Surface Water And Ocean Topography Research Articles

Unveiling three-dimensional sea surface signatures caused by internal solitary waves: insights from the surface water ocean topography mission

Unveiling three-dimensional sea surface signatures caused by internal solitary waves: insights from the surface water ocean topography mission

Improving mean water lake surface elevation estimates using dense lidar measurements from the GEDI satellite mission

Lakes are an essential component of the global water cycle and are considered as sentinels of climate change. An accurate estimate of lake's water levels is necessary for reliable continuous monitoring of their water balance. Due to their huge number worldwide, satellite altimetry has been identified as an efficient tool for measuring their temporal variations of water level. This technique can reach an accuracy of a few centimeters for water level estimates over large lakes. Due to the coarse across-track spatial resolution of the radar altimetry missions, their spatial sampling only covers a small part of the lakes surface. To obtain an accurate estimate of the lake water level, it is necessary to apply a correction to account for the small-scale orthometric height undulations occurring on the lake area and not present in the current global geoid models. In this study, the high-density lidar measurements from GEDI are used to estimate the mean lake surface. From the 1,366,211 GEDI data over 1239 tracks acquired over more than 6000 km2 of the surface of Lake Issy-Kul (Kyrgyzstan, Central Asia) between May 2019 and mid-November 2021, 654,592 shots over 843 tracks were selected after a multi-step quality-check and processed to generate a mean lake surface of Lake Issyk-Kul. Comparison between the GEDI-based mean lake surface and GNSS kinematic surveys corrected from the lake level variations exhibit an RMSE of 0.065 m. The principal objective of performing such mean lake surface is to further use it in the framework of the calibration/validation of the Surface Water and Ocean Topography (SWOT) mission.

Seamount detection using SWOT-derived vertical gravity gradient: advancements and challenges

SUMMARY Launched on 2022 December 16, the Surface Water and Ocean Topography (SWOT) satellite, using synthetic aperture radar interferometric techniques, measures sea surface heights (SSHs) across two 50-km-wide swaths, offering high-resolution and accurate 2-D SSH observations. This study explores the efficiency of SWOT in seamount detection employing the vertical gravity gradient (VGG) derived from simulated SWOT SSH data. Simulated circular and elliptical seamounts (height: 900–1500 m) are integrated within the South China Sea's 4000 m background depths. Geoid perturbations induced by these seamounts are extracted through the residual depth model principle, subsequently merged with the DTU21MSS model for simulating SWOT SSH observations. For comparative assessment, SSH data from Jason-2 and Cryosat-2 are included. An automatic algorithm (AIFS) is presented to identify seamount centres and base polygons using VGG derived from simulated altimeter SSH data. The analysis reveals SWOT-derived VGGs precisely locate all seamount centres, base polygons and elliptical seamount azimuths. The merged Jason-2 and Cryosat-2 data face challenges with identifying small circular and elliptical seamounts. Detecting long narrow elliptical seamounts remains arduous; however, SWOT-derived VGGs successfully elucidate the approximate shapes and major axis azimuths of the elliptical seamounts. Validated against ‘true values’ of VGG, the root-mean-squared deviation (RMSD) of SWOT-derived VGG stands at 1.33 Eötvös, whereas the merged Jason-2 and Cryosat-2 data exhibit an RMSD of 1.93 Eötvös. This study shows the enhanced capability of SWOT from its high-resolution 2-D SSH observations in advancing seamount detection via satellite-derived VGG. We identify challenges and recommend improved detections using data integration and machine learning.

SWOT Level 2 Lake Single-Pass Product: The L2_HR_LakeSP Data Preliminary Analysis for Water Level Monitoring

The Surface Water and Ocean Topography (SWOT) mission, launched in December 2022, aims to address the crucial environmental goal of water monitoring to support preparedness for extreme events and facilitate adaptation to climate change on global and local scales. This mission will provide a comprehensive inventory of worldwide water resources, lakes, reservoir storage, and river dynamics. In this work, we carried out a preliminary assessment of SWOT’s Lake product Level 2 version 1.1, also known as “L2_HR_LakeSP”. The analysis was performed across six diverse lakes on three continents, revealing an average median bias of 0.08 m with respect to the considered reference, after suitable outlier removal. An overall precision of 0.22 m was found, combined with an average correlation of 68% between SWOT and reference time series. Moreover, the accuracy varied in the considered six lakes, since biases up to some decimeters were found for some of them; they could be due to residual inconsistencies between the vertical reference frame of SWOT and that of the considered reference. In summary, the first analysis of the “L2_HR_LakeSP” product, Version 1.1, demonstrated the promising potential of SWOT for monitoring seasonal variations in water levels. Nevertheless, notable anomalies were found in the water masks, particularly in higher latitudes, suggesting potential difficulties in accurately delineating water bodies in those regions. Additionally, a discernible reduction in accuracy was observed towards the end of the monitoring period. These preliminary findings indicate some issues that should be addressed in future investigations about the quality and potential of SWOT’s lake products for advancing our understanding of global water dynamics.

ResORR: A globally scalable and satellite data-driven algorithm for river flow regulation due to reservoir operations

We propose a globally scalable algorithm, ResORR (Reservoir Operations driven River Regulation), to predict regulated river flow and tested it over the heavily regulated basin of the Cumberland River in the US. ResORR was found able to model regulated river flow due to upstream reservoir operations of the Cumberland River. Over a mountainous basin dominated by high rainfall, ResORR was effective in capturing extreme flooding modified by upstream hydropower dam operations. On average, ResORR improved regulated river flow simulation by more than 50% across all performance metrics when compared to a hydrologic model without a regulation module. ResORR is a timely software algorithm for understanding human regulation of surface water as satellite-estimated reservoir state is expected to improve globally with the recently launched Surface Water and Ocean Topography (SWOT) mission.

Enhancing the Assimilation of SWOT Simulated Observations Using a Multi-Scale 4DVAR Method in Regional Ocean Modeling System

This paper presents an innovative approach to enhance the assimilation of high-resolution simulated observations, specifically targeting Surface Water Ocean Topography (SWOT) Ka-band Radar Interferometer Sea Surface Height (SSH) products, within the Regional Ocean Modeling System (ROMS). Responding to the demand for improved assimilation techniques, we developed a multi-scale Four-Dimensional Variational Data Assimilation (4DVAR) system, building upon validated fine-scale correction capabilities from prior studies. The multi-scale strategy was extended to the ROMS-4DVAR system, providing a comprehensive solution for assimilating high-resolution observations. Leveraging the Observing System Simulation Experiment (OSSE) framework, we conducted a twin experiment comprising a nature run and a free run case. Subsequently, synthetic SWOT SSH measurements were decomposed, considering the model configuration resolution. These components, derived from dense SSH observations, were integrated into a two-step 4DVAR assimilation scheme. The first cycle targets large-scale features for model field correction, and the updated analysis serves as the background for the second assimilation step, addressing fine-scale observation components. Comparisons with the primitive ROMS-4DVAR using a single-scale scheme highlight the superiority of the multi-scale strategy in reducing gaps between the model and the SSH observations. The Root Mean Squared Error (RMSE) is halved, and the Mean Absolute Percentage Error (MAPE) decreases from 2.237% to 0.93%. The two-step assimilation procedure ensures comprehensive multi-scale updates in the SSH field simulation, enhancing fine-scale features in the analysis fields. The quantification of three-dimensional-model dynamic fields further validates the efficiency and superiority of the multi-scale 4DVAR approach, offering a robust methodology for assimilating high-resolution observations within the ROMS.

The Surface Water and Ocean Topography Mission: A Breakthrough in Radar Remote Sensing of the Ocean and Land Surface Water

AbstractThe elevations of water surfaces hold important information on the earth's oceans and land surface waters. Ocean sea surface height is related to the internal change of the ocean's density and mass associated with ocean circulation and its response to climate change. The flow rates of rivers and volume changes of lakes are crucial to freshwater supplies and the hazards of floods and drought resulting from extreme weather and climate events. The Surface Water and Ocean Topography (SWOT) Mission is a new satellite using advanced radar technology to make headway in observing the variability of the elevation of water surfaces globally, providing fundamentally new information previously not available to the study of earth's waters. Here, we provide the first results of SWOT over oceans, rivers, and lakes. We demonstrate the potential of the mission to address science questions in oceanography and hydrology.

Enhancing discharge estimation from SWOT satellite data in a tropical tidal river environment

The Surface Water and Ocean Topography (SWOT) mission aims to provide essential data on river width, height and slope in order to estimate worldwide river discharge accurately. This mission offers a powerful tool for monitoring river discharge in dynamic coastal areas, like the Saigon-Dongnai estuary in Southern Vietnam. However, estimating discharge of tidally-influenced rivers using SWOT measurements can be challenging when hydraulic variables have the same order of magnitude as SWOT measurement errors. In this paper we present a methodology to enhance discharge estimation accuracy from SWOT measurements based on simulated SWOT products at the 200 meter node resolution and varying river reach size. We assess measurement error variability and its impact on discharge estimation by employing a Monte Carlo analysis. Our approach significantly improved discharge estimation in the Saigon tidal river, reducing RMSE from 1400 m3/s to 180 m3/s and increasing R² from 0.31 to 0.95. Notably, the percentage of Monte Carlo particles meeting the 30% rRMSE threshold rose from 0% to 79%. This study underscores the feasibility of obtaining reliable discharge estimates from SWOT data in complex coastal areas where hydraulic variables are of the same order of magnitude as SWOT errors. Additionally, the proposed methodology to improve discharge estimation from SWOT measurements is widely adaptable as it can be applied to similar regions and can be combined with any discharge estimation method.

Expected Precision of Gravity Gradient Recovered from Ka-Band Radar Interferometer Observations and Impact of Instrument Errors

Full tensor of gravity gradients contains extremely large amounts of information, which is one of the most important sources for research on recovery seafloor topography and underwater matching navigation. The calculation and accuracy of the full tensor of gravity gradients are worth studying. The Ka-band interferometric radar altimeter (KaRIn) of surface water and ocean topography (SWOT) mission enables high spatial resolution of sea surface height (SSH), which would be beneficial for the calculation of gravity gradients. However, there are no clear accuracy results for the gravity gradients (the gravity gradient tensor represents the second-order derivative of the gravity potential) recovered based on SWOT data. This study evaluated the possible precision of gravity gradients using the discretization method based on simulated SWOT wide-swath data and investigated the impact of instrument errors. The data are simulated based on the sea level anomaly data provided by the European Space Agency. The instrument errors are simulated based on the power spectrum data provided in the SWOT error budget document. Firstly, the full tensor of gravity gradients (SWOT_GGT) is calculated based on deflections of the vertical and gravity anomaly. The distinctions of instrument errors on the ascending and descending orbits are also taken into account in the calculation. The precision of the Tzz component is evaluated by the vertical gravity gradient model provided by the Scripps Institution of Oceanography. All components of SWOT_GGT are validated by the gravity gradients model, which is calculated by the open-source software GrafLab based on spherical harmonic. The Tzz component has the poorest precision among all the components. The reason for the worst accuracy of the Tzz component may be that it is derived by Txx and Tyy, Tzz would have a larger error than Txx and Tyy. The precision of all components is better than 6 E. Among the various errors, the effect of phase error and KaRIn error (random error caused by interferometric radar) on the results is greater than 2 E. The effect of the other four errors on the results is about 0.5 E. Utilizing multi-cycle data for the full tensor of gravity gradients recovery can suppress the effect of errors.

Mapping inundated bathymetry for estimating lake water storage changes from SRTM DEM: A global investigation

Lake water budgets are sensitive to climate change and human activities and have been undergoing rapid changes worldwide over the past few decades. Satellite altimeters greatly promote the large-scale monitoring of lake level and storage variations. However, limited spatiotemporal coverage of the existing individual altimeters prevents long-term and spatially seamless observations on global lakes. These limitations are partially surmounted by the gridded digital elevation model (DEM) data, which can facilitate spatially contiguous measurements of lake bathymetry exposed at the low-level period. The high-resolution SRTM DEM has been widely used for estimating lake level variations due to its early collection time and reliable data quality, while how many lakes worldwide and to what extent of the newly inundated areas can be monitored based on SRTM DEM remains unexplored. Here, we conduct a quasi-global investigation of SRTM DEM regarding its capability of mapping inundated-area bathymetry and estimating lake storage variations. After generating a global-scale lake inventory (122,444 lakes below 60°N, >1 km2) representing the maximum water inundation extents between 1984 and 2020, the feasibility of mapping lake inundated-area bathymetry was evaluated by comparing the maximum inundated area with the waterbody extent derived from SRTM DEM and analyzing the characteristics of interannual and seasonal variability of each lake. Results show that the maximum exposed lake bathymetries from the SRTM DEM data cover an area of 372,986 km2, accounting for 15.95% of the maximum water area of our investigated lakes. Climate-driven lake expansions or human-induced reservoir impoundments after 2000 (the SRTM mission period) are the main contributors to the higher availability of SRTM DEM-based bathymetry mapping on the Tibetan Plateau, India, eastern China, and Amazon Plains. As the newly launched Surface Water and Ocean Topography (SWOT) mission is anticipated to monitor lake water budget variation at an unprecedented resolution, this study provides a base map for supplementing inundated bathymetry information. The joint use of SRTM and SWOT-based observations will extend the time and space extents of lake-level measurements, thereby enhancing our understanding of lake dynamics at a longer timescale.

A network design approach for citizen science-satellite monitoring of surface water volume changes in Bangladesh

This study introduces a reproducible and integrated framework for gauge network design for tracking surface water availability in a citizen science framework. For identifying the optimal number and location of gauges, the framework uses Monte Carlo simulations. With randomized selection of gauges from an existing high-density network, the framework does not impose a single optimal solution but rather provides a range of optimal solutions, allowing water managers the freedom to select the number of gauges and locations in accordance with their specific needs. Using the methodology, the study revealed how a strategic placement of gauges can potentially improve the estimation of surface water storage variations. The study findings can be used to enhance the assessment of lake products derived from missions such as the Surface Water and Ocean Topography (SWOT).

Inversion method of deflection of the vertical based on SWOT wide-swath altimeter data

The deflection of the vertical (DOV) is the key information in the study of ocean gravity field. However, in most areas, the precision of the prime component of DOV is significantly lower than that of the meridian component. To obtain higher accuracy and resolution of ocean gravity information, researchers have proposed a novel altimeter called the wide-swath altimeter. This altimeter allows for the simultaneous acquisition of high-precision and high-resolution two-dimensional measurements of sea surface height (SSH). In this paper, the Surface Water and Ocean Topography (SWOT) mission with a wide-swath altimeter on board is selected for research. One cycle of SWOT sea surface height data is simulated to inverse the DOV in the Arabian Sea (45°E—80°E, 0°–30°N), and the inversion results are compared with those of conventional altimeter data. The results demonstrate that the difference between the meridian and prime components derived from the inversion of SWOT wide-swath data is minimal, significantly outperforming the inversion results of conventional nadir altimeter data. The advantage of SWOT wide-swath altimeter lies in its ability to use the multi-directional geoid slope at any sea surface measurement point to invert the components in the meridian and prime directions. To investigate the impact of this advantage on inversion precision, this paper employs a method to calculate the gradient of the geoid in multiple directions to invert DOV components. The improvement effect of calculating the gradient of the geoid in multiple directions on the precision of DOV component is analyzed. It is found that the accuracy of DOV inversion has significantly improved with the increase of geodetic gradient calculation direction. In addition, the effects of various errors and grid spacing in SWOT wide sea surface height data on the precision of DOV inversion are also analyzed.

Steric heights of submesoscale processes and internal gravity waves in the subtropical northwestern Pacific and northern South China Sea as revealed by moored observations

The Surface Water and Ocean Topography (SWOT) altimeter mission provides a good opportunity to globally detect submesoscale processes (submesoscales) from high-resolution sea surface height (SSH) measurements. However, in addition to the balanced mesoscale eddies and submesoscales, the measured SSH also contains signals of unbalanced internal gravity waves (IGWs) including internal tides (ITs) and supertidal IGWs (IGWs with frequencies of 3–8 cycles per day). Therefore, a quantitative understanding of the contributions of the above multiscale dynamic processes to the SSH is a prerequisite for exploring submesoscales from the SWOT-derived SSH data. Here, this issue was investigated through analyzing one-year moored observation-derived near-surface steric heights (SHs) in the subtropical northwestern Pacific (NWP) and northern South China Sea (SCS) which have different dynamic backgrounds. In the sense of annual mean, the root-mean-squared (RMS) SHs of submesoscales (defined as processes with periods of 2–15 days here) and IGWs in the SCS are 1.30 and 5.54 cm, respectively, while they are only 0.70 and 3.19 cm in the NWP. Seasonally, the RMS SH of submesoscales is larger in winter than summer in both regions; with respect to the IGWs, their RMS SH is larger in summer than winter in the SCS but it is opposite in the NWP. Generally, the SHs of diurnal and semidiurnal ITs are dominated by the stationary component in both regions but the proportion of the nonstationary component is much larger in the NWP than the SCS. The sum of the SHs by nonstationary diurnal and semidiurnal ITs exceeds that of submesoscales except in winter in the SCS. Furthermore, we also found that the SHs of supertidal IGWs are always larger than those of submesoscales in both regions and both seasons. By decomposing the IGWs with frequencies of 1–8 cpd (i.e., cycles per day) into different baroclinic modes, we found that for all of the IGWs bands, the SHs are overwhelmingly attributed to the first mode. The results in this study will provide useful information for the application of SWOT data in regions with active IGWs.

Ocean 2D eddy energy fluxes from small mesoscale processes with SWOT

Abstract. We investigate ocean dynamics at different scales in the Agulhas Current system, a region of important interocean exchange of heat and energy. While ocean observations and some of the most advanced climate models capture the larger mesoscale dynamics (> 100 km), the smaller-scale fronts and eddies are underrepresented. The recently launched NASA–CNES Surface Water and Ocean Topography (SWOT) wide-swath altimeter mission observes the smaller ocean geostrophic scales down to 15 km in wavelength globally. Here we will analyse different eddy diagnostics in the Agulhas Current region and quantify the contributions from the larger mesoscales observable today and the smaller scales to be observed with SWOT. Surface geostrophic diagnostics of eddy kinetic energy, strain, and energy cascades are estimated from modelled sea surface height (SSH) fields of the Massachusetts Institute of Technology general circulation model (MITgcm) latitude–longitude polar cap (LLC4320) simulation subsampled at 1/10∘. In this region, the smaller scales (<150 km) have a strong signature on the horizontal geostrophic strain rate and for all eddy diagnostics in the Western Boundary Current and along the meandering Agulhas Extension. We investigate the horizontal cascade of energy using a coarse-graining technique, and we observe that the wavelength range where the inverse cascade occurs is biased towards larger mesoscale wavelengths with today’s altimetric sampling. We also calculate the projected sampling of the eddy diagnostics under the SWOT swaths built with the NASA–CNES simulator to include the satellite position and realistic noise. For the swaths, a neural network noise mitigation method is implemented to reduce the residual SWOT random error before calculating eddy diagnostics. In terms of SSH, observable wavelengths of 15 to 20 km are retrieved after neural network noise mitigation, as opposed to wavelengths larger than 40 km before the noise reduction.

The Tikhonov-L-curve regularization method for determining the best geoid gradients from SWOT altimetry

The Surface Water and Ocean Topography (SWOT) mission generates dense altimetry data that, when used in geoid gradient component estimations through least-squares collocation (LSC), lead to an ill-conditioned problem. Such problems also arise in geodetic network designs. This study introduces the Tikhonov-L-curve regularization to effectively address this challenge. By pinpointing the maximum curvatures of the L-curve, we discern optimal regularization parameters, countering issues stemming from the dense data of SWOT and the resulting ill-conditioned covariance matrices. Our approach not only stabilizes LSC solutions but also achieves gradient accuracies at 1-microrad levels compared to theoretical values. Additionally, we experimented with a strategic removal process that selectively eliminates adjacent geoid gradients. This technique considerably improves geoid gradient component determinations, especially evident at a threshold distance of 0.755 km within an 8′× 8′ data selection window. While our findings are rooted in simulated SWOT data, they are pivotal for future research intending to employ real SWOT data, anticipated by late 2023. This work serves as a precursor for marine gravity field determinations, emphasizing the importance of stabilized LSC solutions to avoid misleading seafloor signatures due to data compactness.

In Situ Validation of Altimetry and CFOSAT SWIM Measurements in a High Wave Environment

Abstract While satellite altimeters have revolutionized ocean science, validation measurements in high wave environments are rare. Using geodetic Global Navigation Satellite System (GNSS) data collected from the Southern Ocean Flux Station (SOFS; −47°S, 142°E) since 2019, as part of the Southern Ocean Time Series (SOTS), we present a validation of satellite missions in this energetic region. Here we show that high rate GNSS observations at SOFS can successfully measure waves in the extreme conditions of the Southern Ocean and obtain robust measurements in all wave regimes [significant wave height (SWH) ranging from 1.5 to 12.6 m]. We find good agreement between the in situ and nadir altimetry SWH (RMSE = 0.16 m, mean bias = 0.04 m, and n = 60). Directional comparisons with the Chinese–French Ocean Satellite (CFOSAT) Surface Waves Investigation and Monitoring (SWIM) instrument also show good agreement, with dominant directions having an RMSE of 9.1° (n = 22), and correlation coefficients between the directional spectra ranging between 0.57 and 0.79. Initial sea level anomaly (SLA) estimates capture eddies propagating through the region. Comparisons show good agreement with daily gridded SLA products (RMSE = 0.03 m, and n = 205), with scope for future improvement. These results demonstrate the utility of high rate geodetic GNSS observations on moored surface platforms in highly energetic regions of the ocean. Such observations are important to maximize the geophysical interpretation from altimeter missions. In particular, the ability to provide collocated directional wave observations and SLA estimates will be useful for the validation of the recently launched Surface Water and Ocean Topography (SWOT) mission where understanding the interactions between sea state and sea surface height poses a major challenge.

Reconstruction of Surface Kinematics From Sea Surface Height Using Neural Networks

AbstractThe Surface Water and Ocean Topography (SWOT) satellite is expected to observe sea surface height (SSH) down to scales approaching ∼15 km, revealing submesoscale patterns that have never before been observed on global scales. Features at these soon‐to‐be‐observed scales, however, are expected to be significantly influenced by internal gravity waves, fronts, and other ageostrophic processes, presenting a serious challenge for estimating surface velocities from SWOT observations. Here we show that a data‐driven approach can be used to estimate the surface flow, particularly the kinematic signatures of smaller scale flows, from SSH observations, and that it performs significantly better than using the geostrophic relationship. We use a Convolutional Neural Network (CNN) trained on submesoscale‐permitting high‐resolution simulations to test the possibility of reconstructing surface vorticity, strain, and divergence from snapshots of SSH. By evaluating success using pointwise accuracy and vorticity‐strain‐divergence joint distributions, we show that the CNN works well when inertial gravity wave amplitudes are relatively weak. When the wave amplitudes are strong, reconstructions of vorticity and strain are less accurate; however, we find that the CNN naturally filters the wave‐divergence, making divergence a surprisingly reliable field to reconstruct. We also show that when applied to realistic simulations, a CNN model pretrained with simpler simulation data performs well, indicating a possible path forward for estimating real flow statistics with limited observations.

Assessing the potential for the Surface Water and Ocean Topography (SWOT) mission for constituent flux estimations

The recently launched Surface Water and Ocean Topography (SWOT) satellite will simultaneously measure river surface water widths, elevations, and slopes. These novel observations combined with assumptions for unobserved bathymetry and roughness enable the derivation of river discharge. Derived discharge data will not be available until the fall of 2023, despite the satellite having completed approximately 6 months of observations for validation and calibration and transitioning into the nominal orbit phase. SWOT has an irregular flyover frequency, ranging from roughly 1 to 10 times per 21 days. Here, we present how best to use SWOT data when it becomes live, including consideration of how best to accommodate or utilize the irregular flyover frequency of SWOT as it intersects with river reaches. We investigate the predicted capabilities of SWOT for several major rivers using synthetic/theoretical SWOT time series data and evaluate how the characteristics of river discharge dynamics and SWOT sampling frequency impact discharge estimates. This analysis indicates the irregular frequency of SWOT best captures the hydrology of larger, more stable, rivers but presents challenges in smaller, flashier rivers, particularly when sampling frequency decreases (i.e., falls to once per 21 days). Further, the use of SWOT discharge for quantifying constituent fluxes is considered. We provide recommendations concerning how to best use SWOT data for applications related to hydrology and biogeochemistry, including how to design studies to accommodate its irregular orbit cycle.

Regional modeling of internal-tide dynamics around New Caledonia – Part 1: Coherent internal-tide characteristics and sea surface height signature

Abstract. The southwestern tropical Pacific exhibits a complex bathymetry and represents a hot spot of internal-tide generation. Based on a tailored high-resolution regional model, we investigate for the first time the internal-tide field around the New Caledonia islands through energy budgets that quantify the coherent internal-tide generation, propagation, and dissipation. A total of 15.27 GW is converted from the barotropic to the baroclinic M2 tide with the main conversion sites associated with the most prominent bathymetric structures such as continental slopes and narrow passages in the north (2.17 GW) and ridges and seamounts south of New Caledonia (3.92 GW). The bulk of baroclinic energy is generated in shallow waters around 500 m depth and on critical to supercritical slopes, highlighting the limitations of linear semi-analytical models in those areas. Despite the strongly dominant mode-1 generation, more than 50 % of the locally generated energy either dissipates in the near field close to the generation sites or loses coherence. The remaining baroclinic energy propagates within well-defined tidal beams with baroclinic energy fluxes of up to 30 kW m−1 toward the open ocean. The New Caledonia site represents a challenge for SWOT (Surface Water and Ocean Topography) observability of balanced motion in the presence of internal tides with sea surface height (SSH) signatures >6 cm at similar wavelengths. We show for our study region that a correction of SSH for the coherent internal tide potentially increases the observability of balanced motion from wavelengths >160 km to well below 100 km.

Calibration of the Instrumental Errors on Marine Gravity Recovery from SWOT Altimeter

The wide-swath altimetry mission, Surface Water and Ocean Topography (SWOT), makes it possible to further break through the accuracy and resolution of marine gravity field recovery. However, as its main payload, the Ka-band radar interferometer (KaRIN) is easy to be affected by the spacecraft attitude, mechanical deformations and dual antenna signal reception status, which generates instrumental errors including roll errors, phase errors, baseline dilation errors, timing errors, and KaRIN noise. Together with ocean temporal variations, the instrumental errors have large effects on the SWOT Sea Surface Height (SSH) observations and hence the marine gravity field recovery. Here, taking the sea area around Japan as an example, we investigated the calibrations of instrumental errors and ocean temporal variations on the recovery of the marine gravity field. The SSH observations of SWOT are first simulated by Mean Sea Surface (MSS), Absolute Dynamic Topography (ADT), Mean Dynamic Topography (MDT) and instrumental errors. Next, the influence of instrumental errors on determining vertical deflection within single-cycle data was analyzed. Then, three calibration methods (KaRIN/KaRIN cross-calibration, Representative KaRIN/KaRIN cross-calibration, and KaRIN/Nadir cross-calibration) are used to reduce the instrumental errors; the experimental results show KaRIN/KaRIN cross-calibration is the optimal one. Last, for the multi-cycle observations containing ocean temporal variations, crossover calibration is done in single cycle and then followed by collinear adjustment in multi-cycles. This approach is verified by considering 18 simulated cycles that cover almost 1 year. Our result indicates an improvement in the accuracy of marine gravity anomaly by about 45% compared to that of one cycle. The calibration strategy of instrumental errors and ocean temporal variations can be used for high-precision marine gravity field recovery with abundant SWOT observations in the near future.