Marine Gravity Anomalies Research Articles

Performance assessment of sentinel-3/6 altimeter data for marine gravity recovery

High-precision sea surface height is crucial for determining the marine gravity field. The Sentinel-3/6 altimetry missions, equipped with SRAL and Poseidon-4 altimeters, provide this essential data. However, there is a lack of comprehensive assessment of the Sentinel-3/6 altimeters for inverting marine gravity anomalies (MGA). In this study, we employ the inverse Venning-Meinsz method to derive nine sets of 1’×1’ MGAs in the South China Sea (SCS) and the Ross Sea (RS). Specifically, MGAs from Sentinel-3A, Sentinel-3B, Sentinel-6 SARM, Sentinel-6 LRM, HY-2A, ICESat-2, and CryoSat-2 are denoted as S3A, S3B, S6S, S6L, H2A, IS2, and CS2, respectively. MGA from the combined HY-2A, ICESat-2, and CryoSat-2 is referred to as HIC, while 3SHIC denotes the MGA from the combination of Sentinel-3/6 SARM, HY2A, ICESat-2, and CryoSat-2. We assess the performance of these MGAs using the EGM08, DTU17, SIO V32.1, and SDUST2021 gravity field models, as well as shipboard gravity across different ocean regions. Among the Sentinel-3/6 MGAs, S3B exhibits the highest accuracy in the SCS, with a root mean square error (RMSE) of 5.277 mGal, followed closely by S3A. Conversely, S3A demonstrates the highest accuracy with an RMSE of 4.635 mGal, followed by S3B in the RS. The inversion accuracy of MGAs from S6S and S6L are comparable, though S6S outperforms S6L in the open sea. The performance of MGAs from Sentinel-3/6 matches or surpasses that of other altimetry missions during the same period. In the SCS, the best-performing MGA is 3SHIC, with an RMSE of 4.585 mGal, closely matching DTU17. However, 3SHIC exhibits superior performance in the RS with an RMSE of 4.263 mGal compared to DTU17 and SDUST 2021. Furthermore, the performance of 3SHIC, which integrates Sentinel-3/6 data, improves that of HIC by 0.74% and 3.37% in the SCS and RS, respectively. These results underscore the contribution of Sentinel-3/6 altimeters to the MGA, particularly in coastal and high-latitude regions. Integration of Sentinel-3/6 data with other altimetry satellites is expected to enhance the spatial resolution and accuracy of the global marine gravity field, especially with the successful establishment of the network of Sentinel-6 in the future.

The performance of Tiangong-2 InIRA in gravity anomaly recovery from fused conventional nadir-observing altimeter data

Satellite altimetry has emerged as the primary data source for deriving marine gravity, owing to advancements in satellite altimetry technologies. The Tiangong-2 interferometric imaging radar altimeter (TG2 InIRA) is a new generation wide-swath altimeter (WSA) launched by China on 15 September 2016. TG2 InIRA employs a short-baseline interferometry measurement method at a small incidence angle, thereby enabling the precise measurement of wide-swath sea surface heights (SSHs). The present study demonstrates the efficacy of utilizing data from the TG2 InIRA in conjunction with data from the CryoSat-2 (CS2) satellite to recover marine gravity anomalies. In the Northwest Pacific region (15°N ∼ 25°N, 140°E ∼ 150°E), the TG2 InIRA data were filtered to a 2 km × 2 km grid and any anomalous values were excluded using a mean sea surface model. Deflections of the vertical (DOVs) were calculated using the remove-restore technique, and the inverse Vening-Meinesz formula was applied to invert the gravity anomaly. A power spectral density analysis was conducted to assess variations in gravity anomalies at ship locations in the frequency domain. The results, based on the SIO V31.1 (DOV) model, indicate that the gridded vertical deflections derived from CS2 and TG2 InIRA data achieve more balanced accuracy in the east–west and north–south directions. The integration of TG2 InIRA and CS2 data yielded gravity results exhibiting a root mean square (RMS) of 0.519 mGal lower than those derived from TG2 InIRA data alone, and 0.034 mGal lower than those derived from CS2 data. These findings were derived from shipborne gravity data. Furthermore, the inversion of gravity anomalies from TG2 InIRA demonstrated an enhanced capability in the reduction of high-frequency gravity noise.

Enhanced gravity-geologic method to predict bathymetry by considering non-linear effects of surrounding seafloor topography

SUMMARY The gravity-geological method (GGM) is an approach that utilizes marine gravity anomalies (GAs) and shipborne bathymetric data to invert seafloor topography by resolving short-wavelength GAs through the Bouguer Plate approximation. Such an approximation ignores the non-linear effects caused by surrounding seafloor topographical undulations that actually exist in short-wavelength GAs, and thus leaving the space for further modification of GGM. This study thoroughly derives the relationship between seafloor topography and GA, as well as the formula of GGM. Then, we propose a self-adaptive method to improve the accuracy of the inversion significantly: the enhanced GGM (EGGM). The method uses the equivalent mass line method to approximate the non-linear gravitational effects of the surrounding seafloor topography to correct the short-wavelength GAs. By introducing two optimal density contrast parameters, EGGM has been designed to effectively integrate the combined effects of various non-linear factors to a certain extent. The accuracy of the seafloor topography models, produced with a spatial resolution of 1′ × 1′, was evaluated over the study area (132°E–136°E, 36°N–40°N) located in the Sea of Japan. The results indicate that the accuracy of EGGM has a relative improvement of 13.73 per cent compared to that of GGM in the overall study area, while the accuracy of both models is higher than that of the SIO_unadjusted model. The study further investigated the feasibility and stability of EGGM by examining the accuracy of both GGM and EGGM in various water depth ranges and areas with diverse terrain characteristics.

Accuracy and Resolution of SWOT Altimetry: Foundation Seamounts

AbstractWe assess the accuracy and spatial resolution of the surface water and ocean topography (SWOT) swath altimeter for deriving marine gravity anomalies. The analysis is performed at the Foundation Seamounts in the South Pacific where we developed a highly accurate gravity field by combining the long‐wavelength (>40 km) gravity field derived from previous nadir altimeters with the shorter wavelength gravity field from the seafloor topography as constrained by the ship gravity. In this region, the sea surface slope (SSS) of the ocean variability is 50–100 times smaller than the slope signal of the seamounts so can be ignored in the analysis. Each SWOT cycle can deliver SSS accurately with a standard deviation of 2.6 µrad and a spatial resolution of 14 km at typical sea state (significant wave height 4 m), with accuracy diminishing at high significant wave heights (e.g., exceeds 6 m). Averaging repeated SWOT measurements improves the accuracy and resolution. For example, we expect that averaging just 10 repeats (7 months) results in accuracy/resolution that matches the best marine gravity maps based on 230 months of nadir altimetry. With a mission lasting over a year, SWOT promises a substantial leap in marine gravity accuracy and resolution, uncovering previously uncharted details of the seafloor, including thousands of uncharted seamounts.

High-precision 1′ × 1′ bathymetric model of Philippine Sea inversed from marine gravity anomalies

Abstract. The Philippine Sea, located at the edge of the northwestern Pacific Ocean, possesses complex seabed topography. Developing a high-precision bathymetric model for this region is of paramount importance, as it provides fundamental geoinformation essential for Earth observation and marine scientific research, including plate motion, ocean circulation, and hydrological characteristics. The gravity–geologic method (GGM), based on marine gravity anomalies, serves as an effective bathymetric prediction technique. To further strengthen the prediction accuracy of conventional GGM, we introduce the improved GGM (IGGM). The IGGM considers the effects of regional seafloor topography by employing weighted averaging to more accurately estimate the short-wavelength gravity component, along with refining the subsequent modeling of long-wavelength gravity component. In this paper, we focus on seafloor topography modeling in the Philippine Sea based on the IGGM, combining shipborne bathymetric data with the Scripps Institution of Oceanography (SIO) V32.1 gravity anomaly. To reduce computational complexity, the optimal parameter values required for IGGM are first calculated before the overall regional calculation, and then, based on the terrain characteristics and distribution of sounding data, we selected four representative local sea areas as the research objects to construct the corresponding bathymetric models using GGM and IGGM. The analysis indicates that the precision of the IGGM models in four regions is improved to varying degrees, and the optimal calculation radius is 2′. Based on the above finding, a high-precision 1′×1′ bathymetric model of the Philippine Sea (5–35° N, 120–150° E), known as the BAT_PS model, is constructed using IGGM. Results demonstrate that the BAT_PS model exhibits a higher overall precision compared to the General Bathymetric Chart of the Oceans (GEBCO), topo_25.1, and DTU18 models at single-beam shipborne bathymetric points.

Evaluating the Impact of the Recent Combined and Satellite-Only Global Geopotential Model on the Gravimetric Geoid Model

Geoid represents Earth’s surface, ocean, and gravitational field, which influence the elevations, shape, and mass distribution of the geopotential surface, a hypothetical surface that is perpendicular to the direction of gravity at every point. This geopotential surface serves as a reference for measuring elevations and is used as a fundamental reference surface for geodetic and surveying purposes. In this study, the Least Squares Modification of Stokes Formula (LSMS) with Additive Corrections (AC), also known as the KTH method, is used to generate a new gravimetric geoid model for Peninsular Malaysia. The KTH method was developed at the Royal Institute of Technology (KTH) in Stockholm-Sweden. The dataset used is the most recent global digital elevation model, Shuttle Radar Topography Mission (SRTM) 1 Arc-Second Global, generated by the National Aeronautics and Space Administration (NASA) and the National Imagery and Mapping Agency (NIMA). In addition to this elevation data, the dataset includes the Global Geopotential Model (GGM), which is composed of the XGM2016, XGM2019e, Tongji_GGMG2021S, and Tongji-Grace02k models. Furthermore, it incorporates sets of regional gravity data, including terrestrial gravity, airborne gravity, and marine gravity anomalies, all of which are derived from the Technical University of Denmark (DTU 21). The actual 45 Global Navigation Satellite System (GNSS)-levelling points data have been compared to the gravimetric geoid model developed in this study and the geoid acquired from Department of Survey and Mapping Malaysia (DSMM). According to the statistical results, NXGM2019e provides better accuracy, with the Root Mean Square Error (RMSE) geoid model errors of ±0.033 m, compared to the deviations in free-air anomalies, XGM2019e, which has the minimum RMSE of 10.291 mGal. Meanwhile, Tongji-GMMG2021S has the maximum RMSE of 14.792 mGal. The geoid is derived from the XGM2019e model and has maximum and minimum values of 0.032 m and 0.147 m, respectively, with mean residuals of 0.089 m. In conclusion, the XGM2019e has the potential to determine a precise local geoid model for Peninsular Malaysia

Adaptive Gravity-Aided Inertial Navigation Based on Characteristic Analysis of Marine Gravity Anomaly from Satellite Altimetry

Adaptive Gravity-Aided Inertial Navigation Based on Characteristic Analysis of Marine Gravity Anomaly from Satellite Altimetry

Improving High-Frequency Marine Gravity Anomaly Recovery: The Efficacy of SWOT Wide-Swath Altimetry

Improving High-Frequency Marine Gravity Anomaly Recovery: The Efficacy of SWOT Wide-Swath Altimetry

An improved triple collocation-based integration of multiple gravity anomaly grids from satellite altimetry: Contribution of ICESat-2

Satellite altimetry has been widely used to determine the marine gravity fields. Different altimeter missions lead to different gravity grids with varying spatial resolutions and accuracies. Marine gravity accuracy in offshore waters is often low. Integrating marine gravity anomalies (MGA) derived from various altimeter missions are key to obtaining high-precision and high-resolution global marine gravity fields. Here an improved triple collocation (ITC) method is first proposed to establish a new 1´×1′ marine gravity anomaly in the South China Sea (SCS), named MGAITC, by merging the grids of MGA from the Haiyang-2A (HY-2A), CryoSat-2, and ICESat-2 altimeter measurements. A combined MGA (MGACOM) is also constructed by using the least squares collocation (LSC) method from three sets of altimeter-derived geoid gradients. The qualities of MGAITC, MGACOM and each altimeter-derived MGA grids are assessed using shipborne gravity and different global gravity models over waters of varying depths and distances from the coastline. The accuracy of the MGAITC gravity against the shipborne gravity is 5.52 mGal, which represents improvements of 7%, 9%, 13%, and 3% relative to the gravity grids derived only from ICESat-2, CryoSat-2, HY-2A and from MGACOM. In all assessments involving different sub-regions, seafloors, and distances from the coastline, MGAITC performs the best, and ICESat-2 yields the best single-mission MGA grid, especially in offshore waters. We find that ICESat-2 has a high potential to improve shallow-water gravity accuracy and the global marine gravity field can be improved by integrating gravity grids from different altimetry missions using ITC.

Improving the Accuracy of Seafloor Topography Inversion Based on a Variable Density and Topography Constraint Combined Modification Method

The use of satellite altimetry to recover marine gravity anomalies allows for the rapid acquisition of seafloor topography on a wide range of regional scales. Currently, the commonly used approaches for inverting seafloor topography have been focused on the linear correlation between gravity anomalies and seafloor topography and have disregarded the effect of density contrast between the crust and seawater on depth. Therefore, we proposed a variable density and topography constraint combined modification (VDTCCM) method by deriving Parker’s formula and the Bouguer plate formula by introducing variable density and topography factors. This method can effectively recover topography-related nonlinear terms of gravity anomalies. Subsequently, the seafloor topography of the South China Sea was estimated by applying the VDTCCM method and was defined as Seafloor topography one (ST1), and following, the accuracy was evaluated using shipborne sounding data (SSD). The results indicate that the ST1 model’s SSD-checked accuracy is 23.34% and 39.42% higher than the common international models of ETOPO1 and DTU10, respectively. Moreover, the ST1 model has advantages in mapping rugged areas, showing more detailed topographical features. Consequently, the VDTCCM method can provide beneficial references for the construction of seafloor topography models on a large regional scale using gravity anomalies recovered from satellite altimetry.

Enhanced Short-Wavelength Marine Gravity Anomaly Using Depth Data

Satellite altimetry cannot accurately derive the short-wavelength component of ocean gravity anomaly. Since the short-wavelength seabed topography affects the gravity anomaly, we can forward the short-wavelength gravity anomaly by using seabed topography to make up for the shortcomings of altimetry. Based on the Global Marine Gravity Anomaly version 1 (GMGA1) previously released by our group, and on Parker’s formula, the short-wavelength gravity anomaly is forwarded by using the seabed topographic model SRTM15+V2.4, and a new product, Global Marine Gravity Anomaly Version 2 (GMGA2), is obtained. Compared with internationally recognized gravity field products such as SIO V32.1 and DTU17, the accuracy of GMGA2 is 2.5mGal, which is 0.7 mGal higher than GMGA1, and the absolute differences smaller than 5mGal account for more than 96%. An evaluation using ship-borne gravity data showed the accuracy of GMGA2 is 4.8 mGal, which is 0.3 mGal higher than GMGA1. It is concluded from the above results that using the forward method with water depth data significantly improves the short-wavelength gravity anomaly of the altimetry-derived gravity field model, and the accuracy of GMGA2 is close to that of the advanced international level.

Marine Gravity Anomaly From Satellite Altimetry: Interpolation and Matching Navigation

Marine Gravity Anomaly From Satellite Altimetry: Interpolation and Matching Navigation

Recovering Gravity from Satellite Altimetry Data Using Deep Learning Network

The satellite altimetry missions could measure high-accuracy sea surface heights (SSHs) that can be used to recover the marine gravity field. Traditional methods for estimating the marine gravity field from SSHs all rely on approximate physical correlations between SSHs and gravity, which may neglect nature’s complex nonlinearity. This work presents a new deep network-based method to recover the gravity anomaly. This new method uses a multi-channel convolutional neural network (MCCNN) architecture to capture the nolinear features between ship-borne gravity and a group of input parameters including deflections of the vertical (DOVs), submarine topography and the geo-locations. To validate the gravity, ship-borne gravity anomalies on the two independent cruises were not used in the deep learning process. For comparison, we also estimated the gravity using the traditional inverse Vening Meinesz (IVM) method. Our results indicate that the MCCNN method can derive high-quality marine gravity anomalies. The assessments using 1 mGal-accuracy ship-borne gravity anomalies show that the average accuracy for gravity from MCCNN method is higher than 3 mGal and this method achieves 0.05-0.50 mGal improvement over benchmark methods IVM. Assessed by marine gravity anomaly models with the accuracy of 1-2 mGal, the MCCNN method has shown to improve the accuracy of gravity by at least 4%. Comparisons with the IVM results show that improvements of the MCCNN method were mainly in wavelengths between 8 km and 100 km due to the using of bathymetry. The results show that our deep learning method maintains good performance and is promising for gravity recovering.

Global marine gravity anomalies from multi-satellite altimeter data

In this study, China’s first altimeter satellite Haiyang-2A (HY-2A) data combined observations from CryoSat-2, SARAL/AltiKa, and Jason-1&2 are used to calculate the global (60°S–60°N) marine deflections of the vertical and gravity anomalies named Global Marine Gravity Anomaly Version 1(GMGA1), with grid resolution of 1′ × 1′. The deflections of the vertical from each satellite observations are first derived from the gradients of the geoid height through the least squares method. The deflections of the vertical are then merged by assigning different weights to each satellite product based on their accuracy. Finally, gravity anomalies are obtained by the remove-restore method. The results reveal that the fused deflections of the vertical have an accuracy of 0.4 arcsec in the north component and 0.8 arcsec in the east component. HY-2A’s contribution to the north component of the integrated deflections of the vertical is second only to Cryosat-2. Jason-1/2 accounts for a large proportion of the integrated east components. Compared to worldwide products such as DTU17, Sandwell & Smith V31.1, as well as values from EGM2008, EIGEN-6C4 and XGM2019e_2159, GMGA1 has an accuracy of around 3.3 mGal. By not using HY-2A data, the precision of GMGA1 is reduced by about 0.1 mGal. To further improve the accuracy, seafloor topography information is used to provide short wavelength gravity anomaly. It is verified in the South China Sea (112°E–119E°, 12°N–20°N) using the Parker formula. By combining shipborne depth generated data and GMGA1 through a filtering technique, a new version of gravity anomaly grid with an accuracy improvement of 0.4 mGal in the South China Sea is obtained.Graphical

Определение гравитационных аномалий в акватории Вьетнама и на прилегающей территории по данным спутниковой альтиметрии CryoSat-2

The purpose of this study is to determine marine gravity anomalies with high accuracy using the CryoSat-2 satellite altimetry data in the Middle Vietnamese Sea and the adjacent territory. For this, the mentioned data and the process of determining gravity anomalies from the CryoSat-2 data were analyzed. The record from 818 GNSS-leveling points in Vietnam were used to evaluate and select the best global gravity field model for use in the calculation process. The findings from 31 gauge tidal were also used to assess and select the best mean dynamic topography model for the study area. Marine gravity anomalies in the study area were calculated using data from the CryoSat-2 satellite altimeter at 72 483 measurement points. The calculated results are compared with the ship-derived gravity anomalies at 1025 measurement points for assessment. The research results show that of the Earth Geopotential Model EIGEN6C4 and the Mean Dynamic Topography Model DTU15MDT are the most suitable for the research area. The accuracy of satellite-derived gravity anomalies, calculated from the CryoSat-2 satellite altimetry data in the study area, reaches ±1,18 mGal. Compared to the available results in the study area, this accuracy is the highest.

Accuracy comparison of marine gravity derived from HY-2A/GM and CryoSat-2 altimetry data: a case study in the Gulf of Mexico

SUMMARYThe HaiYang-2A (HY-2A) satellite was launched in August 2011, filling a gap in the field of Chinese altimetry. The application of HY-2A-measured altimeter data in gravity research needs to be studied. CryoSat-2 altimetry data play an important role in constructing global marine gravity models. Based on HY-2A and CryoSat-2 altimetry data of Level-2 plus products from March 2016 to June 2020, marine gravity anomaly models on 1′ × 1′ grids were derived by the inverse Vening–Meinesz (IVM) method over the Gulf of Mexico (80–100°W, 17–32°N). The accuracy of the altimeter-derived gravity was assessed by ship-borne gravity anomalies and the SIO V30.1 global marine gravity model. Then, integrated gravity models on 1′ × 1′ grids were constructed from the altimeter-derived gravity anomaly models by the weighted modification method and the combined altimetry data by IVM method. The results show that the accuracy of altimeter-derived marine gravity anomalies is affected by the coastline and complicated submarine topography. The accuracy of gravity anomalies derived from HY-2A is slightly lower than that derived from CryoSat-2 in the offshore region and regions containing complicated submarine topography, and is consistent with that derived from CryoSat-2 in other regions. The HY-2A-measured altimetry data play a significant role in constructing integrated gravity models. To conclude, the gravity anomalies derived from HY-2A have similar accuracy to those derived from CryoSat-2 during the same period, and HY-2A altimetry data can be used to construct high-precision global/local marine gravity models.

Optimised gravity anomaly fields from along-track multi-mission satellite altimeter over Malaysian seas

Marine gravity anomalies are crucial parameters and elements for determining coastal and ocean geoid, tectonics and crustal structures, as well as offshore studies. This study aims to derive and develop a marine gravity anomaly model over Malaysian seas from multi-mission altimetry data. Universiti Teknologi Malaysia 2020 Mean Sea Surface Model is computed based on along-track data from nine satellite missions, incorporating TOPEX, Jason-1, Jason-2, ERS-2, Geosat Follow on (GFO), Envisat-1, CryoSat-2, SARAL/AltiKa, and Sentinel-3A. The data exploited are from 1993 to 2019 (27 years). Residual gravity anomaly is computed using Gravity Software, and two-dimensional planar Fast Fourier Transformation method is applied. The evaluation, selection, blunder detection, combination, and re-gridding of the altimetry-derived gravity anomalies and Global Geopotential Model data are demonstrated. Cross-validation procedure is employed for data cleaning and quality control using the Kriging interpolation method. Then, cross-validation procedure is applied to the tapering window width 200, which adopting the GECO model denotes the optimum gravity anomaly with root mean square errors in the range of ± 4.2472 mGal to ± 6.0202 mGal. The findings suggest that the estimated marine gravity anomaly is acceptable to be implemented in the marine geoid determination and bathymetry estimation over Malaysian seas. In addition, the results of this study are valuable for geodetic and geophysical applications in marine areas.

Comparison of along-track resolution of SARAL/AltiKa and ENVISAT-RA2 satellite altimeters over continental margins

ABSTRACT The objective of the present study is to systematically quantify the along-track resolution of Satellite for Argos and AltiKa (SARAL)/AltiKa and Environmental Satellite (ENVISAT)-RA2 altimeters over continental margins. Spectral coherence and power spectral density estimated from pairs of stacked (averaged) sea surface height (SSH) profiles from repeat tracks as a function of wave number are used to estimate along-track resolution and noise characteristics, respectively. The analyses were carried out along 96 SARAL/AltiKa and ENIVISAT-RA2 tracks covering continental margins of India, Gulf of Mexico, and South America. Our study clearly suggests that for all three sites the short-wavelength resolution of SARAL/AltiKa (15–18 km) is ~27–33% better than ENVISAT-RA2 (22–25 km) data. Variations in sediment thickness along the continental margins have significant influence in the along-track resolution of both altimeters. Strong geoid signals owing to thin sediments (0.1–0.3 km thick) along the South American margin provided higher resolution for both SARAL/AltiKa (15 km) and ENVISAT-RA2 (22 km) altimeters. Conversely, over the continental margins of India and Gulf of Mexico with huge sediment thickness (1–20 km), the resolution of SARAL/AltiKa and ENVISAT-RA2 drops to 18 and 25 km, respectively. We also observe that resolution of both altimeters is higher by 1–2 km for continental margins with narrow shelf. The present study has implications in the generation of high-resolution marine geoid and gravity anomalies using SARAL/AltiKa along with other altimeters.

Evaluation of Marine Gravity Anomaly Calculation Accuracy by Multi-Source Satellite Altimetry Data

The purpose of this paper is to analyze the influence of satellite altimetry data accuracy on the marine gravity anomaly accuracy. The data of 12 altimetry satellites in the research area (5°N–23°N, 105°E–118°E) were selected. These data were classified into three groups: A, B, and C, according to the track density, the accuracy of the altimetry satellites, and the differences of self-crossover. Group A contains CryoSat-2, group B includes Geosat, ERS-1, ERS-2, and Envisat, and group C comprises T/P, Jason-1/2/3, HY-2A, SARAL, and Sentinel-3A. In Experiment I, the 5′×5′ marine gravity anomalies were obtained based on the data of groups A, B, and C, respectively. Compared with the shipborne gravity data, the root mean square error (RMSE) of groups A, B, and C was 4.59 mGal, 4.61 mGal, and 4.51 mGal, respectively. The results show that high-precision satellite altimetry data can improve the calculation accuracy of gravity anomaly, and the single satellite CryoSat-2 enables achieving the same effect of multi-satellite joint processing. In Experiment II, the 2′×2′ marine gravity anomalies were acquired based on the data of groups A, A + B, and A + C, respectively. The root mean square error of the above three groups was, respectively, 4.29 mGal, 4.30 mGal, and 4.21 mGal, and the outcomes show that when the spatial resolution is satisfied, adding redundant low-precision altimetry data will add pressure to the calculation of marine gravity anomalies and will not improve the accuracy. An effective combination of multi-satellite data can improve the accuracy and spatial resolution of the marine gravity anomaly inversion.

Gravity recovery from SWOT altimetry using geoid height and geoid gradient

The Surface Water and Ocean Topography (SWOT) altimeter mission can measure high-resolution wide-swath sea surface heights (SSHs) that may greatly improve the current accuracy and spatial resolution of marine gravity from nadir-looking altimeters. To investigate the potential of SWOT in recovering high-quality marine gravity and how SWOT observation errors should be treated to optimize the accuracy of gravity anomaly from SWOT observations, we create high-wavenumber SSH components from multi-beam depths in the northern South China Sea (SCS) and simulate SWOT SSH errors. To cross-validate gravity signals and avoid gravity errors from SWOT, we use two computational methods (inverse Vening-Meinesz formula, IVM and inverse Stokes' integral, ISM) and recommend separate optimal data processing strategies when using geoid gradients (GGs) and geoid heights (GHs) for gravity recovery. The use of GGs (for IVM) effectively eliminates systematic errors in gravity derivation. If GHs (for ISM) are used in gravity recovery, the tilt in wide-swath SSHs should be removed before gravity computation, and the recovered gravity must be filtered (post-processed) to avoid artificial gravity signals due to the SSH errors. Our assessments using mgal-accuracy shipborne gravity anomalies in the northern SCS show that multiple-cycle SWOT observations can deliver high-quality marine gravity anomalies. IVM is more robust than ISM in resisting random and systematic errors in SWOT. Our processing strategies can be used for the gravity validation of SSHs from SWOT's fast-sampling and science phases.