TWSA) of the Gravity Recovery and Climate Experiment (GRACE), we analyze the observed characteristics of the TWSA over the ACA during 2003–2014. Results indicate that the terrestrial water storage (TWS) in the region showed an overall declining trend from 2003 to 2014, and the autumn TWS in this region is the smallest compared to other seasons and exhibits a strong decreasing trend at least −4.5 cm/decade. This means water resources over the ACA are scarcer and more vulnerable in autumn. The Distance between Indices of Simulation and Observation (DISO) method is employed to evaluate the performance of the sixth phase of the Coupled Model Intercomparison Project (CMIP6) models in simulating the autumn TWSA over the ACA. Compared with observational results, the autumn TWSA values captured by CMIP6 models are larger and the declining TWS trends are weaker. Using the optimal CMIP6 models, the statistical downscaling method constrains the projection results of autumn TWSA values over the ACA using the GRACE datasets. It shows autumn TWS will continue to decrease in most parts of the ACA in the future, and water scarcity will be the most severe in Tajikistan and southwestern Kazakhstan. Under SSP126, Tajikistan’s TWSA is projected to decrease by 11.0 cm in the long term. This study reveals the current situation and possible future changes in TWS over the ACA in autumn, providing references for water resource management and sustainable development policies in this area to avoid losses caused by water scarcity.

Satellite gravimetry observations on the state of groundwater level variability in the Arabian Peninsula Region and the associated socio-economic sustainability challenges

Groundwater is an important resource for the Arabian Peninsula Region. The population increase, rise in agricultural activities, and Gulf Cooperation Council (GCC) countries (Bahrain, Kuwait, Oman, Qatar, Saudi Arabia, and the United Arab Emirates) inclination towards economic diversification and tourism promotion have heightened the freshwater demand. As a result of climate change and varying weather patterns, the situation has become more complicated. Due to arid conditions, recharge is mostly less than withdrawal which consequently results in underground water level decline over time. In the research, we have used Gravity Recovery and Climate Experiment (GRACE/GRACE-FO) MASCON solutions, Global Land Data Assimilation System (GLDAS) soil moisture, and the Integrated Multi-satellite Retrievals for Global Precipitation Mission (IMERG) rainfall data to observe the Equivalent Water Thickness (EWT), and rainfall patterns in this region for the past two decades (2002–2023). The results indicate that in Saudi Arabia the water level is declining nearly at a linear rate and the linear regression model fits well with the data (R2 value, the coefficient of determination, for different cities of Saudi Arabia is ≥ 0.94). In the Al Jouf Area, the water decline is the highest at −1.69 cm/year which is 43% greater than the previous calculations. The lowest decline rate is in Sanaa (Yemen) which is −0.13 cm/year. Furthermore, all the other studied locations show a groundwater declining trend. In Saudi Arabia's Makkah, Madina, Riyadh, and Damam the reduction rate is −0.36, −0.48, −0.72, and −0.48 (cm/year) respectively. Kuwait, UAE's Dubai, and Al Ain show a similar groundwater reduction rate of −0.19 cm/year. In Oman's Masqat, the groundwater decline rate is −0.22 cm/year. Also, in the recent data, one can see the higher seasonal amplitudes that are indicative of greater fluctuations in EWT data in recent times. If water mining continues at the same pace, this important resource can become a rare commodity. Limited water supply can likely become a limiting factor for further social, agricultural, and industrial development. That's why major reviews and shifts are necessary in the current policies related to water resource management and conservation.

Multivariate variational mode decomposition to extract the stripe noise in GRACE harmonic coefficients

SUMMARY In this work, a novel method has been developed to remove the north–south stripe noise in the Level-2 spherical harmonic coefficient products collected by the Gravity Recovery and Climate Experiment (GRACE) mission. The proposed method extracts the stripe noise from the equivalent water height (EWH) map via the Multivariate Variational Mode Decomposition algorithm. The idea behind our method is to extract the cofrequency mode in multiple-channel series in the longitude direction. The parameters of our method are empirically determined. The investigation in a closed-loop simulation proves the improvement of our methods compared with the Singular Spectrum Analysis Spatial (SSAS) filter. Subsequently, the spatial-domain and spectral-domain investigations are conducted by using real GRACE data. Our method only suppresses stripe noise at low latitudes (30°S–30°N) and imposes an order-dependent impact on spherical harmonic coefficients but with potential oversmoothing. Meanwhile, the well-documented water level proves that our method further reduces outliers in a time-series of localized mass variations compared with the SSAS filter. More importantly, users are allowed to reduce the filtering strength of our method to preserve small-scale strong signals while suppressing stripe noise. Moreover, noise levels over the ocean at low latitudes are evaluated as well. The noise level of our method using empirical parameters is 32.48 mm of EWH, with 31.54 and 53.52 mm for DDK6 and SSAS, respectively. Our work introduces a novel method to address the issue of north–south stripe noise in the spatial domain.

An investigation of ocean mass budget in the East China Sea during the GRACE era

The Gravity Recovery and Climate Experiment (GRACE) mission provides uniquely high-precision observations for monitoring ocean mass changes (OMC), allowing for the establishment and evaluation of the ocean mass budget in conjunction with satellite altimetry and temperature and salinity observations. However, it is challenging to perform OMC closed-loop validation in the East China Sea (ECS) due to potential biases in the individual model and the lack of certain data processing. In this study, we comprehensively analyze the ocean mass budget in the ECS during the GRACE era (2005–2015) by utilizing multiple datasets, mainly consisting of three official GRACE RL06 solutions, three altimetry products, and four ocean reanalysis products. The effect of ocean bottom deformation, neglected in previous studies, is −0.38 ± 0.06 mm/yr, and we estimate a more accurate ensemble sea level change to be 4.05 ± 1.50 mm/yr in the ECS from the altimetry products. There are discrepancies between leakage-corrected GRACE OMC observations and steric-corrected altimeter OMC estimations in both the seasonal signals and the long-term trends (e.g., 6.25 mm/yr vs. 4.22 mm/yr). These discrepancies are strongly correlated with sediment runoff from the Yangtze River and in-situ sediment observations, suggesting that ocean sediment accumulation should be considered in the ocean mass budget in the ECS. Since in-situ sediment data are estimated over ∼100 years, we employ an empirical estimation method to determine the corresponding data during the period 2005–2015, to avoid potential biases caused by inconsistencies in observational timespans. The results show that sediment mass changes can explain about 96 % of residual trends. Our results emphasize the significant impact of sediment on improving the ocean mass budget in the ECS, offering a novel perspective for estimating ocean mass changes in other coastal regions.

Assessing drought in Turkish basins through satellite observations

AbstractDrought occurs when there is a sustained decrease in rainfall over an extended period, impacting the socio‐cultural and environmental aspects of humans and other living beings. The geographic distribution and timing of droughts play a crucial role in drought management and mitigation strategies. Identifying and predicting the onset of droughts in specific regions, especially in watershed areas, is a primary concern in the field of hydrology. This study focuses on how the spatiotemporal patterns of drought are developing in Turkish Basins using detailed data on Terrestrial Water Storage (TWS), precipitation, and temperature at the pixel level. GRACE (Gravity Recovery and Climate Experiment), PERSIANN (Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks), and WorldClim (World Climate) data sets are employed to assess long‐term changes of drought on a basin‐scale. Spatial analyses are conducted in a Geographic Information System (GIS) environment for the derivation of basinal monthly mean, minimum, and maximum statistics of TWS, precipitation, and temperature anomalies within Turkish Basins. Time series analyses are implemented to investigate the temporal evolution of droughts in these basins, for the basinal monthly mean, minimum, and maximum statistics obtained. The Mann–Kendall trend test and Pettitt change point detection tests are used to assess the statistical significance of the calculated trends and to expose the existence of any change point therein, respectively. The findings of the study indicate that Turkiye faces a significant risk of drought development in nearly all its basins, particularly after 2016. The GRACE dataset provides realistic insights into the temporal behaviour of hydrological droughts. PERSIANN is effective in identifying years with extreme meteorological conditions, and the standardized precipitation index (SPI) shows similar effectiveness, while they are ineffective in exposing significant trends due to the nature of the precipitation data. WorldClim data proves insufficient for modelling the temporal behaviour of droughts in these basins.

HRU-based Downscaling of GRACE-TWS to Quantify the Hydrogeological Fluxes and Specific Yield in the Lower Middle Ganga Basin

Precise volumetric assessments of different hydrological variables, such as precipitation, evapotranspiration, and groundwater components, are necessary for comprehensive water resource management. This presents several challenges, including topographical complexity and economic limitations, mainly when aiming for high temporal and spatial resolution.The satellite mission Gravity Recovery and Climate Experiment (GRACE) has greatly improved the ability to quantify variations in GWS. We have described a two-stage downscaling system that integrates SWAT Hydrological Response Units (HRUs) with GRACE-derived Terrestrial Water Storage Anomalies (GRACE-TWSA) using Artificial Neural Networks (ANN). Using data from the Global Land Data Assimilation System (GLDAS), GWS was derived with GRACE-TWSA and further downscaled to the HRU level. The GWS trend in most of the study areas has not shown any significant trend from 2001 to 2014. The mean increasing trend was 2.16 mm/year and the mean decreasing was 2.28 mm/year. Using a decision-tree-based CatBoost model, the GWS has been used as an independent variable to determine distributed groundwater levels within the study area. A strong correlation between measured groundwater levels and GWS was observed, and a regularised robust optimization was used to determine the Specific yield. The surface water and groundwater budgeting indicate that most Gangetic area blocks are water-stressed. The study offers an extensive approach to integrated water resource management by providing insights into groundwater availability, aquifer storage characteristics, and budgeting with HRU scale GWS estimates.

Improved Estimates of Sub‐Regional Groundwater Storage Anomaly Using Coordinated Forward Modeling

AbstractGroundwater storage anomaly (GWSA) can be estimated either at the large scale from the Gravity Recovery and Climate Experiment (GRACE) or at the local scale based on in situ observed groundwater level (GWL) and aquifer storage parameters. Yet, the accuracy of GRACE‐based estimate is affected by leakage errors, while that of local GWL‐based estimate requires the reliable specific yield (Sy) data that are usually not available. Here, we developed a novel approach, the coordinated forward modeling (CoFM), based on the iterative forward modeling to improve GWSA estimation at the sub‐regional scale smaller than the typical GRACE footprint. It is achieved by solving Sy through iterative comparisons between GRACE‐based and observation‐based GWSA at 0.5° grid scale, and then re‐calculating GWSA using the updated Sy and observed GWL. The utility of CoFM is explored by using the hypothetical experiments and a real case study in the Piedmont Plain (PP, ∼54,000 km2) and East‐central Plain (ECP, ∼86,000 km2) of North China Plain. Results show that CoFM can detect GWSA at 0.5° grid scale in the hypothetical experiments given the large spatial variability of GWL. While in the real case study, the CoFM distinguishes between the divergent unconfined GWSA trends (2005–2016) in PP (−41.80 ± 0.55 mm/yr) and ECP (−7.57 ± 0.60 mm/yr) caused by the differences in hydrogeological conditions and groundwater use. The improvement made by CoFM can be attributed to the use of the distributed GWL information to constrain GRACE leakage errors. This study highlights a practical important solution for improving sub‐regional GWSA estimation through the joint use of large‐scale GRACE data and local‐scale well observations.

Downscaled‐GRACE Data Reveal Anthropogenic and Climate‐Induced Water Storage Decline Across the Indus Basin

AbstractGRACE (Gravity Recovery and Climate Experiment) has been widely used to evaluate terrestrial water storage (TWS) and groundwater storage (GWS). However, the coarse‐resolution of GRACE data has limited the ability to identify local vulnerabilities in water storage changes associated with climatic and anthropogenic stressors. This study employs high‐resolution (1 km2) GRACE data generated through machine learning (ML) based statistical downscaling to illuminate TWS and GWS dynamics across twenty sub‐regions in the Indus Basin. Monthly TWS and GWS anomalies obtained from a geographically weighted random forest (RFgw) model maintained good consistency with original GRACE data at the 25 km2 grid scale. The downscaled data at 1 km2 resolution illustrate the spatial heterogeneity of TWS and GWS depletion within each sub‐region. Comparison with in‐situ GWS from 2,200 monitoring wells shows that downscaling of GRACE data significantly improves agreement with in‐situ data, evidenced by higher Kling‐Gupta Efficiency (0.50–0.85) and correlation coefficients (0.60–0.95). Hotspots with the highest TWS and GWS decline rate between 2002 and 2023 were Dehli Doab (−442, −585 mm/year), BIST Doab (−367, −556 mm/year), Rajasthan (−242, −381 mm/year), and BARI (−188, −333 mm/year). Based on a general additive model, 47%–83% of the TWS decline was associated with anthropogenic stressors mainly due to increasing trends of crop sown area, water consumption, and human settlements. The decline rate of TWS and GWS anomalies was lower (i.e., −25 to −75 mm/year) in upstream sub‐regions (e.g., Yogo, Gilgit, Khurmong, Kabul) where climatic factors (downward shortwave radiations, air temperature, and sea surface temperature) explained 72%–91% of TWS/GWS changes. The relative influences of climatic and anthropogenic stressors varied across sub‐regions, underscoring the complex interplay of natural‐human activities in the basin. These findings inform place‐based water resource management in the Indus Basin by advancing the understanding of local vulnerabilities.

Boundaries identification of geological structure in lunar Oceanus Procellarum region using full gravity gradient tensor methodology

Boundary recognition visually delineates the horizontal extent of subsurface anomalies, providing a foundational basis for interpreting gravity data. Compared to gravity observations, gravity gradient data offers the benefits of multiple components and the enhancement of shortwave information in graphical representations. In our study, we investigated the delineation of geological structure boundaries in the lunar Oceanus Procellarum region using gravity gradient techniques. First, based on the observations from the Gravity Recovery and Interior Laboratory (GRAIL) mission, we obtained high-precision synthetic full tensor values of the gravity gradient as our primary research data. Moreover, to reduce curvature errors during large-scale terrain forward modeling, we applied the spherical prism of tesseroid to eliminate the effects of near-surface topography. Grounded on the Bouguer anomalies of gravity gradient, four distinct boundary recognition methods have been employed to explore the geological structure of the lunar Oceanus Procellarum region. It includes the Theta map method, the directional Theta map method, the combination of total horizontal derivative and the modulus of full tensor gravity gradient, and the improved edge detection method based on the Theta map method.The common feature of these methods is the utilization of the multi-component data combination from gravity gradient tensors, which can enhance the accuracy of edge detection. From the investigation results presented in the paper, we have found the following: 1) The improved edge detection method, based on the Theta map principle, enables better identification of the center of subsurface anomaly bodies during boundary recognition, utilizing a consistent single color in graphic displays. 2) According to the results of boundary recognition, numerous strip anomalies exist in the Oceanus Procellarum area that show less correlation with topographic relief. One possible explanation for these graphical anomalies of gravity gradient is that they serve as channels for the upwelling of mantle material during lunar evolution.

The Feature Analysis and Modeling of Upper Atmospheric Midnight Density Maximum

The features of upper atmospheric midnight density maximum (MDM) around low geographic latitudes are studied based on neutral mass densities data at altitudes 360–480 km, derived from the accelerometer measurements aboard on the three polar orbiting satellites CHAMP (CHAllenging Minisatellite Payload), GRACE-A (Gravity Recovery and Climate Experiment-A), and SWARM-C (The Earth's Magnetic Field and Environment Explorers-C). The MDM appears during the local times from 23:00 to 02:00 LT (Local Time), whose peak locates at the low latitudes within 15∘ and two valleys locate at the middle latitudes between 35∘ and 45∘ on both hemispheres separately. The structure of MDM drifts toward the southern hemisphere overall. The MDM's amplitude decreases with increases in altitude and solar radiation level. The seasonal effect weakens the MDM's amplitudes around the summer and winter solstices, while the amplitudes around the spring and autumn equinoxes are extremely significant due to the slight seasonal difference between both hemispheres. Three atmospheric density models DTM2000 (Drag Temperature Model 2000), NRLMSISE00 (US Naval Research Laboratory Mass Spectrometer and Incoherent Scatter Radar Extended atmosphere model), and JB2008 (Jacchia-Bowman 2008 model) are used to simulate the MDM along these three satellites' orbits, and compared with the observations. It is found that the JB2008 model is failed to describe the MDM, and the other two models underestimate the MDM's amplitudes at altitudes 360 km and 480 km: the simulated amplitudes by the DTM2000 model are 46% and 53% of the observed amplitudes, respectively, and only 33% and 26% for the NRLMSISE00 model. These three models are also failed to depict the MDM's variation with altitude, solar radiation level, and seasonal effects. In order to correct the model prediction, a 6th-order Legendre polynomial of geographic latitude, coupled with arguments of local time and altitude, is designed to fit the MDM signals from the three satellites' observations. In terms of amplitude and phase of the MDM, the fitting results agree with the observations very well, and the correlation coefficient is 0.923. It indicates that this empirical polynomial could be helpful to the density model correction and high accuracy prediction of spacecrafts in low Earth orbits.

Watching the Grand Ethiopian Renaissance Dam from a distance: Implications for sustainable water management of the Nile water.

Increased demands for sustainable water and energy resources in densely populated basins have led to the construction of dams, which impound waters in artificial reservoirs. In many cases, scarce field data led to the development of models that underestimated the seepage losses from reservoirs and ignored the role of extensive fault networks as preferred pathways for groundwater flow. We adopt an integrated approach (remote sensing, hydrologic modeling, and field observations) to assess the magnitude and nature of seepage from such systems using the Grand Ethiopian Renaissance Dam (GERD), Africa's largest hydropower project, as a test site. The dam was constructed on the Blue Nile within steep, highly fractured, and weathered terrain in the western Ethiopian Highlands. The GERD Gravity Recovery and Climate Experiment Terrestrial Water Storage (GRACETWS), seasonal peak difference product, reveals significant mass accumulation (43 ± 5 BCM) in the reservoir and seepage in its surroundings with progressive south-southwest mass migration along mapped structures between 2019 and 2022. Seepage, but not a decrease in inflow or increase in outflow, could explain, at least in part, the observed drop in the reservoir's water level and volume following each of the three fillings. Using mass balance calculations and GRACETWS observations, we estimate significant seepage (19.8 ± 6 BCM) comparable to the reservoir's impounded waters (19.9 ± 1.2 BCM). Investigating and addressing the seepage from the GERD will ensure sustainable development and promote regional cooperation; overlooking the seepage would compromise hydrological modeling efforts on the Nile Basin and misinform ongoing negotiations on the Nile water management.

Data Quality Assessment of Gravity Recovery and Climate Experiment Follow-On Accelerometer.

Accelerometers are mainly used to measure the non-conservative forces at the center of mass of gravity satellites and are the core payloads of gravity satellites. All kinds of disturbances in the satellite platform and the environment will affect the quality of the accelerometer data. This paper focuses on the quality assessment of accelerometer data from the GRACE-FO satellites. Based on the ACC1A data, we focus on the analysis of accelerometer data anomalies caused by various types of disturbances in the satellite platform and environment, including thruster spikes, peaks, twangs, and magnetic torque disturbances. The data characteristics and data accuracy of the accelerometer in different operational states and satellite observation modes are analyzed using accelerometer observation data from different time periods. Finally, the data consistency of the accelerometer is analyzed using the accelerometer transplantation method. The results show that the amplitude spectral density of three-axis linear acceleration is better than the specified accuracy (above 10-1 Hz) in the accelerometer's nominal status. The results are helpful for understanding the characteristics and data accuracy of GRACE-FO accelerometer observations.