Search Results (18)

Climate wave data, derived from significant wave height (SWH) altimetry, provide accurate information towards nearshore and coastal areas. Their use is crucial to enhance our capabilities of observing, understanding, and forecasting storm waves, even in complex coastal basins. In this study, SWOT nadir data were combined with nine existing altimeters for assessing waves and monitoring their evolution during storms in the English Channel, near UK–French coasts. Validation against wave buoys and numerical models shows high accuracy, with correlations around 95%, decreasing to 85% when buoy track offsets > 50 km, producing the largest errors. The multi-source approach enables depth-resolved monitoring, with SWH mapping revealing ~20–25% modulation in the Channel and ~36% dissipation near the Seine Bay during storms. Spectral analysis of multi-source altimeter-derived merged observations improve time-sampling, resolving high-frequency variability from monthly to daily scales and capturing ~75% of storms. Most storm wave features along altimetry tracks are resolved, with CFOSAT mapping nearshore areas and SWOT capturing coastal zones, both achieving ~80% variance. This temporal and spatial monitoring would be further enhanced with SWOT’s 2D wide swath. This finding provides a complementary, comprehensive understanding of coastal waves and offers valuable input for data assimilation, to improve storm wave estimates in coastal basins. Full article

Mesoscale coastal eddies are key components of ocean circulation, mediating the transport of heat, nutrients, and marine debris. The Surface Water and Ocean Topography (SWOT) mission provides high-resolution sea surface height data, offering a novel opportunity to improve the observation and characterization of these features, especially in coastal regions where conventional altimetry is limited. In this study, we investigate a mesoscale anticyclonic coastal eddy observed southwest of Mallorca Island, in the Balearic Sea, to assess the impact of SWOT-enhanced altimetry in resolving its structure and dynamics. Initial eddy identification is performed using satellite ocean color imagery, followed by a qualitative and quantitative comparison of multiple altimetric datasets, ranging from conventional nadir altimetry to wide-swath products derived from SWOT. We analyze multiple altimetric variables—Sea Level Anomaly, Absolute Dynamic Topography, Velocity Magnitude, Eddy Kinetic Energy, and Relative Vorticity—highlighting substantial differences in spatial detail and intensity. Our results show that SWOT-enhanced observations significantly improve the spatial characterization and dynamical depiction of the eddy. Furthermore, Lagrangian transport simulations reveal how altimetric resolution influences modeled transport pathways and retention patterns. These findings underline the critical role of SWOT in advancing the monitoring of coastal mesoscale processes and improving our ability to model oceanic transport mechanisms. Full article

Sea surface height (SSH) serves as a fundamental geophysical parameter in oceanographic research. In 2023, China successfully launched the world’s first spaceborne interferometric GNSS-R (iGNSS-R) altimeter, which features dual-frequency multi-beam scanning, interferometric processing, and compatibility with three major satellite navigation systems: the BeiDou Navigation Satellite System (BDS), the Global Positioning System (GPS), and the Galileo Satellite Navigation System (GAL). This launch marked the first in-orbit validation of the iGNSS-R altimetry technology. This study provides a detailed overview of the iGNSS-R payload design and analyzes its dual-frequency delay mapping (DM) measurements. We developed a refined DM waveform-matching algorithm that precisely extracts the propagation delays between reflected and direct GNSS signals, enabling the retrieval of global sea surface height (SSH) through the interferometric altimetry model. For validation, we employed an inter-satellite crossover approach using Jason-3 and Sentinel-6 radar altimetry as references, achieving an unprecedented SSH accuracy of 17.2 cm at a 40 km resolution. This represents a breakthrough improvement over previous GNSS-R altimetry efforts. The successful demonstration of iGNSS-R technology opens up new possibilities for cost-effective, wide-swath sea level monitoring. It showcases the potential of GNSS-R technology to complement existing ocean observation systems and enhance our understanding of global sea surface dynamics. Full article

Traditional methods for the construction of intertidal digital elevation models (DEMs) require the integration of long-term multi-sensor datasets and struggle to capture the spatiotemporal variation caused by ocean dynamics. The SWOT (surface water and ocean topography) mission, with its wide-swath interferometric altimetry technology, provides instantaneous full-swath elevation data in a single pass, offering a revolutionary data source for high-precision intertidal topographic monitoring. This study presents a framework for SWOT-based intertidal DEM extraction that integrates data preprocessing, topographic slope map construction, and tidal channel masking. The radial sand ridge region along the Jiangsu coast is analyzed using SWOT L2 LR (Low Resolution) unsmoothed data from July 2023 to December 2024. Multisource validation data are used to comprehensively assess the accuracy of sea surface height (SSH) and land elevation derived from LR products. Results show that the root mean square error (RMSE) of SSH at Dafeng, Yanghe, and Gensha tide stations is 0.25 m, 0.19 m, and 0.32 m, respectively. Validation with LiDAR data indicates a land elevation accuracy of ~0.3 m. Additionally, the topographic features captured by LR products are consistent with the patterns observed in the remote sensing imagery. A 16-month time-series analysis reveals significant spatiotemporal variations in the Tiaozini area, particularly concentrated in the tidal channel areas. Furthermore, the Pearson correlation coefficient for the DEMs generated from SWOT data decreased from 0.94 over a one-month interval to 0.84 over sixteen months, reflecting the persistent impact of oceanic dynamic processes on intertidal topography. Full article

New observations of ocean surface topography obtained by wide-swath satellite interferometry require new capabilities to process spatially correlated errors in order to assimilate these data into numerical models. The sea surface height (SSH) variations have to be weighted against other types of assimilated data using information on their precision, as represented by the inverse of the SSH error covariance matrix $\mathit{R}$. The latter can be well approximated by a block-circulant (BC) structure and, therefore, allows numerically efficient implementation in operational data assimilation (DA) systems. In this note, we extend the technique of approximating $\mathit{R}$ for wide-swath altimeters by including the uncertainties associated with the state of the atmosphere. It is shown that such an extension keeps the BC approximation error within acceptable (±10%) bounds in a wide range of environmental conditions and could be beneficial for improving the accuracy of SSH retrievals from wide-swath altimeter observations. Full article

The SWOT satellite, carrying the KaRIN first wide-swath onboard altimeter, was launched in December 2022, and has now delivered more than a year of surface water elevation data over the ocean and inland lakes/rivers. These data are affected by systematic errors which constitute the dominant part of the error budget at scales larger than a few thousands of kilometers. Some strategies for their estimation and calibration were explored during the pre-launch studies with performance estimations. Now, based on the real data, we propose in this study to assess the systematic error budget with statistical methods relying on spectral and co-spectral analysis. From this assessment, suggesting very low error levels (below requirements), we propose the implementation of the calibration algorithms at Level-2 and Level-3 with a few minor adjustments justified by the error spectra. The calibrated products are then validated with usual CalVal metrics. Full article

Conventional altimetry has greatly advanced our understanding of mesoscale eddies but falls short in studying fine-scale eddies (<150 km). The newly launched Surface Water and Ocean Topography (SWOT) altimeter, however, with its unprecedented high-resolution capabilities, offers new opportunities to observe these fine-scale eddies. In this study, we use SWOT data to explore these previously elusive fine-scale eddies in the Kuroshio Extension. During SWOT’s fast sampling phase from 29 May 2023 to 10 July 2023, we identified an average of 4.5 fine-scale eddies within each 120 km wide swath. Cyclonic eddies, which are slightly more frequent than the anticyclonic ones (ratio of 1.16), have a similar mean radius of 23.4 km. However, cyclonic eddies exhibit higher amplitudes, averaging 3.5 cm compared to 2.8 cm for anticyclonic eddies. In contrast to the mesoscale eddies detected by conventional altimeters, the fine-scale eddies revealed by SWOT are characterized by smaller sizes and weaker amplitudes. This study offers a preliminary view of fine-scale eddy characteristics from space, highlighting SWOT’s potential to advance our understanding of these dynamic processes. Nonetheless, it also emphasizes the necessity for comprehensive analysis to fully exploit the satellite’s capabilities in monitoring and interpreting complex eddy behaviors. Full article

The recently deployed Surface Water and Ocean Topography (SWOT) mission for the first time has observed the ocean surface at a spatial resolution of 1 km, thus giving an opportunity to directly monitor submesoscale sea surface height (SSH) variations that have a typical magnitude of a few centimeters. This progress comes at the expense of the necessity to take into account numerous uncertainties in calibration of the quality-controlled altimeter data. Of particular importance is the proper filtering of spatially correlated errors caused by the uncertainties in geometry and orientation of the on-board interferometer. These “systematic” errors dominate the SWOT error budget and are likely to have a notable signature in the SSH products available to the oceanographic community. In this study, we explore the utility of the block-circulant (BC) approximation of the SWOT precision matrix developed by the Jet Propulsion Laboratory for assessment of a mission’s accuracy, including the possible impact of the systematic errors on the assimilation of the wide-swath altimeter data into numerical models. It is found that BC approximation of the precision matrix has sufficient (90–99%) accuracy for a wide range of significant wave heights of the ocean surface, and, therefore, could potentially serve as an efficient preconditioner for data assimilation problems involving altimetry observations by space-borne interferometers. An extensive set of variational data assimilation (DA) experiments demonstrates that BC approximation provides more accurate SSH retrievals compared to approximations, assuming a spatially uncorrelated observation error field as is currently adopted in operational DA systems. Full article

The interferometric imaging radar altimeter (InIRA), mounted on the Tiangong-2 space laboratory, utilizes a small incidence and a short interferometric baseline to achieve altimetry for wide swathes of ocean surface topography and inland water surface elevation. To obtain a high-precision digital elevation model (DEM), calibration of the interferometric system parameters is necessary. Because InIRA utilizes the small-incidence interference system design, serious coupling occurs between the interferometric parameters. Commonly used interferometric calibration methods tend to fall into the local optimal solution for InIRA. Because evolutionary algorithms have a stronger robustness and global search ability, they are better suited to handling the solution space structure under the coupling of complex interferometric parameters. This article establishes an interferometric calibration optimization model for InIRA by utilizing the relative flatness of the lake surface as an inequality constraint. Furthermore, an adaptive penalty coefficient constraint evolutionary algorithm is designed to solve the model. The proposed method was tested on actual InIRA data, and the results indicate that it efficiently adjusts interferometric parameters, enhancing the precision of measurements for Qinghai Lake elevation. Full article

The upcoming technology of wide-swath altimetry from space will enable monitoring the ocean surface at 4–5 times better spatial resolution and 2–3 times better accuracy than traditional nadir altimeters. This development will provide a chance to directly observe submesoscale sea surface height (SSH) variations that have a typical magnitude of a few centimeters. Taking full advantage of this opportunity requires correct treatment of the correlated SSH errors caused by uncertainties in environmental conditions beneath the satellite and in the geometry and orientation of the on-board interferometer. These observation errors are highly correlated both along and across the surface swath scanned by the satellite, and this presents a significant challenge for accurate processing. In particular, the SWOT precision matrix has off-diagonal elements that are too numerous to allow standard approaches to remain tractable. In this study, we explore the utility of a block-diagonal approximation to the SWOT precision matrix in order to reconstruct SSH variability in the region east of Greenland. An extensive set of 2dVar assimilation experiments demonstrates that the sparse approximation proposed for the precision matrix provides accurate SSH retrievals when the background-to-observation error ratio ν does not exceed 3 and significant wave height is below 2.5 m. We also quantify the range of ν and significant wave heights over which the retrieval accuracy of the exact spatially correlated SWOT error model will outperform the uncorrelated model. In particular, the estimated range is found to be substantially wider ($\nu <10$ with significant wave heights below 8–10 m), indicating the potential benefits of further improving the accuracy of approximations for the SWOT precision matrix. Full article

Surface wind speed measurements from a satellite radar altimeter are used to adjust altimeter sea level measurements via sea state bias range correction. We focus here on previously neglected ocean radar backscatter and subsequent wind speed variations due to sea surface temperature (SST) change that may impact these sea level estimates. The expected error depends on the radar operating frequency and may be significant at the Ka band (36 GHz) frequency chosen for the new Surface Water and Ocean Topography (SWOT) satellite launched in December 2022. SWOT is expected to revolutionize oceanography by providing wide-swath Ka band observations and enhanced spatial resolution compared to conventional Ku band (14 GHz) altimetry. The change to the Ka band suggests a reconsideration of SST impact on wind and sea level estimates, and we investigate this in advance of SWOT using existing long-term Ku and Ka band satellite altimeter datasets. This study finds errors up to 1.5 m/s in wind speed estimation and 1.0 cm in sea level for AltiKa altimeter data. Future SWOT data analyses may require consideration of this dependence prior to using its radar backscatter data in its sea level estimation. Full article

Scientometric reviews, facilitated by computational and visual analytical approaches, allow researchers to gain a thorough understanding of research trends and areas of concentration from a large number of publications. With the fast development of satellite altimetry, which has been effectively applied to a wide range of research topics, it is timely to summarize the scientific achievements of the previous 50 years and identify future trends in this field. A comprehensive overview of satellite altimetry was presented using a total of 8541 publications from the Web of Science Core Collection covering the years from 1970 to 2021. We begin by presenting the fundamental statistical results of the publications, such as the annual number of papers, study categories, countries/regions, afflictions, journals, authors, and keywords, in order to provide a comprehensive picture of satellite altimetry research. We discuss the co-occurrence of the authors in order to reveal the global collaboration network of satellite altimetry research. Finally, we utilised co-citation networks to detect the development trend and associated crucial publications for various specific topics. The findings show that satellite altimetry research has been changed immensely during the last half-century. The United States, France, China, England, and Germany made the most significant contributions in the field of satellite altimetry. The analysis reveals a clear link between technology advancements and the trend in satellite altimetry research. As a result, wide swath altimetry, GNSS-reflectometry, laser altimetry, terrestrial hydrology, and deep learning are among the most frontier study subjects. The findings of this work could guide a thorough understanding of satellite altimetry’s overall development and research front. Full article

The upcoming technology of wide-swath altimetry from space will deliver a large volume of data on the ocean surface at unprecedentedly high spatial resolution. These data are contaminated by errors caused by the uncertainties in the geometry and orientation of the on-board interferometer and environmental conditions, such as sea surface roughness and atmospheric state. Being highly correlated along and across the swath, these errors present a certain challenge for accurate processing in operational data assimilation centers. In particular, the error covariance matrix $\mathit{R}$ of the Surface Water and Ocean Topography (SWOT) mission may contain trillions of elements for a transoceanic swath segment at kilometer resolution, and this makes its handling a computationally prohibitive task. Analysis presented here shows, however, that the SWOT precision matrix ${\mathit{R}}^{-1}$ and its symmetric square root can be efficiently approximated by a sparse block-diagonal matrix within an accuracy of a few per cent. A series of observational system experiments with simulated data shows that such approximation comes at the expense of a relatively minor reduction in the assimilation accuracy, and, therefore, could be useful in operational systems targeted at the retrieval of submesoscale variability of the ocean surface. Full article

The spaceborne interferometric synthetic aperture radar (InSAR) is expected to measure the sea surface height (SSH) with high accuracy over a wide swath. Since centimeter-level accuracy is required to monitor the ocean sub-mesoscale dynamics, the high accuracy implies that the altimetric errors should be totally understood and strictly controlled. However, for the dynamic waves, they move randomly all the time, and this will lead to significant altimetric errors. This study proposes an analytical method for the dynamic wave-related errors of InSAR SSH measurement based on the wave spectrum and electromagnetic scattering model. Additionally, the mechanisms of the dynamic wave-related errors of InSAR altimetry are analyzed, and the detailed numerical model is derived. The proposed analytical method is validated with NASA’s Surface Water and Ocean Topography (SWOT) project error budget, and the Root-Mean-Square Errors (RMSEs) are in good agreement (0.2486 and 0.2470 cm on a 0.5 km² grid, respectively). Instead of analysis for a typical project, the proposed method can be applied to different radar parameters under multiple sea states. The RMSEs of Ka-band under low sea state, moderate sea state, and high sea state are 0.2670, 1.3154, and 6.6361 cm, respectively. Moreover, the RMSEs of X-band and Ku-band are also simulated and presented. The experimental results demonstrate that the dynamic wave-related errors of InSAR altimetry are not sensitive to the frequencies but are sensitive to the sea states. The error compensation method is necessary for moderate and higher sea states for centimetric accuracy requirements. This can provide feasible suggestions on system design and error budget for the future interferometric wide-swath altimeter. Full article

Over the last few years, a very active field of research has aimed at exploring new data-driven and learning-based methodologies to propose computationally efficient strategies able to benefit from the large amount of observational remote sensing and numerical simulations for the reconstruction, interpolation and prediction of high-resolution derived products of geophysical fields. In this paper, we investigate how they might help to solve for the oversmoothing of the state-of-the-art optimal interpolation (OI) techniques in the reconstruction of sea surface height (SSH) spatio-temporal fields. We focus on two small $10°\times 10°$ GULFSTREAM and $8°\times 10°$ OSMOSIS regions, part of the North Atlantic basin: the GULFSTREAM area is mainly driven by energetic mesoscale dynamics, while OSMOSIS is less energetic but with more noticeable small spatial patterns. Based on observation system simulation experiments (OSSE), we used a NATL60 high resolution deterministic ocean simulation of the North Atlantic to generate two types of pseudo-altimetric observational dataset: along-track nadir data for the current capabilities of the observation system and wide-swath SWOT data in the context of the upcoming SWOT (Surface Water Ocean Topography) mission. We briefly introduce the analog data assimilation (AnDA), an up-to-date version of the DINEOF algorithm, and a new neural networks-based end-to-end learning framework for the representation of spatio-temporal irregularly-sampled data. The main objective of this paper consists of providing a thorough intercomparison exercise with appropriate benchmarking metrics to assess whether these approaches help to improve the SSH altimetric interpolation problem and to identify which one performs best in this context. We demonstrate how the newly introduced NN method is a significant improvement with a plug-and-play implementation and its ability to catch up the small scales ranging up to 40 km, inaccessible by the conventional methods so far. A clear gain is also demonstrated when assimilating jointly wide-swath SWOT and (aggregated) along-track nadir observations. Full article