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The Surface Water and Ocean Topography (SWOT) mission was launched on 16 December 2022 to measure water levels over both open ocean and inland waters. To achieve these objectives, the SWOT Payload contains an innovative Ka-band radar interferometer, called KaRIn, completed with a nadir altimeter called POSEIDON-3C that was switched on a month after launch and a few days before KaRIn. POSEIDON-3C measurements provide a link between large-scale phenomena and high resolution. The POSEIDON-3C design is based on POSEIDON-3B, its predecessor on board JASON-3. It is also a dual-frequency radar altimeter operating in C- and Ku-bands, but with some improvements to enhance its performance. Even though it is a Low Resolution Mode altimeter, its performance over open ocean, inland waters and coastal zones are indeed excellent. This paper first describes the POSEIDON-3C design and its modes with a focus on its new features and the Digital Elevation Model that drives its open-loop tracking mode. Then, we assess the in-flight performances of the altimeter from an instrumental point of view. For that purpose, special and routine calibrations have been realized. They show the good performance and stability of the radar. In-flight assessments thus provide confidence when it comes to ensuring excellent altimeter measurement stability throughout the mission duration. [ABSTRACT FROM AUTHOR]

Among the marine gravity field models derived from satellite altimetry, the Scripps Institution of Oceanography (SIO) series and Denmark Technical University (DTU) series models are the most representative and are often used to integrate global gravity field models, which were inverted by the deflection of vertical method and sea surface height method, respectively. The fusion method based on the offshore distance used in the EGM2008 model is just model stitching, which cannot realize the true fusion of the two types of marine gravity field models. In the paper, a new fusion method based on water depth segmentation is proposed, which established the Precision–Depth relationship of each model in each water depth segment in the investigated area, then constructed the FUSION model by weighted fusion based on the precision predicted from the Precision–Depth relationship at each grid in the whole region. The application in the South China Sea shows that the FUSION model built by the new fusion method has better accuracy than SIO28 and DTU17, especially in shallow water and offshore areas. Within 20 km offshore, the RMS of the FUSION model is 5.10 mGal, which is 8% and 4% better than original models, respectively. Within 100 m of shallow water, the accuracy of the FUSION model is 4.01 mGal, which is 14% and 12% higher than the original models, respectively. A further analysis shows that the fusion model is in better agreement with the seabed topography than original models. The new fusion method can blend the effective information of original models to provide a higher-precision marine gravity field. [ABSTRACT FROM AUTHOR]

Numerical tesseroid and radial-type approaches are presented and compared in terms of their efficiency for deriving the regional geoid height, vertical gravity, and gradiometric anomalies from sea floor topography grids. The vertical gradient function is particularly suitable for representing shorter wavelengths of gravity, typically less than 10 km. These two modeling methods were applied to the Great Meteor guyot in the Atlantic Ocean using its bathymetry. To optimize the computation of high-resolution gravity anomalies, the Armadillo, GSL, and OpenMP libraries were used to provide an environment for fast vector implementation, numerical integration for tesseroid calculation, and parallelization for loop iterations, resulting in a computation speed increase. The tesseroid and radial methods remain equivalent up to a resolution of about 1 min, with the radial method being faster when dealing with a large number of model points for the geoid. Aside from optimization enabling high-resolution gravity simulations, these fast modeling data can be used as the main operators in gravimetric inversion or to reduce the terrain effects in gravity observations, revealing gravity and sedimentary layers. [ABSTRACT FROM AUTHOR]

Increasing climatic and human pressures are changing the world's water resources and hydrological processes at unprecedented rates. Understanding these changes requires comprehensive monitoring of water resources. Hydrogeodesy, the science that measures the Earth's solid and aquatic surfaces, gravity field, and their changes over time, delivers a range of novel monitoring tools that are complementary to traditional hydrological methods. It encompasses geodetic technologies such as Altimetry, Interferometric Synthetic Aperture Radar (InSAR), Gravimetry, and Global Navigation Satellite Systems (GNSS). Beyond quantifying these changes, there is a need to understand how hydrogeodesy can contribute to more ambitious goals dealing with water‐related and sustainability sciences. Addressing this need, we combine a meta‐analysis of over 3,000 articles to chart the range, trends, and applications of satellite‐based hydrogeodesy with an expert elicitation that systematically assesses the potential of hydrogeodesy. We find a growing body of literature relating to the advancements in hydrogeodetic methods, their accuracy and precision, and their inclusion in hydrological modeling, with a considerably smaller portion related to understanding hydrological processes, water management, and sustainability sciences. The meta‐analysis also shows that while lakes, groundwater and glaciers are commonly monitored by these technologies, wetlands or permafrost could benefit from a wider range of applications. In turn, the expert elicitation envisages the potential of hydrogeodesy to help solve the 23 Unsolved Questions of the International Association of Hydrological Sciences and advance knowledge as guidance toward a safe operating space for humanity. It also highlights how this potential can be maximized by combining hydrogeodetic technologies simultaneously, exploiting artificial intelligence, and accurately integrating other Earth science disciplines. Finally, we call for a coordinated way forward to include hydrogeodesy in tertiary education and broaden its application to water‐related and sustainability sciences in order to exploit its full potential. Plain Language Summary: Increasing climatic and human pressures are changing the world's water resources and hydrological processes at unprecedented rates. Understanding these changes requires comprehensive monitoring of water resources. Hydrogeodesy, the science that measures the Earth's solid and aquatic surfaces, gravity field, and their changes over time, delivers a range of novel monitoring tools complementary to traditional hydrological methods. It encompasses technologies such as Altimetry, Interferometric Synthetic Aperture Radar (InSAR), Gravimetry, and Global Navigation Satellite Systems (GNSS). Beyond quantifying these changes, we need to understand the potential of hydrogeodesy to contribute to more ambitious goals of water‐related and sustainability sciences. Addressing this need, we combine a meta‐analysis of over 3,000 articles to chart the range, trends, and applications of hydrogeodesy with an expert elicitation that systematically assesses this potential. We find a growing body of literature relating to advancements in hydrogeodetic methods, their accuracy and precision, and their inclusion in hydrological modeling. The expert elicitation envisages the large potential to solve hydrological problems and sustainability challenges. It also highlights how this potential can be maximized by combining several hydrogeodetic technologies, exploiting artificial intelligence, and accurately integrating other Earth science disciplines. Key Points: This is a community view on hydrogeodesy, the science that measures the Earth's solid and aquatic surfaces, gravity field, and their changesHydrogeodesy encompasses geodetic technologies such as Altimetry, Interferometric Synthetic Aperture Radar, Mass gravimetry, and Global Navigation Satellite SystemsWe study the evolution of hydrogeodesy and its role within current hydrological, sustainability science, and management frameworks [ABSTRACT FROM AUTHOR]

Studying ocean tides with satellite altimetry has traditionally been difficult in coastal regions. The 1 day repeat of the Cal/Val phase of SWOT provides a unique dataset that can be exploited for tidal analysis. In this work, KaRIn data from the SWOT Cal/Val phase are analyzed in two coastal regions to present a first look at the possibilities for tidal analysis from SWOT. The areas are: (a) Bristol Channel and (b) Great South Bay. When benchmarked against in situ measurements in these regions, substantial improvements over tide models, which typically report errors exceeding tens of centimeters and degrees, are seen. Specifically, the SWOT ocean‐tide estimates exhibit amplitude discrepancies ranging from 1.75 to 3 cm and phase lag discrepancies between 1.75° and 2.75° when compared with in situ tide gauge data. These findings underscore the value of SWOT for tidal research in complex coastal regions. Plain Language Summary: Estimating ocean tides in the coastal region has challenged tide modelers for decades. The recently launched SWOT satellite provides the opportunity to derive estimations of ocean tides at unprecedented spatial scales thanks to the innovative wide‐swath measurement principle, particularly in complex coastal regions. The mission's Calibration and Validation (Cal/Val) phase is particularly interesting for tidal research, as the tide‐favorable orbit allows for the derivation of the major tidal constituents with a relatively short time series of SWOT data. This manuscript evaluates the largest tidal constituent, the principal lunar M2 ${\mathrm{M}}_{2}$ tide, derived from SWOT's Cal/Val phase within two complex coastal regions. Results within the Bristol Channel and the Great South Bay demonstrate unprecedented spatial variability in the amplitude and phase lag of the M2 ${\mathrm{M}}_{2}$ tide. Additionally, with respect to in situ measurements, SWOT‐derived estimates resulted in reduced errors compared with global tide models in these complex coastal regions. The initial insights demonstrated several strengths and opportunities for using SWOT to improve tide models and new avenues of research with satellite measurements of ocean tides, particularly within fjords and estuaries. Key Points: SWOT KaRIn data from the Cal/Val phase is used to derive M2 ${\mathrm{M}}_{2}$ tide in two complex coastal regionsResults demonstrate the spatial variability of amplitude and phase lag of coastal tidesSWOT KaRIn measurements are useful for studying tidal flats and ocean tides in river mouths and estuaries [ABSTRACT FROM AUTHOR]

Sea ice altimetry currently remains the primary method for estimating sea ice thickness from space, however time-series of sea ice thickness estimates are of limited use without having been quality-controlled against reference measurements. Such reference observations for sea ice thickness validation in the polar regions are sparse and rarely presented in a format matching the satellite-derived products. Here, the first published comprehensive collection of sea ice reference observations including freeboard, thickness, draft and snow depth from sea ice-covered regions in the Northern Hemisphere (NH) and the Southern Hemisphere (SH) is presented. The observations have been collected using airborne sensors, autonomous drifting buoys, moored and submarine-mounted upward-looking sonars, and visual observations. The data package has been prepared to match the spatial (25 km for NH and 50 km for SH) and temporal (monthly) resolutions of conventional satellite altimetry-derived sea ice thickness data products for a direct evaluation of these. This data package, also known as the Climate Change Initiative (CCI) sea ice thickness (SIT) Round Robin Data Package (RRDP) was produced within the ESA CCI sea ice project. The current version of the CCI SIT RRDP covers the polar satellite altimetry era (1993–2021) and is part of ongoing efforts to keep the dataset updated. The CCI SIT RRDP has been collocated to satellite-derived sea ice thickness products from CryoSat-2, Envisat and ERS-1/2 produced within ESA CCI and the Fundamental Data Records for Altimetry (FDR4ALT) project to demonstrate the overlap and inter-comparison between the reference observations and satellite-derived products. Here, the CCI SIT RRDP is introduced along with examples of its use as a validation source for satellite altimetry products, where the averaging, collocation and uncertainty methodology is presented and their advantages and limitations are discussed. [ABSTRACT FROM AUTHOR]

The sea ice extent in the Weddell Sea exhibited a positive trend from the start of satellite observations in 1978 until 2016 but has shown a decreasing trend since then. This study analyzes seasonal and interannual variations in sea ice thickness using ICESat-2 laser altimetry data over the Weddell Sea from 2019 to 2022. Sea ice thickness was calculated from ICESat-2's ATL10 freeboard product using the Improved Buoyancy Equation. Seasonal variability in ice thickness, characterized by an increase from February to September, is more pronounced in the eastern Weddell sector, while interannual variability is more evident in the western Weddell sector. The results were compared with field data obtained between 2019 and 2022, showing a general agreement in ice thickness distributions around predominantly level ice. A decreasing trend in sea ice thickness was observed when compared to measurements from 2003 to 2017. Notably, the spring of 2021 and summer of 2022 saw significant decreases in Sea Ice Extent (SIE). Although the overall mean sea ice thickness remained unchanged, the northwestern Weddell region experienced a noticeable decrease in ice thickness. [ABSTRACT FROM AUTHOR]

A satellite altimetry mission can measure high-precision sea surface height (SSH) to recover a marine gravity field. The reference gravity field model plays an important role in this recovery. In this paper, reference gravity field models with different degrees are used to analyze their effects on the accuracy of recovering gravity anomalies using the inverse Vening Meinesz (IVM) method. We evaluate the specific performance of different reference gravity field models using CryoSat-2 and HY-2A under different marine bathymetry conditions. For the assessments using 1-mGal-accuracy shipborne gravity anomalies and the DTU17 model based on the inverse Stokes principle, the results show that CryoSat-2 and HY-2A using XGM2019e_2159 obtains the highest inversion accuracy when marine bathymetry is less than 2000 m. Compared with the EGM2008 model, the accuracy of CryoSat-2 and HY-2A is improved by 0.6747 mGal and 0.6165 mGal, respectively. A weighted fusion method that incorporates multiple reference models is proposed to improve the accuracy of recovering gravity anomalies using altimetry satellites in shallow water. The experiments show that the weighted fusion method using different reference models can improve the accuracy of recovering gravity anomalies in shallow water. [ABSTRACT FROM AUTHOR]

The three‐dimensional structure of the Tropical Cyclone's baroclinic wake is synthesized as an averaged baroclinic‐dominant response of the upper ocean. The resulting persisting sea surface depression can easily be monitored using the present‐day altimeter constellation. Following a semi‐empirical framework, these baroclinic wake signatures are linked to the inner core TC dynamic and the ocean stratification. To collect these fine‐scale parameters, spaceborne SAR instruments and Argo fleet are used, to precisely capture the maximum wind region and the irregularities of the ocean vertical structure. This combination of high‐resolution information is found paramount to fully capture the modulation of sea surface height anomalies, and its mean trend, especially for major hurricanes. Baroclinic signatures mostly range around 10–20 cm and peak at 40 cm. Deeper anomalies correspond to barotropic response, removed from the present analysis. Plain Language Summary: In the wakes of Tropical Cyclones (TCs), sea surface depressions of about 10 cm appear. These TC signatures are persistent enough to be easily monitored by the current fleet of altimeter instruments. A measured sea surface height anomaly integrates and reduces the air/sea interactions during the TC passage into a single observable metric. It mostly encodes the cyclonic wind forcing and the interior ocean state. A broad constellation of remote sensing and in‐situ instruments has been gathered to compile 200 cyclonic episodes, collecting a wide range of TC sizes, intensities, and translation speeds together with oceanic conditions. A synthetic relationship is found to robustly predict most observed sea surface height anomalies. Moreover, when high‐resolution information is available to estimate the ocean interior state and the TC radius of maximum winds. Such a diagnostic thus explains the dominant baroclinic ocean response to a TC passage, and, inversely, can be used to infer ocean stratification or forcing parameters in the absence of high‐resolution observations. Key Points: Residual sea surface height anomalies from the cold wakes of Tropical Cyclones are analyzed using a multi‐modal approach at global scaleA scaling law provides a robust interpretation of the baroclinic response to given ocean stratification and forcing conditionsHigh resolution measurements are found critical to correctly anticipate the SSHA amplitudes with localized pre‐storm ocean stratification [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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'X 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-3/6MGAs, S3B exhibits the highest accuracy in the SCS, with a rootmean 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. [ABSTRACT FROM AUTHOR]

Conventional wisdom about mesoscale eddies is that cyclonic (anticyclonic) eddies are commonly associated with cold(warm) surface cores. Nevertheless, plenties of surface warm cyclonic eddies (WCEs) and cold anticyclonic eddies (CAEs) in the North Pacific Subtropical Countercurrent (STCC) region are observed by a synergistic investigation based on data from satellite altimetry, microwave radiometer, and Argo float profiles in this study. The results indicate that these two types of abnormal eddies (WCEs and CAEs) are prevalent in the STCC region, comprising approximately 30% of all eddies detected via satellite observations. We then analyze their spatial-temporal distribution characteristics and composite vertical structures. A statistical comparison with surface cold cyclonic eddies (CCEs) and warm anticyclonic eddies (WAEs) reveals notable differences between the anomalous and typical eddies. Additionally, we present the composite vertical structures of temperature and salinity anomalies for the anomalous eddies across five delineated subregions within an eddy-coordinate system. Furthermore, the close relationship between these abnormal eddies and subsurface-intensified mesoscale eddies are discussed. [ABSTRACT FROM AUTHOR]

Abstract Sea level rise (SLR) poses a significant threat to coastal regions worldwide, particularly affecting over 60 million people living below 10 m above sea level along the African coast. This study analyzes the spatio-temporal trends of sea level anomaly (SLA) and its components (thermosteric, halosteric and ocean mass) in the Eastern Tropical Atlantic Ocean (ETAO) from 1993 to 2022. The SLA trend for the ETAO, derived from satellite altimetry, is 3.52 ± 0.47 mm/year, similar to the global average of 3.56 ± 0.67 mm/year. Of the three upwelling regions, the Gulf of Guinea (GoG) shows the highest regional trend of 3.42 ± 0.12 mm/year. Using the ARMORD3D dataset, a positive thermosteric sea level trend of 0.88 ± 0.04 mm/year is observed, particularly in the equatorial and southern Atlantic regions. The steric component drives the interannual SLA variability, while the ocean mass component dominates the long-term trends, as confirmed by the GRACE and GRACE-FO missions for 2002–2022. For those two decades, the total SLR from altimetry amounts to 3.80 ± 0.8 mm/year, whilst the steric component is reduced to only 0.19 ± 0.05 mm/year, leaving a residual increase in the ETAO of 3.69 ± 0.5 mm/year. The independent mass change from GRACE amounts to 2.78 ± 0.6 mm/year for this region, which just closes the sea level budget within present uncertainty levels. Spatial analysis of the steric components indicates a warming along the equatorial African coast including the GoG and a freshening near Angola. Strong correlations with regional climate factors, particularly the Tropical South Atlantic Index, highlight the influence of persistent climate modes. These findings underscore the urgent need for mitigation and adaptation strategies to SLR in the ETAO, especially for densely populated coastal communities.

Arctic sea ice volume (SIV) is a key climate indicator and memory source in sea ice predictions and projections, yet suffering from large observational and model uncertainty. Here, we test whether passive microwave (PMW) data constrain the long-term evolution of Arctic SIV, as recently hypothesized. We find many commonalities in Arctic SIV changes from a PMW sea ice thickness (SIT) 1992-2020 time series reconstructed with a neural network algorithm trained on lidar altimetry, and the reference PIOMAS reanalysis: relatively low differences in SIV mean (4615 km3, 37%), SIV trends (46 km3, 17%), and phased variability (r2=0.55). Key to reduced differences is the consistent evolution of many SIV contributors: seasonal and perennial ice coverage, their SIT contrast, whereas perennial SIT provides the largest remaining uncertainty source. We argue that PMW includes useful SIT information, reducing SIV uncertainty. We foresee progress from sea ice reanalyses combining dynamical models and data assimilation of PMW SIT estimates, in addition to the already assimilated PWM sea ice concentration. [ABSTRACT FROM AUTHOR]

Sea level rise (SLR) poses a significant threat to coastal regions worldwide, particularly affecting over 60 million people living below 10 m above sea level along the African coast. This study analyzes the spatio-temporal trends of sea level anomaly (SLA) and its components (thermosteric, halosteric and ocean mass) in the Eastern Tropical Atlantic Ocean (ETAO) from 1993 to 2022. The SLA trend for the ETAO, derived from satellite altimetry, is 3.52 ± 0.47 mm/year, similar to the global average of 3.56 ± 0.67 mm/year. Of the three upwelling regions, the Gulf of Guinea (GoG) shows the highest regional trend of 3.42 ± 0.12 mm/year. Using the ARMORD3D dataset, a positive thermosteric sea level trend of 0.88 ± 0.04 mm/year is observed, particularly in the equatorial and southern Atlantic regions. The steric component drives the interannual SLA variability, while the ocean mass component dominates the long-term trends, as confirmed by the GRACE and GRACE-FO missions for 2002–2022. For those two decades, the total SLR from altimetry amounts to 3.80 ± 0.8 mm/year, whilst the steric component is reduced to only 0.19 ± 0.05 mm/year, leaving a residual increase in the ETAO of 3.69 ± 0.5 mm/year. The independent mass change from GRACE amounts to 2.78 ± 0.6 mm/year for this region, which just closes the sea level budget within present uncertainty levels. Spatial analysis of the steric components indicates a warming along the equatorial African coast including the GoG and a freshening near Angola. Strong correlations with regional climate factors, particularly the Tropical South Atlantic Index, highlight the influence of persistent climate modes. These findings underscore the urgent need for mitigation and adaptation strategies to SLR in the ETAO, especially for densely populated coastal communities. [ABSTRACT FROM AUTHOR]

The study investigates sea-level measurements along the coastal area of Europe for the 60-year (1961-2020) time span. Linear and quadratic modeling of tide gauge measurements showed an almost positive rate of trend of sea-level rise (0.09 to 3.6 mm/yr) and low acceleration (-0.05 to 0.40 mm/yr²). A least-squares harmonic estimation tidal modeling was carried out to estimate frequency (cycles per day) for a certain period. The smaller and higher tidal frequencies of these stations indicate their stability in terms of their surface variation. We used the 1993-2020 satellite altimetry data from the nearest grid points of the tide gauge station. The correlation coefficient between observed and satellite altimetry (lowest 0.53 and highest 0.93) varies at each station. This happens because of many factors that can affect the large difference in the sea-level trend between the satellite-derived and tide gauge results. Finally, to implement a global reference system for physical heights, the offshore topographic slope direction and slope range with contour spacing from the sea to the associated coastline were analyzed using bathymetry data. The abrupt change in slope from the coastline toward the sea can be seen toward the east, west, and southeast on the European coast. This is also an important factor that affects the variation of sea level. [ABSTRACT FROM AUTHOR]

Recently, climate extremes have been grabbing attention as important drivers of environmental change. Here, we assemble an observational inventory of energy and mass fluxes to quantify the ice loss from glaciers on the Russian High Arctic archipelago of Novaya Zemlya. Satellite altimetry reveals that 70 ± 19% of the 149 ± 29 Gt mass loss between 2011 and 2022 occurred in just four high-melt years. We find that 71 ± 3% of the melt, including the top melt cases, are driven by extreme energy imports from atmospheric rivers. The majority of ice loss occurs on leeward slopes due to foehn winds. 45 of the 54 high-melt days (>1 Gt d−1) in 1990 to 2022 show a combination of atmospheric rivers and foehn winds. Therefore, the frequency and intensity of atmospheric rivers demand accurate representation for reliable future glacier melt projections for the Russian High Arctic. Moist, warm air from mid-latitudes lead to a speed-up of glacial ice loss in Novaya Zemlya, High Russian Arctic. Foehn winds enable especially high melt rates. These conditions became more frequent over the past decade. [ABSTRACT FROM AUTHOR]

A method for reconstructing weekly Baltic gridded sea levels was developed and tested. This method uses input data from tide gauge and altimetry observations. The reconstruction is based on sea level empirical orthogonal function (EOF) modes, calculated as spatiotemporal statistics from daily model reanalysis results available from the Copernicus Marine Service for the 1993–2021 period. In the semi-enclosed, tideless Baltic Sea, the four leading EOF modes cover 99% of the sea level variance. Several experiments with different combinations of input data were carried out. This method was validated against coastal tide gauges and altimetry data. The best reconstruction was obtained when both the tide gauges and altimetry data were used as inputs. An assessment of the centered root-mean-square difference (cRMSD) of the reconstruction versus the tide gauges revealed a value of 0.05 m, and a result of 0.10 m was revealed versus altimetry. The average coefficient of determination (R2) was determined to be 0.93 for the tide gauges and 0.82 for the altimetry data. In the cases where only one type of input data was used, the reconstruction worsened with respect to other data sources. The reconstruction method demonstrated its usefulness for the reconstruction of coastal sea levels in unsampled locations and the calculation of changes in sea volume. [ABSTRACT FROM AUTHOR]

The Radar for Europa Assessment and Sounding: Ocean to Near-surface (REASON) is a dual-frequency ice-penetrating radar (9 and 60 MHz) onboard the Europa Clipper mission. REASON is designed to probe Europa from exosphere to subsurface ocean, contributing the third dimension to observations of this enigmatic world. The hypotheses REASON will test are that (1) the ice shell of Europa hosts liquid water, (2) the ice shell overlies an ocean and is subject to tidal flexing, and (3) the exosphere, near-surface, ice shell, and ocean participate in material exchange essential to the habitability of this moon. REASON will investigate processes governing this material exchange by characterizing the distribution of putative non-ice material (e.g., brines, salts) in the subsurface, searching for an ice–ocean interface, characterizing the ice shell's global structure, and constraining the amplitude of Europa's radial tidal deformations. REASON will accomplish these science objectives using a combination of radar measurement techniques including altimetry, reflectometry, sounding, interferometry, plasma characterization, and ranging. Building on a rich heritage from Earth, the moon, and Mars, REASON will be the first ice-penetrating radar to explore the outer solar system. Because these radars are untested for the icy worlds in the outer solar system, a novel approach to measurement quality assessment was developed to represent uncertainties in key properties of Europa that affect REASON performance and ensure robustness across a range of plausible parameters suggested for the icy moon. REASON will shed light on a never-before-seen dimension of Europa and – in concert with other instruments on Europa Clipper – help to investigate whether Europa is a habitable world. [ABSTRACT FROM AUTHOR]

The provision of accurate wet tropospheric corrections (WTC), accounting for the delay of the radar pulses caused mostly by the atmospheric water vapor in the altimeter‐range observations, is pivotal for the full exploitation of altimeter‐derived surface heights. The WTC is best retrieved by measurements from Microwave Radiometers (MWR) on board the same altimeter mission. However, these instruments fail to provide valid WTC over land and ice and under rainy conditions. The GNSS‐derived Path Delay Plus (GPD+) algorithm has been designed to provide WTC over these surfaces where the onboard MWR WTC is invalid. This study focuses on the estimation of enhanced GPD+ WTC for the Copernicus Sentinel‐3A and Sentinel‐3B satellites, for the latest Baseline Collection 005.02 (BC005.2), spanning the period since the beginning of the missions until March 2023. GPD+ corrections are being provided operationally since 2022 and have been adopted as the default WTC in the calculation of the sea level anomaly (SLA). Compared to previous versions, the BC005.2 GPD+ WTC features improved data combination procedures, possesses a larger percentage of points estimated from observations, a better intermission alignment and reduced systematic differences among ascending and descending passes. Overall, GPD+ WTC are consistent, calibrated corrections, valid over all points present in the Non Time Critical marine product, allowing to recover, on average, about 17% of the altimeter observations with valid SLA, which otherwise, most of them would be rejected. Impacts of these WTC are most significant over coastal and inland water regions, at high latitudes and during rain events. Plain Language Summary: Satellite radar altimetry is a powerful technique to measure the Earth's topography during day and night, in all weather conditions. It uses radar pulses to measure the distance between the satellite and the surface beneath the satellite, from which the height of the mean sea level, rivers and lakes, for example, can be obtained. The atmosphere affects the propagation by delaying the signal and increasing the measured trajectory. The effect of the atmospheric water vapor is particularly difficult to model, since it is highly variable. This study concerns with a method to estimate the so‐called wet tropospheric correction, which accounts for the water vapor effects in the altimeter measurements. Over open ocean, the correction is usually based on the measurements from a dedicated instrument collocated on the same satellite, which fails to provide valid information over non‐water surfaces. The method, called GNSS‐derived Path Delay Plus (GPD+), aims to fill the gaps left by the previous instrumental correction. The study describes the latest version of the GPD+ wet tropospheric corrections for the Copernicus Sentinel‐3 altimeter products. It is demonstrated that these corrections can extend the altimeter observations to important regions such as coastal regions, rivers and lakes and high latitudes. Key Points: New GPD+ wet tropospheric corrections have been produced for Sentinel‐3, for the latest Baseline Collection (BC) 005.02These corrections are consistent, calibrated, valid over all surface types, improving data coverage mainly over coastal and polar regionsGPD+ are improved wet tropospheric corrections with respect to the Sentinel‐3 onboard radiometer and to the European Centre for Medium Range Weather Forecasts (ECMWF) operational model [ABSTRACT FROM AUTHOR]

With the development of satellite altimetry technology and the application of new altimetry satellites, the accuracy and resolution of altimeter-derived gravity field models have improved over the last decades. Nowadays, they are close enough to shipborne gravimetry. In this paper, multi-source shipborne gravity data in the South China Sea were taken to evaluate the accuracies of two high-precision altimeter-derived marine gravity field models (SS V30.1, DTU17). In these shipborne gravity data, there are dozens of routes' ship gravimetry data, obtained from the National Geophysical Data Center (NGDC); data were tracked from a marine survey with a commercial marine gravimeter (type KSS31M), and data were tracked from a marine gravimetry campaign that was conducted with a newly developed platform gravimeter (type JMG) in the South China Sea in September 2020. After various data filtering, processing, and calibrations, the shipborne gravity data were validated with crossover points analysis. Then, the processed shipborne data were employed to evaluate the accuracy of the altimeter-derived marine gravity field models. During this procedure, the quality of JMG shipborne gravity data was compared with the results of KSS31M and NGDC data. Analysis and evaluation results show that the crossover points verification accuracies of KSS31M and JMG are 0.70 mGal and 1.61 mGal, which are much better than the accuracy of NGDC, which is larger than 8.0 mGal. In the area where the bathymetry changes slowly, the root mean square error values between altimetry gravity models and KSS31M data are respectively 3.28 mGal and 4.54 mGal, and those of the JMG data are respectively 2.94 mGal and 2.60 mGal. According to the above results, we can conclude that the JMG has the same 1–2 mGal accuracy level as KSS31M and can meet the measurement requirements of marine gravity. [ABSTRACT FROM AUTHOR]

The Sentinel-3A and Sentinel-3B satellites, launched in February 2016 and April 2018 respectively, build on the legacy of CryoSat-2 by providing high-resolution Ku-band radar altimetry data over the polar regions up to 81° North. The combination of synthetic aperture radar (SAR) mode altimetry (SRAL instrument) from Sentinel-3A and Sentinel-3B, and the Ocean and Land Colour Instrument (OLCI) imaging spectrometer, results in the creation of the first satellite platform that offers coincident optical imagery and SAR radar altimetry. We utilise this synergy between altimetry and imagery to demonstrate a novel application of deep learning to distinguish sea ice from leads in spring. We use SRAL classified leads as training input for pan-Arctic lead detection from OLCI imagery. This surface classification is an important step for estimating sea ice thickness and to predict future sea ice changes in the Arctic and Antarctic regions. We propose the use of Vision Transformers (ViT), an approach adapting the popular deep learning algorithm Transformer, for this task. Their effectiveness, in terms of both quantitative metric including accuracy and qualitative metric including model roll-out, on several entire OLCI images is demonstrated and we show improved skill compared to previous machine learning and empirical approaches. We show the potential for this method to provide lead fraction retrievals at improved accuracy and spatial resolution for sunlit periods before melt onset. [ABSTRACT FROM AUTHOR]

Gravity measurements have important applications in geophysics, resource exploration, geodesy, and inertial navigation. The range of classical gravimetry includes laser interferometer (LI)-based absolute gravimeters, spring relative gravimeters, superconducting gravimeters, airborne/marine gravimeters, micro-electromechanical-system (MEMS) gravimeters, as well as gravity satellites and satellite altimetry. Atomic gravimetry is a new absolute gravity measurement technology based on atom interferometers (AIs) and features zero drift, long-term stability, long-term continuous measurements, and high precision. Atomic gravimetry has been used to measure static, marine, and airborne gravity; gravity gradient; as well as acceleration to test the weak equivalence principle at the China Space Station. In this paper, classical gravimetry is introduced, and the research progress on static and airborne/marine atomic gravimeters, space AIs, and atomic gravity gradiometers is reviewed. In addition, classical and atomic gravimetry are compared. Future atomic gravimetry development trends are also discussed with the aim of jointly promoting the further development of gravity measurement technologies alongside classical gravimetry. [ABSTRACT FROM AUTHOR]

In the context of escalating climate change-induced impacts on water resources, robust monitoring tools are imperative. Satellite altimetry, benefiting from technical improvement such as the use of SAR and InSAR techniques and tracking modes considering topography, is emerging as a crucial means of estimating lake levels, data that are fundamental to understanding climate dynamics. This study delves into the use of satellite-altimetry-determined water levels to analyze changes in water storage and superficial area in Lake Ranco, in south-central Chile, from 1995 to 2023. The main objective is to provide valuable information for water-resource management and policy formulation. Leveraging AlTiS software (v2.2.9-0-gf5938ab), radar-altimetry data from the missions ERS-2, ENVISAT, SARAL, and Sentinel-3A were processed, generating a complete time series of water levels. The lake-level data were complemented by the bathymetric data for the lake to obtain the variation in the area and volume in the period 1995–2023. These results were analyzed with respect to hydrometeorological data from the study area, such as precipitation, temperature, relative humidity, and potential evapotranspiration. Additionally, the effects of ENSO (ENSO 3.4 index) and the Pacific Decadal Oscillation index (PDO) were considered. Results reveal a strong correlation between altimetry-derived lake levels and observed in situ data, with a mean square error of 0.04 m, a coefficient of determination of 0.99, an index of agreement of 0.99, and a Kling−Gupta efficiency of 0.90. The analysis of climatic variables showed that variations in lake level coincide with changes in precipitation within the study area and also showed the influence of variations in temperature and potential evapotranspiration. Additionally, the effects of the ENSO phenomenon can be seen within the study area for its cold phase (i.e., La Niña) in the 2010–2012 period and for its warm phase (i.e., El Niño) in the 2015–2016 period, with a decrease and increase in precipitation, respectively. These effects were enhanced when the cold and warm phases of the ENSO and PDO phenomena occured. The successful application of satellite altimetry demonstrated in this study underscores its critical role in advancing our understanding and management of water resources amidst changing climate scenarios. [ABSTRACT FROM AUTHOR]

Digital Elevation Models (DEMs) are a necessity for modelling many large-scale environmental processes. In this study, we investigate the potential of data from two spaceborne lidar altimetry missions, ICESat-2 and GEDI—with respect to their vertical accuracies and planimetric data collection patterns—as sources for rasterisation towards creating global DEMs. We validate the terrain measurements of both missions against airborne lidar datasets over three areas in the Netherlands, Switzerland, and New Zealand and differentiate them using land-cover classes. For our experiments, we use five years of ICESat-2 ATL03 data and four years of GEDI L2A data for a total of 252 million measurements. The datasets are filtered using parameter flags provided by the higher-level products ICESat-2 ATL08 and GEDI L3A. For all areas and land-cover classes combined, ICESat-2 achieves a bias of −0.11 m, an MAE of 0.43 m, and an RMSE of 0.93 m. From our experiments, we find that GEDI is less accurate, with a bias of 0.09 m, an MAE of 0.98 m, and an RMSE of 2.96 m. Measurements in open land-cover classes, such as "Cropland" and "Grassland", result in the best accuracy for both missions. We also find that the slope of the terrain has a major influence on vertical accuracy, more so for GEDI than ICESat-2 because of its larger horizontal geolocation error. In contrast, we find little effect of either beam power or background solar radiation, nor do we find noticeable seasonal effects on accuracy. Furthermore, we investigate the spatial coverage of ICESat-2 and GEDI by deriving a DEM at different horizontal resolutions and latitudes. GEDI has higher spatial coverage than ICESat-2 at lower latitudes due to its beam pattern and lower inclination angle, and a derived DEM can achieve a resolution of 500 m. ICESat-2 only reaches a DEM resolution of 700 m at the equator, but it increases to almost 200 m at higher latitudes. When combined, a 500 m resolution lidar-based DEM can be achieved globally. Our results indicate that both ICESat-2 and GEDI enable accurate terrain measurements anywhere in the world. Especially in data-poor areas—such as the tropics—this has potential for new applications and insights. [ABSTRACT FROM AUTHOR]

We have analyzed the relationship between wind variability and sea level anomalies (SLA) on the Southwestern Atlantic Continental Shelf, focusing on sub-annual temporal scales. For this, we tested the capability of gridded altimetry to represent wind-driven SLA and compared results using an oceanographic model and tide gauge data. The present study used coherence analysis to analyze frequencies for which SLA and wind stress are coherent. The altimetry-SLA were found to have less energy below the three-month period compared to the model SLA. The coherence of along-shore wind stress and altimetry SLA was only significant for > 50 days (d), while the model SLA showed significant agreement in all periods considered, 20 d to annual. We further showed that geostrophic velocities on the continental shelf agreed significantly with SLA for > 50 d. As a result of an Empirical Orthogonal Function (EOF) analysis, we found that the second mode is highly coherent with the along-shore wind stress and accounts for 18.1% and 10.7% of variability in the model and altimetry sea level anomalies, respectively. [ABSTRACT FROM AUTHOR]

This investigation estimates a regional Mean Sea Surface (MSS) model, named SY21MSS, over the eastern Mediterranean Sea using satellite altimetry data from nine Exact Repeat Missions (ERM) and two Geodetic Missions (GM). Two interpolation methods, Least Squares Collocation (LSC) and Ordinary Kriging (OK), were employed, and statistical metrics were applied to assess their performance within a 15 km buffer from the coast. The comparison between LSC and OK techniques in the context of regional MSS modeling primarily centers on the covariance functions used by these methods. Furthermore, generalized cross-validation results indicate that OK outperforms LSC in this region. Consequently, the study recommends adopting the Kriging-based model for calculating regional MSS models in this region due to its superior performance. The investigation further explored the disparities between estimated regional MSS models and the global model DTU18MSS, highlighting a pronounced similarity between OK-SY21MSS and DTU18MSS, as evidenced by a lesser standard deviation (SD) difference compared to LSC-SY21MSS. The practical implications of this research underscore the importance of selecting an appropriate interpolation technique based on data characteristics and study area specifics. While both LSC and OK techniques are deemed viable for MSS modeling, the study emphasizes the superior performance of OK, particularly concerning covariance functions. Additionally, the results emphasize caution when applying global models in regions with significant local variations. [ABSTRACT FROM AUTHOR]

Satellite altimetry combined with data assimilation and optimal interpolation schemes have deeply renewed our ability to monitor sea surface dynamics. Recently, deep learning schemes have emerged as appealing solutions to address space‐time interpolation problems. However, the training of state‐of‐the‐art neural schemes on real‐world case‐studies is hindered by the sparse space‐time coverage of the sea surface of real altimetry data set. Here, we introduce an innovative approach that leverages state‐of‐the‐art ocean models to train simulation‐based neural schemes for the mapping of sea surface height and demonstrate their performance on real altimetry data sets. We analyze further how the ocean simulation data set used during the training phase impacts this performance. This experimental analysis covers both the resolution from eddy‐present configurations to eddy‐rich ones, forced simulations versus reanalyzes using data assimilation and tide‐free versus tide‐resolving simulations. Our benchmarking framework focuses on a Gulf Stream region for a realistic 5‐altimeter constellation using NEMO ocean simulations and 4DVarNet mapping schemes. All simulation‐based 4DVarNets outperform the operational observation‐driven and reanalysis products, namely DUACS and GLORYS. The more realistic the ocean simulation data set used during the training phase, the better the mapping. The best 4DVarNet mapping was trained from an eddy‐rich and tide‐free simulation data sets. It improves the resolved longitudinal scale from 151 km for DUACS and 241 km for GLORYS to 98 km and reduces the root mean square error by 23% and 61%. These results open research avenues for new synergies between ocean modeling and ocean observation using learning‐based approaches. Plain Language Summary: To train an artificial intelligence (AI) model, one need to describe a task using data and an evaluation procedure. Here we aim at constructing images related to the ocean surface currents. The satellite data we use provide images of the ocean surface with a lot of missing data (around 95% of missing pixels for a given day), and we aim at finding the values of the missing pixels. Because we don't know the full image, it is challenging to train an AI on this task using only the satellite data. However, today's physical knowledge makes it possible to numerically simulate oceans on big computers. For these simulated oceans, we have access to the gap‐free image, so we can train AI models by first hiding some pixels and checking if the model fill the gaps with the correct values. Here, we explore under which conditions AIs trained on simulated oceans are useful for the real ocean. We show that today's simulated oceans work well for training an AI on this task and that training on more realistic simulated oceans improve the performance of the AI! Key Points: We suggest utilizing ocean simulation data sets to train neural schemes for mapping real altimeter dataThe trained neural scheme improves the spatial scales resolved over the operational mapping product on a GulfStream case study by 30%Using more realistic simulation data sets improves the resulting neural mapping scheme by up to 20% in the spatial scales resolved [ABSTRACT FROM AUTHOR]

Nearshore bathymetry changes on scales of hours to months in ways that strongly impact coastal processes. However, even at the best-monitored sites, surveys are typically not conducted with sufficient frequency to capture important changes such as sandbar migration. As a result, nearshore models often rely on outdated bathymetric boundary conditions, which may introduce significant errors. In this study, we investigate ensemble optimal interpolation (EnOI) as a method to update survey-derived bathymetry with altimetric measurements that are spatially sparse but have high temporal availability. We present the results of two synthetic examples and two field data experiments that demonstrate the ability of the method to accurately track morphological change between surveys. The method reduces the RMSE relative to a static bathymetry (corresponding to the day before the first assimilation step) by 23% to 68%. When compared with an estimate linearly interpolated between survey-derived bathymetries, the EnOI analysis reduces the RMSE by 19% to 47% in three out of the four experiments. [ABSTRACT FROM AUTHOR]

Abstract Studying ocean tides with satellite altimetry has traditionally been difficult in coastal regions. The 1 day repeat of the Cal/Val phase of SWOT provides a unique dataset that can be exploited for tidal analysis. In this work, KaRIn data from the SWOT Cal/Val phase are analyzed in two coastal regions to present a first look at the possibilities for tidal analysis from SWOT. The areas are: (a) Bristol Channel and (b) Great South Bay. When benchmarked against in situ measurements in these regions, substantial improvements over tide models, which typically report errors exceeding tens of centimeters and degrees, are seen. Specifically, the SWOT ocean‐tide estimates exhibit amplitude discrepancies ranging from 1.75 to 3 cm and phase lag discrepancies between 1.75° and 2.75° when compared with in situ tide gauge data. These findings underscore the value of SWOT for tidal research in complex coastal regions.

Abstract The three‐dimensional structure of the Tropical Cyclone's baroclinic wake is synthesized as an averaged baroclinic‐dominant response of the upper ocean. The resulting persisting sea surface depression can easily be monitored using the present‐day altimeter constellation. Following a semi‐empirical framework, these baroclinic wake signatures are linked to the inner core TC dynamic and the ocean stratification. To collect these fine‐scale parameters, spaceborne SAR instruments and Argo fleet are used, to precisely capture the maximum wind region and the irregularities of the ocean vertical structure. This combination of high‐resolution information is found paramount to fully capture the modulation of sea surface height anomalies, and its mean trend, especially for major hurricanes. Baroclinic signatures mostly range around 10–20 cm and peak at 40 cm. Deeper anomalies correspond to barotropic response, removed from the present analysis.

The importance of satellite altimetry for monitoring inland water bodies is increasing, with the increasing need for fresh water. With the addition of the Sentinel-6 Michael Freilich (MF) in 2020 to the satellite altimetry record, we have parallel high- and low-resolution inland water observations. In this study, we validate Sentinel-6MF low- and high-resolution lake water levels, as determined with a state-space model, with data from 124 gauges in 85 lakes (of size > 20 km2) from the United States, Canada, Sweden, and Australia. Furthermore, we estimate the scatter of the observations at 1330 globally distributed lakes. We address the difference in performance when using a physical (ocean) and empirical (OCOG) retracker. Using the 124 gauges as ground truth, we determine a best-case unbiased root mean squared error (u-RMSE) of 6.4 cm for Sentinel-6MF, when using the high-resolution mode and the OCOG retracker. The u-RMSE is between 6.4 and 12.3 cm when correcting for ice-covered lakes, and 15.6 to 31.3 cm for all data, depending on retracker and resolution mode. The corresponding median standard deviation of water surface elevations per transect from the 1330 lakes is 3.5 cm and 8.1 cm for high and low-resolution OCOG-based water levels, respectively. The corresponding median standard deviation of Sentinel-3A/B OCOG (enhanced measurement, 20 Hz mode, baseline-3/4) is 5.9 cm and 6.0 cm. We find a lower u-RMSE and standard deviation for high-resolution data, and the ability to observe more lakes, compared to the low-resolution mode. From this, we see that Sentinel-6MF yields valid estimates of the water surface elevation, including smaller lakes, and would provide additional value to future water level monitoring via remote sensing. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Argo floats are widely used to characterize vertical structures of ocean eddies, yet their capability to invert sea surface features of eddies, especially those overlooked by available altimeters, has not been explored. In this paper, we propose an "interior-to-surface" inversion algorithm to effectively expand the capacity of eddy detection by estimating altimeter-missed eddies' surface attributes from their Argo-derived potential density anomaly profiles, given that the interior property and surface signature of eddies are highly correlated. An altimeter-calibrated machine learning ensemble is employed for the inversion training based on the joint altimeter–Argo eddy data and shows promising performance with mean absolute errors of 5.4 km, 0.5 cm, and 14.3 cm2 s−2 for eddy radius, amplitude, and kinetic energy, respectively. Then, the trained ensemble model is applied to independently invert the properties of eddies captured by an Argo-alone detection scheme, which yields high spatiotemporal consistency with their altimeter-captured counterparts. In particular, a portion of Argo-alone eddies is ∼25% smaller than altimeter-derived ones, indicating Argo's unique capability of profiling weaker submesoscale eddies. Sea surface temperature and chlorophyll data are further applied to validate the reliability of eddies identified and characterized by the Argo-only algorithm. This new methodology effectively complements that of altimetry in eddy detection and can be expanded to estimate other physical/biochemical eddy variables from a variety of in situ observations. Significance Statement: Despite thousands of eddies being routinely identified on a daily basis, it has been recognized that a substantial portion of eddies may still be missed due to inadequate sampling of altimeter constellations. Taking advantage of eddy's correlation between surface and interior, a considerable number of eddies are discovered for the first time through an Argo-based eddy identification scheme. Here, we propose a new methodology to independently infer these recaptured eddies' surface properties from their vertical signals through an "interior-to-surface" inversion process. The inferred eddy properties are verified by the spatiotemporal consistency with those derived from altimetry. Since Argo is capable of profiling smaller and weaker eddies, the proposed methodology significantly complements and expands that of altimetry in eddy observation. [ABSTRACT FROM AUTHOR]

We 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. Plain Language Summary: The surface water and ocean topography (SWOT) is a satellite mission designed to measure Earth's water body heights in wide‐swath, offering opportunities to measure the ocean surface in unprecedented details. This capability brings valuable high‐resolution information about the gravity field and seafloor underneath the ocean. This study aims to evaluate SWOT's performance and our test area is in the South Pacific Ocean where we already know the ocean topography and gravity field well. Results show that with SWOT global measurements lasting over 1 year, it promises a significant improvement in uncharted details of the seafloor. Key Points: A single cycle of surface water and ocean topography (SWOT) at a typical significant wave height of 4 m, has an accuracy of 2.6 μrad and a spatial resolution of 14 kmA stack of ∼60 cycles of SWOT data provides a significant improvement in accuracy to ∼1.2 μrad and spatial resolution ∼8 kmThe accuracy and resolution of the marine gravity field derived from SWOT will exceed current models after 8 months [ABSTRACT FROM AUTHOR]

The Ice, Cloud, and Land Elevation Satellite‐2 (ICESat‐2) mission has collected surface elevation measurements for over 5 years. ICESat‐2 carries an instrument that emits laser light at 532 nm, and ice and snow absorb weakly at this wavelength. Previous modeling studies found that melting snow could induce significant bias to altimetry signals, but there is no formal assessment on ICESat‐2 acquisitions during the melting season. We performed two case studies over the Greenland Ice Sheet to quantify bias in ICESat‐2 signals over snow: one to validate Airborne Topographic Mapper (ATM) data against Next Generation Airborne Visible/Infrared Imaging Spectrometer (AVIRIS‐NG) grain sizes, and a second to estimate ICESat‐2 bias relative to ATM. We used snow optical grain sizes derived from ATM and AVIRIS‐NG to attribute altimetry bias to snowpack properties. For the first case study, the mean and standard deviation of optical grain sizes were 340 ± 65 µm (AVIRIS‐NG) and 670 ± 420 µm (ATM). A mean altimetry bias of 4.81 ± 1.76 cm was found for ATM, with larger biases linked to increases in grain size. In the second case study, we found a mean grain size of 910 ± 381 µm and biases of 6.42 ± 1.77 cm (ICESat‐2) and 9.82 ± 0.97 cm (ATM). The grain sizes and densities needed to recreate biases with a model are uncommon in nature, so we propose that additional surface attributes must be considered to characterize ICESat‐2 bias over snow. The altimetry biases are within the accuracy requirements of the ICESat‐2 mission, but we cannot rule out more significant errors over coarse‐grained snow. Plain Language Summary: The Ice, Cloud, and Land Elevation Satellite‐2 (ICESat‐2) mission has been used to measure changes in land ice, vegetation cover, and sea ice, and there is growing interest to use ICESat‐2 for snow science. ICESat‐2 uses a green laser to estimate the elevation of the Earth's surface, and recent work has shown that snow can introduce errors in green laser measurements such as ICESat‐2. In this study, we used ICESat‐2 and airborne data to (a) identify errors in the ICESat‐2 data and (b) link the errors to snow properties over the Greenland Ice Sheet. We found that ICESat‐2 errors are linked to two snow properties: the size of individual snow grains and the density of the snow. Two retrieval methods were used to estimate snow grain size, though the methods show significant differences when large snow grains are observed. Snow grain size and density are insufficient to fully explain ICESat‐2 biases, so we propose that other factors also play a role. The ICESat‐2 errors are within the accuracy requirements of ICESat‐2, but more significant errors may be possible during the Northern Hemisphere melting season. Key Points: Very large snow grains and densities are needed to explain centimeter‐level differences between ICESat‐2 and airborne lidarBiases from snow grain size and other factors may be influenced by different height measurement methods between ICESat‐2 and airborne lidarSnow grain size retrievals strongly differ between airborne lidar and AVIRIS‐NG over regions with coarse‐grained snow [ABSTRACT FROM AUTHOR]

Geodesy can provide valuable information on marine current estimation based on the combination of gravity and altimetry. Gravity is standardly used to estimate the geoid undulation, i.e. the height of the geoid over a given reference ellipsoid. As it is well known, the geoid undulation over the oceans is closely related to the Mean Sea Surface (MSS) with discrepancies that can reach 1–2 m at global scale. By satellite altimetry, one can get the MSS and then estimate the Mean Dynamic Topography (MDT) as the difference between the MSS and the geoid undulation. As the MDT is related to the ocean circulation, information on the ocean circulation to be compared with oceanographic estimates can be provided using these geodetic measurements. In this context, the GeoMed2 project aims at estimating a high-accuracy and high-resolution geoid model for the Mediterranean Sea based on land and marine gravity data and on recent Global Geopotential Models. In this paper, the processing methodology based on the well-known remove–compute–restore approach for the determination of the geoid in the Mediterranean area is presented. In a pre-processing step, all available gravity observations for the wider Mediterranean basin have been collected, validated, homogenized, and unified in terms of their horizontal and gravity system. In this way, a reliable gravity database to be used for the determination of the geoid has been prepared. This data set has been used in computing a gravimetric geoid estimate based on which the MDT over the Mediterranean Sea was obtained. The results of this computation were then revised, commented and compared with other existing MDT solutions. By these comparisons, it can be concluded that the geodetic computed MDT is not yet satisfactory since it is too noisy. This is possibly due to some inconsistencies still present in the gravity data used for estimating the geoid undulation and to the adopted MSS which seems to be too smooth over the Mediterranean area. [ABSTRACT FROM AUTHOR]

Conventionally, information from the tide gauge stations was used to establish the localized tidal datum. However, limitations in coverage, due to the sparse station distribution along the coast, have caused insufficient tidal datum information in some areas. Therefore, this study aims to develop the Peninsular Malaysia Quasi-Continuous Tidal Datum (PMQCTD) by integrating tide gauges, satellite altimetry, and Tide Model Driver (TMD) data. The research methodology includes data acquisition from 12 Departments of Survey and Mapping Malaysia (DSMMs) tide gauge stations along the coast of Peninsular Malaysia, satellite altimetry data of TOPEX, Jason-1, Jason-2, and GEOSAT Follow-On (GFO) from Radar Altimeter Database System (RADS), and the global hydrodynamic model from TMD. The tide gauge, satellite altimetry, and TMD data encompass 23 years of tidal observation data from 1993 to 2015. For the derivation of the tidal datum, tide gauge, and satellite altimetry data were analyzed following a harmonic analysis approach in the Unified Tidal Analysis and Prediction (UTide) software. Meanwhile, for the TMD data, the tidal datum was determined based on the tidal prediction from the 11 extracted major tidal constituents. For compatibility in data integration, the derived Lowest and Highest Astronomical Tide (LAT and HAT) from tide gauge, satellite altimetry, and TMD data were referenced to the Mean Sea Level (MSL), denoted as LATMSL and HATMSL, respectively. Next, the LATMSL and HATMSL were interpolated employing Inverse Distance Weighting (IDW) to develop the PMQCTD (LATMSL and HATMSL) with the ArcGIS software. The statistical assessment indicated that the established PMQCTD (LATMSL and HATMSL) has a better agreement with the DSMM tide gauges with a Root Mean Square Error (RMSE) of ± 0.228 m for LATMSL and ± 0.159 m for HATMSL In conclusion, the establishment of PMQCTD (LATMSL and HATMSL) has led to the availability of the tidal datum at any location along the coast of Peninsular Malaysia. [ABSTRACT FROM AUTHOR]

Satellite altimeters are the most common source of wave measurement in phenomenal sea states, with significant wave heights exceeding 14 m. Unfortunately their data is still considered with skepticism, because there is usually no other data to verify the accuracy of the largest values. Here we investigate the self‐consistency of the measurement, and their small scale variability, in order to define an estimate of satellite altimeter precision. Using numerical simulations of ocean surfaces and the processing involved in satellite retracking, we find that wave groups are responsible for a variance in estimated altimeter wave heights that is proportional to the square of the spectral peakedness parameter and the significant wave height. Additional variance induced by speckle noise is proportional to the wave height. The effect of wave groups generally dominates in the most severe storms. This variability requires a relatively large scale smoothing or filtering to yield accurate wave height estimates. For example, the largest ever reported 1 s average significant wave height from altimeters sampled by Jason‐2 in the North Atlantic in 2011, at H‾s=20.1 ${\overline{H}}_{s}=20.1$m, is now interpreted to correspond to a true wave height Hs = 18.5 ± 0.3 m. The difference between 20.1 and 18.5 m is mostly due to wave group contributions to the raw measurement. We argue that wave group effects should not be included in the definition of the significant wave height, just like the maximum wave height differs from the significant wave height. Plain Language Summary: Over most of the past 30 years, satellite altimeters have been the only means to measure wave properties in the most severe ocean storms. How do we know that these data are trustworthy, and how can we define uncertainties? Here we show that as a satellite flies along its orbit, it reports wave height that fluctuate because of the random nature of the wavefield that can be organized in groups at the scale of a few kilometers. We are able to simulate the precision of the measurements, as a function of the wave height and the degree of organization of the wavefield, measured by a "spectral peakedness" parameter. This novel understanding can be used to define the precision of the measurements. For example, as far as we know, the largest reported value for a 1 s averaged satellite measurement of the significant wave height was H‾s=20.1 ${\overline{H}}_{s}=20.1$m in a 2011 North Atlantic Storm, with no precision given. We can now re‐interpret this data as evidence of a true significant wave height Hs = 18.5 ± 0.3 m. The local fluctuations up to 20 m are caused by wave groups and should not be counted in the significant wave height. Key Points: Retracking of altimeter waveforms yields fluctuations in wave height and sea level, correlated at the scale of the effective footprintA good approximation for the effective footprint diameter is the square root of the product of wave height and satellite altitudeEstimating phenomenal wave heights precise to better than 2% requires filtering over wave groups, typically over a distance of 20–50 km [ABSTRACT FROM AUTHOR]

Recent droughts have severely threatened water security in many regions worldwide. Reservoirs, designed to combat droughts and secure water supply partially, are reported failing to fill up to the total capacity due to severe droughts. How bad is climate affecting reservoir filling up on a global scale? This issue has not been studied. We present a big picture of reservoirs in crisis using satellite altimetry. Thanks to the unique characteristics of CryoSat‐2, 525 reservoirs worldwide were investigated during 2010–2022. Results show that most reservoirs (93%) are found not fully filled up at least once. About 21% of reservoirs, which are mainly located in the Southern Hemisphere, show a significant decline in water levels. Moreover, about 20% of reservoirs with larger level fluctuations (>3 m) are located in less developed economies, indicating informed operation rules are needed. Further analyses indicate reservoirs are largely affected by extreme climate events, such as ENSO. Plain Language Summary: A reservoir is an artificial lake where water is collected and stored for various purposes, such as flood control, irrigation, hydropower generation, industrial use, etc. In a changing climate, drought events can cause a decline in the natural flow of streams and rivers to the reservoirs. Consequently, many of the functions provided by the reservoir might be halted if the drought continues, just like the cases of Lake Powell and Lake Mead. The past decade saw several record‐breaking global annual temperatures. How have global reservoirs been affected in terms of the filling up? Leveraging more than a decade of CryoSat‐2 altimetry observations, we provided a global picture of this issue. We found that 93% of studied reservoirs have not been fully filled up at least once during 2010–2022. Our analyses revealed that droughts are the most probable culprits. About 86% of the 398 reservoirs with accessible SPEI data exhibited significant susceptibility to drought, while 43% of the 525 reservoirs demonstrated notable sensitivity to ENSO events. These findings have important implications for future reservoir operations to cope with more intensive drought events. It also means the benefits and costs of both existing and planned reservoirs need to be re‐assessed to take adaptation strategies. Key Points: Water levels of reservoirs in the southern hemisphere show a declining trendAbout 93% of the 525 studied reservoirs have not been fully filled up at least once in the past 12 yearsLess developed economies need to develop informed reservoir operation rules to cope with climate change [ABSTRACT FROM AUTHOR]

For the past 20 years, Global Navigation Satellite System reflectometry (GNSS-R) technology has successfully shown its potential for remote sensing of the Earth's surface, including ocean and land surfaces. It is a multistatic radar that uses the GNSS signals reflected from the Earth's surface to extract land and ocean characteristics. Because of its numerous advantages such as low cost, multiple signal sources, and all-day/weather and high-spatiotemporal-resolution observations, this new technology has attracted the attention of many researchers. One of its most promising applications is GNSS-R ocean altimetry, which can complement existing techniques such as tide gauging and radar satellite altimetry. Since this technology for ocean altimetry was first proposed in 1993, increasing progress has been made including diverse methods for processing reflected signals (such as GNSS interferometric reflectometry, conventional GNSS-R, and interferometric GNSS-R), different instruments (such as an RHCP antenna with one geodetic receiver, a linearly polarized antenna, and a system of simultaneously used RHCP and LHCP antennas with a dedicated receiver), and different platform applications (such as ground-based, air-borne, or space-borne). The development of multi-mode and multi-frequency GNSS, especially for constructing the Chinese BeiDou Global Navigation Satellite System (BDS-3), has enabled more free signals to be used to further promote GNSS-R applications. The GNSS has evolved from its initial use of GPS L1 and L2 signals to include other GNSS bands and multi-GNSS signals. Using more advanced, multi-frequency, and multi-mode signals will bring new opportunities to develop GNSS-R technology. In this paper, studies of GNSS-R altimetry are reviewed from four perspectives: (1) classifications according to different data processing methods, (2) different platforms, (3) development of different receivers, and (4) our work. We overview the current status of GNSS-R altimetry and describe its fundamental principles, experiments, recent applications to ocean altimetry, and future directions. [ABSTRACT FROM AUTHOR]

The application of ICESAT-2 altimetry data in river hydrology critically depends on the accuracy of the mean water surface elevation (WSE) at a virtual station (VS) where satellite observations intersect solely with water. It is acknowledged that the ATL13 product has noise elevations of the adjacent land, resulting in biased high mean WSEs at VSs. Earlier studies have relied on human intervention or water masks to resolve this. Both approaches are unsatisfactory solutions for large river basins where the issue becomes pronounced due to many tributaries and meanders. There is no automated procedure to partition the truly representative water height from the totality of the along-track ICESAT-2 photon segments (portions of photon points along a beam) for increasing precision of the mean WSE at VSs. We have developed an automated approach called "auto-segmentation". The accuracy of our method was assessed by comparing the ATL13-derived WSEs with direct water level observations at 10 different gauging stations on 37 different dates along the Lower Murray River, Australia. The concordance between the two datasets is significantly high and without detectable bias. In addition, we evaluated the effects of four methods for calculating the mean WSEs at VSs after auto-segmentation processing. Our results reveal that all methods perform almost equally well, with the same R2 value (0.998) and only subtle variations in RMSE (0.181–0.189 m) and MAE (0.130–0.142 m). We also found that the R2, RMSE and MAE are better under the high flow condition (0.999, 0.124 and 0.111 m) than those under the normal-low flow condition (0.997, 0.208 and 0.160 m). Overall, our auto-segmentation method is an effective and efficient approach for deriving accurate mean WSEs at river VSs. It will contribute to the improvement of ICESAT-2 ATL13 altimetry data utility on rivers. [ABSTRACT FROM AUTHOR]

This article proposes an integer ambiguity determination method based on Beidou system-reflectometry (Beidou-R) observations of the carrier phase at the B1I and B3I frequencies. To enhance the accuracy of sea surface height (SSH) estimation, this study introduces a parallel filtering algorithm and an adaptive iterative fusion algorithm, enabling data fusion based on the variance at B1I and B3I frequencies. To validate and evaluate the proposed method, a coastal experiment was conducted at the Shenxian River. In this experiment, reflected signals from GEO and IGSO satellites were collected. Data analysis reveals that the method is effective, demonstrating that the root mean square error (RMSE) of SSH achieves 2.85 cm and 2.89 cm for PRN 04 and PRN 33, respectively. Furthermore, the impact of the elevation angle on measurement accuracy is analyzed. This study aims to propose a method to enhance coastal sea surface height estimation, offering potential advancements in sea surface altimetry. [ABSTRACT FROM AUTHOR]

Multi-satellite altimetry has been employed in tidal modelling as its accuracy has been proven acceptable in constructing good-quality models. However, the modelling process often fails to consider the varying temporal resolution and observation periods among satellites, which can affect the accuracy of the model due to aliasing and Rayleigh effects. In Indonesia, we investigate and propose a satellite selection procedure for tidal modelling utilizing the response method, validated with along-track data obtained from both older and newer generations of ERM (Exact Repeat Mission)-type altimetry satellites, including the TOPEX/Jason series (TOPEX, Jason-1, Jason-2, Jason-3, and SENTINEL-6A), ENVISAT, ERS-2, GFO, SENTINEL-3B, and SENTINEL3A. The most optimal satellite combination identified is the TOPEX/Jason series, GFO, and ENVISAT, as they contribute significantly less error compared to ERS-2, SENTINEL-3A, and SENTINEL-3B, with errors exceeding 50%, primarily due to aliasing and Rayleigh effects. This combination of three satellites with tide gauge stations achieves higher precision (11.31 cm) than the current global tidal model. This study provides empirical evidence that the accuracy of tidal models is not solely dependent on the number of altimetry satellites utilized, but implementing effective satellite selection procedures is also crucial to enhance the precision of a model. [ABSTRACT FROM AUTHOR]

In this research, we utilize AVISO altimetry data, the GLORYS12V1 product, and the META3.2 DT Atlas to investigate the Benguela upwelling. By combining these three datasets, we explore the propagation of mesoscale eddies generated within the upwelling zone and examine the dispersion of particles originating from the upwelling zone. The geographical scope of our analysis is confined to the region between 10–36°S and 0–20°E. We employ Lagrangian analysis and the AMEDA approach to study the eddies formed in the upwelling zone. The diverse methods applied enable us to track the movement of upwelling fluid elements in the specified area. The identification of the upwelling zone relies on temperature and salinity gradients in the coastal region. The primary focus of this study revolves around mesoscale eddies emerging in the upwelling zone. We scrutinize the trajectories of cyclones and anticyclones as they propagate westward from the upwelling zone, highlighting variations in the number of upwelling-origin particles within these eddies. We observe distinctions in the locations of upwelling cells between cyclones and anticyclones. Our results indicate that among mesoscale eddies generated in the upwelling zone cyclones predominate. We show that Lagrangian particles, leaving the upwelling zone, propagate throughout the area under consideration. For these particles, we can determine the travel time from the upwelling zone from 1 to 365 days and distances of 500 km for cyclones and 300 km for anticyclones. We found that cyclones are more stable structures with a longer lifetime and with a longer distance traveled in contrast to anticyclones. We believe this is a distinctive feature of the eddies with upwelling origins in comparison with other mesoscale eddies in the area. Finally, we analyze the change of water properties inside the eddies after they leave the upwelling zone and show a significant renewal of vortex cores occurring after 1–2 months of their life. [ABSTRACT FROM AUTHOR]

For nearly three decades, satellite radar altimetry has provided measurements of the water surface elevation (WSE) of rivers. These observations can be used to calculate the water surface slope (WSS), which is an essential parameter for estimating flow velocity and river discharge. In this study, we calculate a non time‐varying high‐resolution WSS of 11 Polish rivers based on multi‐mission altimetry observations from 11 satellites in the period from 1994 to 2023. The proposed approach is based on a weighted least squares adjustment with an additional Laplace condition and an a priori gradient condition. The processing is divided into river sections not interrupted by dams and reservoirs. After proper determination of the WSE for each river kilometer (bin), the WSS between adjacent bins is calculated. To assess the accuracy of the estimated WSS, it is compared with slopes between gauge stations, which are referenced to a common vertical datum. Such gauge stations are available for 8 studied rivers. The root mean squared error (RMSE) ranges from 4 mm/km to 77 mm/km, with an average of 27 mm/km. However, the mean RMSE decreases to 11 mm/km when the 2 mountain rivers are excluded. The WSS accuracies are also compared with slope data sets based on digital elevation models, ICESat‐2 altimetry, and lidar. For 6 rivers the estimated WSS shows the highest accuracy. The improvement was particularly significant for mountain rivers. The proposed approach allows an accurate, non time‐varying high‐resolution WSS even for small and medium‐sized rivers and can be applied to almost any river worldwide. Plain Language Summary: The Water Surface Slope (WSS) of a river is a measure of how steeply it flows downstream. This value affects the velocity of the water and also the force with which the water erodes the river bed. WSS is calculated by dividing the difference between two water surface elevations (WSE) by the length of the river section between these points. In this paper, we determine the non time‐varying WSS on almost every kilometer of 11 Polish rivers. For this purpose, we used almost 30 years of satellite altimetry measurements, which provide information about the height of the water surface at a given place and time. After filtering and mathematical adjustment of these measurements, we determined the WSE and WSS on almost every kilometer of the studied rivers. We compared our results with the average gradients between neighboring water level gauge stations, and for most rivers we obtained very small errors. Compared to other sources of WSS data, our method showed the highest accuracy. The results presented in this work are the first such accurate and spatially dense WSS information of Polish rivers. Moreover, the proposed method allows the determination of WSS on almost any river in the world. Key Points: High‐resolution non time‐varying water surface slope (WSS) for 11 Polish rivers have been determined using cross‐calibrated multi‐mission altimetry measurementsFor 8 rivers studied, we obtained a mean root mean square error of 27 mm/km, which decreases to 11 mm/km if 2 mountain rivers are excludedFor 6 rivers, the estimated WSS showed the highest accuracy compared to WSS data sets based on digital elevation models, ICESat‐2, or lidar [ABSTRACT FROM AUTHOR]

This study assesses the variability of coastal extreme sea levels globally by utilizing nearly three decades of along-track, multi-mission satellite altimetry data. An altimetry-based global coastal database of the non-tidal residual sea level component has been produced. The climate variability of extremes is modeled through a parametric, non-stationary statistical model. This model captures intra-annual, inter-annual and long-term variations in non-tidal residual return levels. Comparisons with tide gauge data demonstrate the ability of altimetry data to capture the variability of coastal extreme sea levels. Our findings reveal a greater complexity in the monthly variability patterns of non-tidal residual extremes in tropical latitudes, often exhibiting multiple storm periods, contrasting with coasts in extratropical latitudes, which are mostly controlled by a winter–summer pattern. This study also highlights the significant influence of established climate circulation patterns on sea level extremes. The positive phase of the Arctic Oscillation pattern leads to increases of over 25% in non-tidal residual return levels in Northwestern Europe with respect to a neutral phase. Furthermore, return levels in the western coast of Central America could be 50% higher during El Niño compared to La Niña. Our results show a robust increasing trend in non-tidal residual return levels along most global coastlines. A comparative analysis shows that variations during the 1995–2020 period were primarily driven by intra-annual variations. [ABSTRACT FROM AUTHOR]