The potential of using airborne gravity gradient tensor (GGT) for coastal quasi-geoid (QG) refinement is explored, and the contributions introduced from individual GGT components and their combinations are quantified and evaluated. High-resolution QGs, with a spatial resolution of ~0.5 km, are computed over St. George’s Bay in southwestern Newfoundland, Canada. The findings indicate that fully focused Synthetic Aperture Radar (FFSAR) and Surface Water and Ocean Topography (SWOT) altimetry data are effectively in differentiating the performance of various QGs in coastal areas. The application of the vertical gravity gradient obtains the highest quality QG when utilizing individual GGT components. The combination two or more components results in improved QGs compared to the results derived from individual components. The integration of full GGT yields the best QG, with standard deviation (SD) of misfits against Sentinel-3A FFSAR (SWOT) altimetry data being 1.13 (2.49) cm, representing reductions of 28.48–53.50% (5.32–15.02%) compared to results derived from individual GGT components. Comparisons of the QG computed by fusing full GGT with the Canadian gravimetric QG CGG2013 and high-degree global geopotential models further underscore the advantages of using GGT in QG modeling, revealing SD reductions of 55.16–65.02% (7.55–33.95%) against FFSAR (SWOT) altimetry data. These findings underscore the effectiveness of using airborne GGT in coastal QG modeling, particularly in recovering short-wavelength signals and addressing challenges in satellite altimetry over coastal environments. Additionally, this study highlights the superiority of using full GGT over individual components in QG modeling.

Bathymetry provides instrumental information for studying sedimentary processes, global climate change, and benthic morphologies. The advantages and applicabilities of different techniques for bathymetry detection vary. We propose a framework for bathymetry enhancement from multisource data based on spherical radial basis functions (SRBFs). A case study is conducted over the Paracel Islands in South China Sea (SCS), where Ice, Cloud, and land Elevation Satellite-2 (ICESat-2) measurements, airborne gravimetric observations, echo soundings, and the reference model DTU18BAT are merged. Numerical results suggest that the fusion of ICESat-2 observations dramatically enhances the quality of the computed bathymetry model near the islands, the root-mean-squared error (RMSE) of which is reduced by 45.35%–67.95% compared to existing models when validated against the satellite-derived bathymetry (SDB) with decimeter-level accuracy. By additionally fusing the airborne gravimetric data, bathymetry is further enhanced by ~22.49%, particularly over islands with sparse ICESat-2 trajectories. Comparisons with surveyed airborne bathymetric lidar data over the northern Antelope Reef yielded results consistent with those obtained from the SDB, suggesting that SDB is possible to serve as control data in waters devoid of ground truth data. Further analysis reveals that the models constrained by echo soundings performed better than existing models in deep waters, with reductions of 17.79%–44.99% in terms of RMSE. By fusing airborne gravity data, bathymetry is improved by ~10%, highlighting the utilization of airborne gravimetry in both shallow and deep waters. The proposed SRBF approach offers an effective way to merge heterogeneous data for high-quality bathymetry determination.

The lack of marine gravimetric measurements and the presence of severely contaminated altimetry data pose multiple challenges in high-quality quasi-geoid (QG) and mean dynamic topography (MDT) determination over islands, where the application of nadir altimetry alone is inadequate. We explore the potential for regional enhancement using wide-swath data from the Surface Water and Ocean Topography (SWOT) mission. Numerical experiments over the Paracel Islands in South China Sea underscore the superiority of using SWOT data in QG/MDT computation. Comparisons with the airborne gravimetry-derived QG reveal that the Root Mean Square Errors (RMSEs) of QGs derived from the SWOT data are reduced by 38.24–60.90% compared to those derived solely from nadir altimetry. The QG profiles retrieved from the Sentinel-3A/B altimetry using the fully-focused SAR technology are effective in discriminating the quality of different QGs near islands. The RMSEs of SWOT-derived QGs constitute reductions of 6.27–17.52% compared to those computed from nadir altimetry alone. Notable improvements up to 4 cm are observed when Sentinel-3A/B tracks approached islands. The mutual comparison of the QGs computed from the SWOT gravity anomaly (GRA) and vertical gravity gradient (VGG) data suggests that the VGG-derived QG has improved quality, and the utilization of VGG recovers more small-scale signals. The SWOT-derived MDTs reduce the bubble-like errors up to several centimeters compared to those computed exclusively using nadir altimetry. Our findings highlight that utilizing SWOT data enables the acquisition of an accurate QG/MDT with an RMSE less than 1 cm compared to that derived from airborne gravimetry.

Gravity anomaly over shallow waters is one of the fundamental data sources for studying sea level change, ocean currents, and water exchanges between coastal areas and open seas. However, the acquirement of gravity data over shallow waters faces multiple challenges due to the degraded quality of satellite altimetry data and scarcity of surveyed gravimetric observations. To alleviate this problem, we establish a framework for marine gravity anomaly refinement by using satellite-derived bathymetry (SDB). We use a cosine-tapered band pass filter to extract high-frequency gravity signals from the SDB data, which compensate for the unresolved signals in satellite altimetric gravity data. Numerical experiments over the Discovery Reef and an offshore region near the Port Hedland demonstrate that the utilization of SDB effectively strengths marine gravity anomaly. By combining the SDB data, the fits between the enhanced gravity anomaly models and surveyed airborne gravity data are improved, by 5.3–15.7% in comparison to an altimetric gravity model DTU21GRA. The SDB calculated from the linear band model has slightly better performances in gravity anomaly modeling than that computed from the band ratio model and physical-based approach, agreeing well with the SDB validation results. Our results verify the feasibility of using the SDB computed from the physical-based approach for gravity anomaly augmentation, which is of great value in areas devoid of ground truth depths. This study cements a way for the augmentation of marine gravity anomaly worldwide, especially in remote regions characterized by the scarcity of ground-based gravity data.

We study the role of airborne gravimetry for seamless bathymetry modeling over the Paracel Islands in northern South China Sea, and investigate the possibility of using ICESat-2 data and satellite-derived bathymetry (SDB) to evaluate bathymetry models over shallow waters. We use ICESat-2 data for training Sentinel-2 imagery and derive the SDB data with a Root Mean Squared Error (RMSE) of 0.29-0.50 m, which is lower than 10% of the maximum depths. The local bathymetry is modeled by using a modified version of S&S band-pass filter, and a partition-wise scheme is applied for determining the scaling factors. Numerical experiments verify the feasibility of using ICESat-2 and SDB data to assess bathymetry models. By utilizing the airborne gravity data, the fit between the computed bathymetry and the SDB data is significantly improved, by 18.7-58.0% over different shallow waters compared to recently released bathymetry models. The bathymetry predicted from the airborne data has also higher performance in deep water areas, which performs best in all these depth ranges from 500 to 3000 m. In comparison to the existing models, the RMSEs of the misfits between the computed bathymetry and the National Oceanic and Atmospheric Administration depths are reduced by tens to hundreds of meters in different depth ranges. Our study highlights that using airborne gravimetry for bathymetry modeling over island areas is advantageous, in both shallow and deep waters; and that ICESat-2 and SDB data can largely alleviate the lack of in-situ depths over shallow waters.

The outburst of Zhuonai Lake (ZL) in 2011 changed the local hydro-ecological system in northeast Hoh Xil (HX). This study focuses on the impact of the outburst on lake water storage changes (LWSCs) of four lakes in this region. Monthly LWSC from 2009 to 2016 were constructed using Landsat and Cryosat-2 data. We determined and validated lake levels and areas derived from Cryosat-2 and Landsat data, respectively. The two satellite-derived sequences were merged by interpolation to compute LWSC, based on the level-area curve derived from the digital elevation model (DEM). Results reveal the apparent impact of the outburst on the hydrological system. Before the outburst, water volumes in all four lakes continuously grew from January 2009 to September 2011, with a total increase of 1.49 ± 0.08 Gt. Most increased water was distributed in ZL and Kusai Lake (KL). The LWSC of each lake was strongly correlated (>0.9) with those of the whole basin. However, from October 2011 to December 2016, there was no ascending trend in LWSC of the three upper stream lakes, although the water volume in the basin was still increasing. More than 80% of the increased water flowed into Salt Lake (SL). Only the LWSC of SL kept a high correlation (0.91) with those of the whole basin.

Predicting and monitoring the spatiotemporal characteristics of heavy rain events are important to hazard preparedness, mitigation efforts, and local water resource management. Using three data sets, namely, the daily rain product from the Integrated Multi-satellitE Retrievals for Global Precipitation Measurement (IMERG) version 04 Final Run, the daily output from European Centre for Medium-Range Weather Forecasts reanalysis data Interim version (ERA-Interim), and the high-quality gauge-satellite merged precipitation product, the spatiotemporal patterns of three heavy rain events are investigated for the first time over China in 2016, with the objective of assessing the capability of IMERG product for monitoring heavy rain events. It is found that the daily IMERG Final Run can better capture the spatial and temporal characteristics of heavy rain compared with that from ERA-Interim, but it significantly overestimates the amounts of the heaviest rainfalls by 11%-85% over the example regions. The comparison of regional averaged precipitation demonstrates that time series of precipitation retrieved by the IMERG algorithm agree well with that from gauge-satellite merged data set, with differences less than 10 mm on most days over each region. The statistic metrics demonstrate that the IMERG Final Run has a strong potential for detecting heavy rain events but with a relatively large error. This letter may provide useful feedback and insights for further improving the precipitation retrieving algorithm and the application of such data sets.