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"Synergistic Observing Network for Ocean Prediction (SynObs)" was launched in 2022 as a project of the United Nations Decade of Ocean Science for Sustainable Development to evaluate the importance of ocean observation systems and co-design the future evolution of the ocean observing network. SynObs is currently leading the flagship OSEs/OSSEs, an internationally coordinated activity in which observing system experiments (OSEs) and observing system simulation experiments (OSSEs) are conducted using a variety of ocean and coupled atmosphere–ocean prediction systems to evaluate ocean observation impacts consistent across most prediction systems. The flagship OSEs/OSSEs comprises the ocean prediction (OP) OSEs for high-resolution ocean predictions, the subseasonal-to-seasonal (S2S) OSEs for long-term lead-time coupled ocean–atmosphere predictions, and the OP OSSEs for evaluating new and future observing systems. SynObs plans to use the results of the flagship OSEs to contribute to the reports on the ocean observing network design made by international organizations and projects. Here, we introduce this initiative, and we report on some initial results. Some observation impacts consistent across four ocean prediction systems are found by a preliminary analysis of the analysis runs for the OP OSEs. For example, impacts of the altimetry data on the assimilated sea surface height (SSH) field are generally large in the westerly boundary current regions and around Antarctic Circumpolar Currents where SSH has large variability but are small in the tropical regions, despite the relatively large SSH variability there. The analysis also indicates the possibility that there are some characteristic differences in the observation impacts between low-resolution and eddy-resolving ocean prediction systems. Although OSE outputs of only four ocean prediction systems are available now, we will make further investigation, adding OSE outputs of other prediction systems that will be submitted in the near future. [ABSTRACT FROM AUTHOR]

Although fluctuations in ice sheet surface mass balance lead to seasonal and interannual elevation changes, it is unclear if they are resolved differently by radar and laser satellite altimeters. We compare methods of computing elevation change from CryoSat‐2 and ICESat‐2 over the Greenland Ice Sheet to assess their consistency and to quantify recent change. Solutions exist such that interannual trends in the interior and the ablation zone agree to within −0.2 ± 1.5 and 3.3 ± 6.0 cm/yr, respectively, and that seasonal cycle amplitudes within the ablation zone agree to within 3.5 ± 38.0 cm. The agreement is best in the north where the measurements are relatively dense and worst in the southeast where the terrain is rugged. Using both missions, we estimate Greenland lost 196 ± 37 km3/yr of volume between 2010 and 2022 with an interannual variability of 129 km3/yr. Plain Language Summary: The polar ice sheets are reacting to climate warming. Changes in their height can be used to study changes in their snowfall, surface melting, glacier flow, and sea level contribution. Although satellite altimeters are able to detect changes in ice sheet height, it is not clear whether these changes are sensed differently by laser and radar systems. Using four years of coincident measurements recorded by ESA's CryoSat‐2 and NASA's ICESat‐2, we show that radar‐laser differences at the ice sheet scale are, in fact, a small proportion (<10%) of the changes in height that are taking place. This means that either system can be used with confidence to study the effects of climate change on the polar ice sheets. At smaller spatial scales, the remaining differences are still important and should be investigated further so that we can understand their causes. Key Points: Greenland Ice Sheet elevation change between 2018 and 2022 from CryoSat‐2 and ICESat‐2 was −11.4 ± 0.8 and −11.7 ± 1.3 cm/yr, respectivelyAblation zone seasonal cycle amplitude between 2018 and 2022 from CryoSat‐2 and ICESat‐2 was 62.9 ± 26.5 and 59.4 ± 24.4 cm, respectivelyVolume change between 2010 and 2022 was −196 ± 37 km3/yr with an interannual variability of 129 km3/yr [ABSTRACT FROM AUTHOR]

Observing System Simulation Experiments (OSSEs) with the Mercator Ocean/Copernicus Marine global 1/12° data assimilation system have been carried out to compare and quantify the expected performance of two high resolution altimetry mission concepts envisioned for the long-term evolution (post-2032) of the Copernicus Sentinel-3 topography mission. The two mission concepts are a constellation of two wide-swath altimeters and a constellation of 12 nadir altimeters. These two configurations greatly improve ocean forecasting and monitoring capabilities. Compared to a constellation of three nadir altimeters (the present configuration), analysis and forecast errors are reduced by a factor of 2. Our results also show that a constellation of two wide-swath altimeters has better performance than a constellation of 12 nadirs. Compared to a constellation of 12 nadirs, the error of the Sea Surface Height (SSH) forecast of a two wide swath constellation is reduced by 14% overall. Improvements are also observed when analyzing surface currents and Lagrangian diagnostics. A constellation of two wide-swath altimeters thus seems to be a very promising concept for the long-term evolution of the Sentinel-3 topography mission. [ABSTRACT FROM AUTHOR]

The use of satellite altimetry data for monitoring the water level regime of rivers in Arctic regions is limited due to the negative effect of complex fluvial morphology and ice cover on altimetric radar measurements. The generation of time series of river water level consists of two main stages: (1) accurate geographic selection of satellite measurements over the river channel and (2) calculation of the average level for a given date after filtering outliers. This work is based on measurements from the European altimetry satellites Sentinel-3A and Sentinel-3B. The paper proposes a method for detection of aberrant values in altimetric measurements (outliers) acquired over a wide floodplain section of the Kolyma River. The method improved the accuracy of resulting satellite time series of water level by 0.04–1.59 m (or 4–85%) compared to the widely used standard statistical method of altimetric measurement filtering. The suggested method is based on the combination of three algorithms of different complexity: statistical (Mahalanobis distance), clustering (Density-Based Spatial Clustering of Applications with Noise (DBSCAN)), and machine learning (Isolating Forest) methods. In the combined approach, values classified as outliers by at least two algorithms were considered as outliers. This approach allowed us to reduce the impact of potential individual shortcomings of each of the three methods. [ABSTRACT FROM AUTHOR]

Data from tide gauges and satellite altimeters are used to provide an up‐to‐date assessment of the mean seasonal cycle in sea level (ζ $\zeta $) over most of the global coastal ocean. The tide gauge records, where available, depict a ζ $\zeta $ seasonal cycle with complex spatial structure along and across continental boundaries, and an annual oscillation dominating over semiannual variability, except in a few regions (e.g., the northwestern Gulf of Mexico). Comparisons between tide gauge and altimeter data reveal substantial root‐mean‐square differences and only slight improvements in agreement when using along‐track data optimized for coastal applications. Quantification of the uncertainty in the altimeter products, inferred from comparing gridded and along‐track estimates, indicate that differences to tide gauges partly reflect short‐scale features of the seasonal cycle in proximity to the coasts. We additionally probe the ζ $\zeta $ seasonal budget using satellite gravimetry‐based manometric estimates and steric terms calculated from the World Ocean Atlas 2023. Focusing on global median values, the sum of the estimated steric and manometric harmonics can explain ∼ ${\sim} $ 65% (respectively 40%) of the annual (semiannual) variance in the coastal ζ $\zeta $ observations. We identify several regions, for example, the Australian seaboard, where the seasonal ζ $\zeta $ budget is not closed and illustrate that such analysis is mainly limited by the coarse spatial resolution of present satellite‐derived mass change products. For most regions with a sufficiently tight budget closure, we find that although the importance of the manometric term generally increases with decreasing water depth, steric contributions are non‐negligible near coastlines, especially at the annual frequency. Key Points: Altimetry and tide gauges disclose the complex spatial structure of the mean sea level seasonal cycle from the coast to adjacent deep watersSum of steric and manometric effects, deduced from observations, explains ∼65% of the annual sea level variance in global set of tide gaugesSatellite gravimetry is useful for examining near‐shore manometric seasonality but coarse spatial resolution remains a limiting factor [ABSTRACT FROM AUTHOR]

Oceanic mesoscale eddies are a kind of typical geostrophic dynamic process which can cause vertical movement in water bodies, thereby changing the temperature, salinity, density, and chlorophyll concentration of the surface water in the eddy. Based on multisource remote sensing data and Argo profiles, this study analyzes and compares the mesoscale eddy properties in four major western boundary current regions (WBCs), i.e., the Kuroshio Extension (KE), the Gulf Stream (GS), the Agulhas Current (AC), and the Brazil Current (BC). The 30-year sea surface height anomaly (SSHA) data are used to identify mesoscale eddies in the four WBCs. Among the four WBCs, the GS eddies have the largest amplitude and the BC eddies have the smallest amplitude. Combining the altimeter-detected eddy results with the simultaneous observations of sea surface temperature, sea surface salinity, sea surface density, and chlorophyll concentration, the local impacts of eddy activities in each WBCs are analyzed. The eddy surface temperature and salinity signals are positively correlated with the eddy SSHA signals, while the eddy surface density and chlorophyll concentrations are negatively correlated with eddy SSHA signals. The correlation analysis of eddy surface signals in the WBCs reveals that eddies have regional differences in the surface signal changes of eddy activities. Based on the subsurface temperature and salinity information provided by Argo profiles, the analysis of the vertical thermohaline characteristics of mesoscale eddies in the four WBCs is carried out. Eddies in the four WBCs have deep influence on the vertical thermohaline characteristics of water masses, which is not only related to the strong eddy activities but also to the thick thermocline and halocline of water masses in the WBCs. [ABSTRACT FROM AUTHOR]

Satellite altimetry observations are checked against in situ measurements to assess the capability of this remote sensing technique to describe the surface circulation in the Ligurian Sea. CTD profiles were collected during five oceanographic campaigns from 2017 and 2024 along the satellite track Jason 044, crossing the Ligurian Sea from the Corsica Channel to the coast close to Genoa. Eight months of ADCP surface currents from a fixed mooring were also used for the comparison with altimetric-derived geostrophic currents. Moreover, the possible contribution of ICESat-2 to oceanographic studies in the area is investigated. Altimetric measurements successfully reproduce the basic circulation features of the region and their seasonal variation and, despite the different nature of the used systems, can be well integrated with in situ observations. The results from the direct comparison with daily mean values of ADCP surface currents reported an RMSD of the same order as the standard deviation, which is consistent with similar investigations in other areas but evidences the need to define more appropriate metrics and methods. [ABSTRACT FROM AUTHOR]

Global marine vertical deflection is essential for understanding Earth's internal mass and density distribution and improving the long-term inertial navigation accuracy of underwater vehicles. Spaceborne global navigation satellite system reflectometry (GNSS-R) interferometric altimetry, with its advantages of low-cost, rapid global coverage, and revisiting capability, shows promise as new data for compensating the radar altimeters. In this study, we present the first simulation of spaceborne GNSS-R interferometric altimetry data based on FY-3E GNSS-R trajectory and evaluate its potential for inverting global marine vertical deflection. Our results showed that, in the operational scenario (with a spatial resolution of 10 km and an altimetry accuracy of 14.68 cm), the total accuracy of marine vertical deflection for global 2.5′, 5′, and 20′ grids, obtained from ten years of simulation data, was 4.998″, 1.268″, and 0.1″, respectively. Furthermore, we observed that, when the average global revisit times reached approximately 90 times and 6 times, the total accuracy of marine vertical deflection for global 5′ and 20′ grids was below 1″. As the GNSS-R detection on the FY-3E satellite covers 90% of the global sea area in 20′ grids within 23 days, with an average revisit time of 7.3, spaceborne GNSS-R interferometric altimetry has the potential to invert the high-precision time-variable gravity field with a 20′ resolution, thus compensating for the lower resolution provided by satellite gravimetry.

In East Antarctica, the largest thinning rates are observed at Totten Glacier in recent years. Hydrologic activity of the three active subglacial lakes (Totten1, Totten2, and Wilkes1) located on Totten Glacier may affect the ice sheet mass balance in the region on time scales of decades. In this article, we utilized laser altimetry data (ICESat and ICESat-2) and radar altimetry data (CryoSat-2 and Sentinel-3) to establish a 20-year time series of surface ice sheet elevation changes for three subglacial lakes, employing different least squares fitting methods, and this analysis aimed to study their hydrological activities. Additionally, we combined REMA and BedMachine data to acquire the subglacial drainage pathways in the region, analyzing the hydrological connections among the three subglacial lakes. The results indicate that Totten1 and Totten2 exhibited frequent inflow and outflow throughout the observation period, with periodic characteristics in lake activities. From 2003 to 2009, Wilkes1 showed an ascending trend in surface ice sheet elevation, followed by a relatively stable state. The characteristics of lake activities changes and subglacial drainage pathways indicate connections among these three subglacial lakes. This article highlights that CryoSat-2 and Sentinel-3 radar data can fill the gaps between ICESat and ICESat-2 data. Furthermore, ICESat-2 laser altimetry data not only extend the records of subglacial lake activities but also capture more densely and accurately resolved spatial details. The integration of these four altimeters proves effective for long-term monitoring of active subglacial hydrological activities.

Abstract For more than three decades, satellite altimetry has provided valuable measurement data for the monitoring and analysis of ocean and inland water surfaces. Since 1992, there have always been at least two simultaneous missions providing continuous measurement data, starting with TOPEX/Poseidon and ERS‐1 in the early 1990s and continuing with about 10 satellites active today, including ICESat‐2, Sentinel‐6A and SWOT. Most mission data are freely available, but in different formats, processing levels and with respect to different references (e.g. ellipsoid or time), making common multi‐mission applications difficult. In addition, the derivation of ready‐to‐use and high‐quality scientific products requires expertise that not every user is willing to acquire. Over the years, DGFI‐TUM has developed and maintained an Open Altimeter Database (OpenADB) that allows consistent data management and combination. It consists of the internal Multi‐Version Altimetry (MVA) data repository and the OpenADB web portal. OpenADB provides user‐friendly access to derived along‐track products, such as sea surface heights and ocean tides. It also provides general information about the satellite altimetry missions, their observing configurations and about the data provided in the database. All products are freely available on the OpenADB web portal (https://openadb.dgfi.tum.de) after registration.

In the current most accepted global geopotential model, EGM2008, there are often data gaps in the source data used to compute the model over inland water. As a result, EGM2008 may be less reliable over lakes. Satellite altimetry has the potential to estimate gravity anomalies and update EGM2008 over lakes. Here, we evaluate the first attempt to extract gravity anomalies from ICESat-2 laser altimetry over several medium (100–1000 km 2 ) and large (>1000 km 2 ) lakes and compare them with conventional radar altimetry from CryoSat-2 and SARAL to investigate the performance of ICESat-2 for gravity determination over lakes. Aerial gravimetry from the GRAV-D project over the United States are utilized as the best estimate of the gravity field over the lakes. Gravity determination from altimetry is done using Fast Fourier Techniques (FFT) within a remove-restore geoid-to-gravity approach. The resulting altimetry derived gravity anomalies are then compared to the EGM2008 geoid over each lake with respect to GRAV-D. 18 lakes with area ranging from 108 km 2 to 82,220 km 2 across the United States were considered. Overall, gravity determination from ICESat-2 provides more reliable estimates than the other two radar altimetry missions. For all considered lakes, the performance of ICESat-2, measured in terms of standard deviation with GRAV-D, is comparable or better than the EGM2008 field over the same lake. Lake Pend Orielle is the best performing case, in which the standard deviation of the ICESat-2 derived gravity field is 2.14 mGal and the standard deviation of the EGM2008 gravity field is 2.66 mGal with respect to the GRAV-D measurements. Over Lake Tahoe, which is surrounded by mountainous terrain, ICESat-2 performs comparably to EGM2008 and captures clear gravity signal related to the lake's bathymetry, whereas CryoSat-2 produces very unstable results. The method presented here for deriving gravity anomalies from altimetry applied to ICESat-2 laser altimetry data produces results that validate in supplement to the GRAV-D project over medium to large lakes in the United States. [ABSTRACT FROM AUTHOR]

The present study introduces a comprehensive, open-access atlas of mesoscale eddies in the global ocean, as identified and tracked by the TOEddies algorithm implemented on a global scale. Unlike existing atlases, TOEddies detects eddies directly from absolute dynamic topography (ADT) without spatial filtering, preserving the natural spatial variability and enabling precise, high-resolution tracking of eddy dynamics. This dataset provides daily information on eddy characteristics, such as size, intensity, and polarity, over a 30-year period (1993–2023), capturing complex eddy interactions, including splitting and merging events that often produce networks of interconnected eddies. This unique approach challenges the traditional single-trajectory perspective, offering a nuanced view of eddy life cycles as dynamically linked trajectories. In addition to traditional metrics, TOEddies identifies both the eddy core (characterized by maximum azimuthal velocity) and the outer boundary, offering a detailed representation of eddy structure and enabling precise comparisons with in situ data. To demonstrate its value, we present a statistical overview of eddy characteristics and spatial distributions, including generation, disappearance, and merging/splitting events, alongside a comparative analysis with existing global eddy datasets. Among the multi-year observations, TOEddies captures coherent, long-lived eddies with lifetimes exceeding 1.5 years, while highlighting significant differences in the dynamic properties and spatial patterns across datasets. Furthermore, this study integrates TOEddies with 23 years of colocalized Argo profile data (2000–2023), allowing for a novel examination of eddy-induced subsurface variability and the role of mesoscale eddies in the transport of global ocean heat and biogeochemical properties. This atlas aims to be a valuable resource for the oceanographic community, providing an open dataset that can support diverse applications in ocean dynamics, climate research, and marine resource management. [ABSTRACT FROM AUTHOR]

Internal tides serve as essential intermediate steps in the cascading of oceanic energy, playing a crucial role in oceanic mixing. M2 internal tides are the dominant tidal constituent in many oceanic regions, significantly influencing ocean dynamics. The Madagascar–Mascarene Region has high-energy internal tides, but due to a lack of observational studies, their propagation remains underexplored and warrants further investigation. In this study, we used satellite altimetry data to capture the sea surface manifestation of the first-mode M2 internal tides in the region. The results show that the Mascarene Plateau plays a key role in shaping the region's uneven internal tide distribution. The Mascarene Strait is the most intense generation area, with an east-west energy flux of 1.42 GW. Using the internal tidal energy concentration index, we decomposed the internal tidal beams, finding the primary beam oriented at 148°. These beams propagate outward for over 800 km, with a maximum distance exceeding 1000 km. Geostrophic currents intensify the northward refraction of westward-propagating internal tides in the Mascarene Basin, particularly between 15°S and 20°S. [ABSTRACT FROM AUTHOR]

"Synergistic Observing Network for Ocean Prediction (SynObs)" was launched in 2022 as a project of the United Nations Decade of Ocean Science for Sustainable Development to evaluate the importance of ocean observation systems and co-design the future evolution of the ocean observing network. SynObs is currently leading the flagship OSEs/OSSEs, an internationally coordinated activity in which observing system experiments (OSEs) and observing system simulation experiments (OSSEs) are conducted using a variety of ocean and coupled atmosphere–ocean prediction systems to evaluate ocean observation impacts consistent across most prediction systems. The flagship OSEs/OSSEs comprises the ocean prediction (OP) OSEs for high-resolution ocean predictions, the subseasonal-to-seasonal (S2S) OSEs for long-term lead-time coupled ocean–atmosphere predictions, and the OP OSSEs for evaluating new and future observing systems. SynObs plans to use the results of the flagship OSEs to contribute to the reports on the ocean observing network design made by international organizations and projects. Here, we introduce this initiative, and we report on some initial results. Some observation impacts consistent across four ocean prediction systems are found by a preliminary analysis of the analysis runs for the OP OSEs. For example, impacts of the altimetry data on the assimilated sea surface height (SSH) field are generally large in the westerly boundary current regions and around Antarctic Circumpolar Currents where SSH has large variability but are small in the tropical regions, despite the relatively large SSH variability there. The analysis also indicates the possibility that there are some characteristic differences in the observation impacts between low-resolution and eddy-resolving ocean prediction systems. Although OSE outputs of only four ocean prediction systems are available now, we will make further investigation, adding OSE outputs of other prediction systems that will be submitted in the near future. [ABSTRACT FROM AUTHOR]

The gravity–geologic method (GGM) is widely used for bathymetric predictions. However, the conventional GGM cannot be applied in regions without actual bathymetric data. The modified gravity–geologic method (MGGM) enhances the accuracy of bathymetric models by supplementing short-wavelength gravity anomalies with an a priori bathymetric model, but it overlooks the significance of actual bathymetric data in the prediction process. In this study, we used the BP neural network (BPNN), incorporating shipborne depth soundings and coastline data as zero-depth estimates combined with the MGGM to produce a bathymetric model (BPGGM_BAT) for the South China Sea (105°E–122°E, 0°N–26°N). The results indicate that the BPGGM_BAT model decreases the root-mean-square (RMS) of bathymetry differences from 154.33 m to approximately 140.43 m relative to multibeam depth data. Additionally, the RMS differences between the BPGGM_BAT model and multibeam depth data show further improvements of 19.63%, 20.10%, and 19.54% when compared with the recently released SRTM15_V2.6, GEBCO_2022, and topo_V27.1 models, respectively. The precision of the BPGGM_BAT model is comparable to that of the SDUST2023BCO model, as verified using multibeam depth data in open sea regions. The BPGGM_BAT model outperforms existing models with RMS differences of 8.54% to 32.66%, as verified using Electronic Navigational Chart (ENC) bathymetric data in the regions around the Zhongsha and Nansha Islands. A power density analysis suggests that the BPGGM_BAT model is superior to the MGGM_BAT model for predicting seafloor topography within wavelengths shorter than 15 km, and its performance is closely consistent with that of the topo_V27.1 and SDUST2023BCO models. Overall, this integrated method demonstrates significant potential for improving the accuracy of bathymetric predictions. [ABSTRACT FROM AUTHOR]

The ICESat-2 and SWOT satellite earth observation missions have provided highly accurate water surface slope (WSS) observations in global rivers for the first time. While water surface slope is expected to remain constant in time for approximately uniform flow conditions, we observe time varying water surface slope in many river reaches around the globe in the ICESat-2 record. Here, we investigate the causes of time variability of WSSs using simplified river hydraulic models based on the theory of steady, gradually varied flow. We identify bed slope or cross section shape changes, river confluences, flood waves, and backwater effects from lakes, reservoirs, or the ocean as the main non-uniform hydraulic situations in natural rivers that cause time changes of WSSs. We illustrate these phenomena at selected river sites around the world, using ICESat-2 data and river discharge estimates. The analysis shows that WSS observations from space can provide new insights into river hydraulics and can enable the estimation of river discharge from combined observations of water surface elevation and WSSs at sites with complex hydraulic characteristics. [ABSTRACT FROM AUTHOR]

Polar sea surface height observation by radar altimeters requires missions with high-latitude orbit and specific processing to observe the sea-ice-covered region within fractures in the ice. Here, we combine sea surface height estimates from different radar satellites over the ice-free and ice-covered polar oceans to create cross-calibrated along-tracks and gridded products over the Arctic Ocean (2011-2021) and the Southern Ocean (2013-2021). The sea surface height from our regional polar products is in great agreement with tide gauges and bottom pressure recorders at monthly timescales in seasonally to year-round icecovered regions. Thanks to the use of several missions and the mapping strategy, our multi-mission products have a greater resolution than monomission products. Part of the sea level variability of the Arctic Ocean product is related to the Arctic Oscillation atmospheric circulation. At long term, the Arctic altimetry sea level is coherent with in-situ steric height evolution in the Beaufort gyre, and negative sea level trends over the 10-year period are observed in the East Siberian slope region, which may be related to the local freshwater decrease observed by other studies. Our regional polar sea level products are limited by current understanding of the sea-ice lead measurements, and homogenization of these polar products with global sea level products needs to be tackled. [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]

Accurately monitoring vertical land motion (VLM) near coasts and understanding its spatial and temporal variability is crucial for quantifying its impact on water-land interactions. VLM can be estimated from the global navigation satellite system (GNSS) time series, but only a few tide gauges (TGs) are equipped with a GNSS receiver. TG records encompass relative sea level (RSL) change and VLM, while satellite altimetry (SA) provides absolute sea level (ASL) change in the Earth's center-fixed frame. Accordingly, the difference between these two observations can be used to estimate geocentric VLM along the coasts (altimetry-minus-TG, ALT-TG). This paper addresses the temporal correlated noise in time series to reduce its effect on sea level estimation. Firstly, we analyze the ASL trends at 13 Australian sites using the optimal stochastic noise model from 1993-2021. The mean ASL trend is found to be 3.01 ± 0.75 mm/a from SA, and the mean RSL trend is 4.61 ± 2.00 mm/a, and it shows a good consistency of existing research of White et al. (2014) with 3.40 ± 0.40 mm/a (ASL) and 4.50 ± 1.30 mm/a (RSL). Secondly, the estimated GNSS trend shows a good agreement with NGL/SONEL solutions, and we utilized the weighted VLM as a reference to ALT-TG estimation. Thirdly, our study shows that the standard deviation (SD) of the VLM difference between ALT-TG and GNSS is 0.46 mm/a (the VLM difference typically between ~±0.12-1.68 mm/a), which indicates that it is possible to utilize SA and TG data for VLM estimation along the coastline of Australia. Furthermore, we investigate the accuracy of ALT-TG inversion for VLM and its influencing factors. Our findings indicate that, in regions with high observation quality and reliable data sources, the length of the overlapping period between TG and GNSS observations is the most critical parameter affecting the consistency of trend between the two technologies. [ABSTRACT FROM AUTHOR]

Estimates and projections of sea level change are critical for coastal areas. In this work, we utilize satellite altimetry (SA) and tide gauge (TG) technologies to estimate variations in sea level, and we also evaluate the consistency of sea level changes obtained using TG and SA from 1993 to 2020. Additionally, we use deep learning models (artificial neural network (ANN), gated recurrent unit (GRU), and long short-term memory (LSTM)) to forecast sea level changes with SA time series. Our results reveal that the average absolute sea level (ASL) rate in the China Seas and the neighboring ocean based on SA is 3.55 mm/yr, which is higher than the global rate of 3.30 mm/yr. Specifically, the ASL rates of East China Sea and South China Sea are 3.21 mm/yr and 4.24 mm/yr, respectively. The sea level change in the South China Sea is significantly greater than that in the East China Sea. Secondly, the relative sea level (RSL) rate based on TGs is 3.88 mm/yr. We perform VLM correction on TGs with co-located GNSS following the method of Zhou et al. (2022) and obtain a TG-based ASL result of 3.77 mm/yr. Our results show that there is good consistency between coastal sea level changes estimated using tide gauges and satellite radar altimetry. Finally, we use the ANN, GRU, and LSTM models to predict sea level change with SA. The results show that LSTM's prediction accuracy is better than that of the other models, with average RMSE, MAE, and R² values of 48.92 mm, 35.99 mm, and 0.85, respectively. [ABSTRACT FROM AUTHOR]

For more than three decades, satellite altimetry has provided valuable measurement data for the monitoring and analysis of ocean and inland water surfaces. Since 1992, there have always been at least two simultaneous missions providing continuous measurement data, starting with TOPEX/Poseidon and ERS‐1 in the early 1990s and continuing with about 10 satellites active today, including ICESat‐2, Sentinel‐6A and SWOT. Most mission data are freely available, but in different formats, processing levels and with respect to different references (e.g. ellipsoid or time), making common multi‐mission applications difficult. In addition, the derivation of ready‐to‐use and high‐quality scientific products requires expertise that not every user is willing to acquire. Over the years, DGFI‐TUM has developed and maintained an Open Altimeter Database (OpenADB) that allows consistent data management and combination. It consists of the internal Multi‐Version Altimetry (MVA) data repository and the OpenADB web portal. OpenADB provides user‐friendly access to derived along‐track products, such as sea surface heights and ocean tides. It also provides general information about the satellite altimetry missions, their observing configurations and about the data provided in the database. All products are freely available on the OpenADB web portal (https://openadb.dgfi.tum.de) after registration. [ABSTRACT FROM AUTHOR]

Ocean eddies affect large‐scale circulation and induce a kinetic energy cascade through their non‐linear interactions. However, since global observations of eddy dynamics come from satellite altimetry maps that smooth eddies and distort their geometry, the strength of this cascade is underestimated. Here, we use deep learning to improve observational estimates of global surface geostrophic currents and explore the implications for the cascade. By synthesizing multi‐modal satellite observations of sea surface height (SSH) and temperature, we achieve up to a 30% improvement in spatial resolution over the community‐standard SSH product. This reveals numerous strongly interacting eddies that were previously obscured by smoothing. In many regions, these newly resolved eddies lead to nearly an order‐of‐magnitude increase in the upscale kinetic energy cascade that peaks in spring and is strong enough to drive the seasonality of large mesoscale eddies. Our study suggests that deep learning can be a powerful paradigm for satellite oceanography. Plain Language Summary: We developed a deep learning method to estimate global maps of surface ocean currents from satellite observations with significantly improved resolution and accuracy compared to existing methods. These maps dramatically improve our ability to observe eddy dynamics and the impact of eddies on the transfer of energy between scales in the ocean. Our study suggests that deep learning can be a powerful paradigm for satellite oceanography. Key Points: We develop the first deep learning global estimates of surface ocean currents from multi‐modal satellite observationsOur deep learning method is able to map surface currents with state‐of‐the‐art resolution and accuracyThe diagnosed kinetic energy cascade is an order of magnitude higher compared to conventional altimetry products [ABSTRACT FROM AUTHOR]

Satellite altimetry provides high-accuracy geometrical measurements of sea level changes. We analyze altimetry time series representing sea surface height anomalies over the mean sea surface provided by the TOPEX/Poseidon, Jason-1, Jason-2, and Jason-3 satellite missions to estimate the annual rate of sea level rise. Then, we compare the results with satellite gravimetric data from GRACE and GRACE Follow-On missions and surface water temperature data, employing statistical analyses to examine the interrelationships and correlations between them. We carry out the main analyses for the period 2001–2021 with a division into 5-year periods for six different areas of the Baltic Sea. The altimetric results show that between 2001 and 2021, the water level of the Baltic Sea rose by 5.8 mm/year on average. About 72% of the changes detected by altimetry missions can be explained by satellite gravimetry from GRACE and GRACE Follow-On, which means that the mass component is responsible for most of the observed sea level change, whereas the remaining 28% can be greatly explained by thermal expansion due to the water temperature rise. [ABSTRACT FROM AUTHOR]

A comprehensive analysis was carried out to investigate the driving factors and influencing mechanisms of spatiotemporal variation of sea level at multiple scales in the East China Sea (ECS) via satellite altimetry datasets from 1993 to 2020. Based on the altimetry grid data processed by the local mean decomposition method, the spatiotemporal changes of ECS sea level are analyzed from the multi-scale perspective in terms of multi-year, seasonal, interannual, and multi-modal scales. The results revealed that the ECS regional mean sea level change rate is 3.41 ± 0.58 mm/year over the 28-year period. On the seasonal scale, the regional mean sea level change rates are 3.45 ± 0.66 mm/year, 3.35 ± 0.60 mm/year, 3.39 ± 0.71 mm/year, and 3.57 ± 0.75 mm/year, for the four seasons (i.e., spring, summer, autumn, and winter) respectively. The spatial distribution analysis showed that ECS sea level changes are most pronounced in coastal areas. The northeast sea area of Taiwan and the edge of the East China Sea shelf are important areas of mesoscale eddy activity, which have an important impact on regional sea level change. The ECS seasonal sea level change is mainly affected by monsoons, precipitation, and temperature changes. The spatial distribution analysis indicated that the impact factors, including seawater thermal expansion, monsoons, ENSO, and the Kuroshio Current, dominated the ECS seasonal sea level change. Additionally, the ENSO and Kuroshio Current collectively affect the spatial distribution characteristics. Additionally, the empirical orthogonal function was employed to analyze the three modes of ECS regional sea level change, with the first three modes contributing 26.37%, 12.32%, and 10.47%, respectively. Spatially, the first mode mainly corresponds to ENSO index, whereas the second and third modes are linked to seasonal factors, and exhibit antiphase effects. The analyzed correlations between the ECS sea level change and southern oscillation index (SOI), revealed the consistent spatial characteristics between the regions affected by ENSO and those by the Kuroshio Current. [ABSTRACT FROM AUTHOR]

Lakes provide societies and natural ecosystems with valuable services such as freshwater supply and flood control. Water level changes in lakes reflect their natural responses to climatic and anthropogenic stressors; however, their monitoring is costly due to installation and maintenance requirements. With its advanced hardware and computational capabilities, altimetry has become a popular alternative to conventional in-situ gauging, although subject to the temporal availability of altimetric observations. To further improve the temporal resolution of altimetric measurements, we here combine radar altimetry data with Differential Interferometric Synthetic Aperture Radar (D-InSAR), using ten lakes in Sweden as a testing platform. First, we use Sentinel-1A and Sentinel-1B SAR images to generate consecutive six-day baseline interferograms across 2019. Then, we accumulate the phase change of coherent pixels to construct the time series of InSAR-derived water level anomalies. Finally, we retrieve altimetric observations from Sentinel-3, estimate their mean and standard deviation, and apply them to the D-InSAR standardized anomalies. In this way, we build a water-level time series with more temporal observations. In general, we find a strong agreement between water level estimates from the combination of D-InSAR and Satellite Altimetry (DInSAlt) and in-situ observations in eight lakes (Concordance Correlation Coefficient - CCC >0.8) and moderate agreement in two lakes (CCC >0.57). The applicability of DInSAlt is limited to lakes with suitable conditions for double-bounce scattering, such as the presence of trees or marshes. The accuracy of the water level estimates depends on the quality of the altimetry observations and the lake's width. These findings are important considering the recently launched Surface Water and Ocean Topography (SWOT) satellite, whose capabilities could expand our methodology's geographical applicability and reduce its reliance on ground measurements.

Observing System Simulation Experiments (OSSEs) with the Mercator Ocean/Copernicus Marine global 1/12° data assimilation system have been carried out to compare and quantify the expected performance of two high resolution altimetry mission concepts envisioned for the long-term evolution (post-2032) of the Copernicus Sentinel-3 topography mission. The two mission concepts are a constellation of two wide-swath altimeters and a constellation of 12 nadir altimeters. These two configurations greatly improve ocean forecasting and monitoring capabilities. Compared to a constellation of three nadir altimeters (the present configuration), analysis and forecast errors are reduced by a factor of 2. Our results also show that a constellation of two wide-swath altimeters has better performance than a constellation of 12 nadirs. Compared to a constellation of 12 nadirs, the error of the Sea Surface Height (SSH) forecast of a two wide swath constellation is reduced by 14% overall. Improvements are also observed when analyzing surface currents and Lagrangian diagnostics. A constellation of two wide-swath altimeters thus seems to be a very promising concept for the long-term evolution of the Sentinel-3 topography mission.

Vertical land motion (VLM) is complex in Southeast Asia because this region is subject to a range of natural processes (e.g., earthquakes) and anthropogenic activities (e.g., groundwater withdrawal) that can change land heights. To aid in coastal management, long-term observations of VLM are as crucial as observations for climate-induced sea surface height changes; however, such long-term observations are sparse for Southeast Asian coasts. To fill this observational gap, here we derive monthly VLM time series from 1993 to 2020 at 50 coastal sites across Southeast Asia by combining tide-gauge records and newly generated satellite altimetry observations. These altimetry observations are reproduced sea-level products using new altimetry standards and more accurate geophysical corrections. Our 27-year-long VLM dataset shows high spatial variability and non-linear temporal changes in VLM across Southeast Asia. We identify several major sources that dominate the regional land-height changes, which include large subsidence due to groundwater extraction in Manila and Bangkok, land uplift in Indonesia and subsidence in Thailand from postseismic deformation resulting from the sequence of large Sumatran earthquakes since 2004, and land subsidence as a result of sediment compaction in Malaysia. Those signals are quantitatively or qualitatively consistent with observations from other sources. This VLM dataset can be used to advance our understanding of the physical mechanisms behind land-height changes and to improve sea level projections in the region.

In the absence of in-situ data, satellite radar altimetry, critical for studies requiring water elevation data, faces challenges in outlier removal over reservoirs, influenced by surrounding land. We present JASTER (Jason Altimetry Stand-Alone Tool for Enhanced Research), an open-source, fully automated tool processing Jason-2/3 altimetry data for water elevation time series generation over a user-defined inland water body. JASTER uses two outlier removal approaches. The first method employs interquartile range (IQR)-based filtering and K-means clustering. The second method incorporates water occurrence (WO) and Digital Elevation Model (DEM)-derived elevation thresholds. The Hampel filter embedded in JASTER further removes non-physical peaks in the time series caused by signal noise. We validated JASTER’s capabilities using 44 Jason altimeter crossings over 37 water bodies in the US and Canada. We assessed the significance of applying water occurrence and elevation thresholds, and investigated how the Hampel filter parameters and satellite crossing lengths affect accuracy. In all case studies, the Hampel filter significantly increased the consistency between JASTER-derived water elevations and in-situ data. Moreover, the DEM + WO-based method outperformed the IQR-based outlier removal approach in some cases where the greater number of altimeter footprints belonged to land instead of water.

China has successfully launched four Haiyang-2 (HY-2) series altimetry satellites. HY-2A has attracted significant attention in gravity field recovery, but the performance of other HY-2 series satellites, including HY-2B/C/D, is seldom discussed. This study evaluated the performance of all the HY-2 series satellites in recovering marine gravity field. First, the crossover discrepancies in sea surface height of the four satellites, HY-2A, HY-2B, HY-2C, and HY-2D, were analyzed to assess their altimetry stability. It was found that HY-2B had the best altimetry quality, followed by HY-2D. Subsequently, different combinations of altimetry data were used to calculate vertical deflections and gravity anomalies in the South China Sea (112°E−119°E, 12°N-20°N). The results showed that combining data from HY-2B, HY-2C, and HY-2D improved the inversion accuracy of gravity anomalies by 0.3 mGal compared to using HY-2A data alone. HY-2C and HY-2D contributed to enhancing the accuracy of the east component of vertical deflections.

This research aims to optimize the utilization of long-term sea level data from the TOPEX/Poseidon, Jason1, Jason2, and Jason3 altimetry missions for tidal modeling. We generate a time series of along-track observations and apply a developed method to produce tidal models with specific tidal constituents for each location. Our tidal modeling methodology follows an iterative process: partitioning sea surface height (SSH) observations into analysis/training and prediction/validation parts and ultimately identifying the set of tidal constituents that provide the best predictions at each time series location. The study focuses on developing 1256 time series along the altimetry tracks over the Baltic Sea, each with its own set of tidal constituents. Verification of the developed tidal models against the SSH observations within the prediction/validation part reveals mean absolute error (MAE) values ranging from 0.0334 m to 0.1349 m, with an average MAE of 0.089 m. The same validation process is conducted on the FES2014 and EOT20 global tidal models, demonstrating that our tidal model, referred to as BT23 (short for Baltic Tide 2023), outperforms both models with an average MAE improvement of 0.0417 m and 0.0346 m, respectively. In addition to providing details on the development of the time series and the tidal modeling procedure, we offer the 1256 along-track time series and their associated tidal models as supplementary materials. We encourage the satellite altimetry community to utilize these resources for further research and applications.

The development of satellite altimetry has significantly advanced the application of satellite Earth observation technologies in surface water monitoring, resulting in a substantial body of research. Although numerous reviews have summarized progress in this field, their analyses are often limited in scope and fail to provide a systematic, quantitative assessment of the current research prospects and trends. To address this gap, we utilize CiteSpace and VOSviewer bibliometric software to analyze 13,500 publications from the WOS database, spanning the years from 1988 to 2022. Our analysis focused on publication volume, authorship, collaboration networks, and content. We also compare data from Google Scholar and Scopus to validate the reliability of our dataset. Our findings indicate a steadily growing research potential in this field, as evidenced by trends in publication volume, authorship, journal influence, and disciplinary focus. Notably, the leading journals are primarily in the realm of remote sensing, while key disciplines include geology, remote sensing science, and oceanography. Keyword analysis revealed current research hotspots such as sea-level rise, snow depth, and machine learning applications. Among various water body types, research on glaciers ranks second only to ocean studies. Furthermore, research focus areas are shifting from large oceanic regions like the Pacific and Atlantic Oceans to significant inland water bodies, notably the Tibetan Plateau and the Amazon basin. This study combines qualitative and quantitative methods to analyze vast amounts of information in the field of surface water monitoring by satellite altimetry. The resulting visualizations provide researchers with clear insights into the development trends and patterns within this domain, offering valuable support for identifying future research priorities and directions. [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]

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 Copernicus Sentinel-6 Michael Freilich (S6-MF) and Jason-3 (J3) Tandem Experiment (S6-JTEX) provided over 12 months of closely collocated altimeter sea state measurements, acquired in "low-resolution" (LR) and synthetic aperture radar "high-resolution" (HR) modes onboard S6-MF. The consistency and uncertainties associated with these measurements of sea state are examined in a region of the eastern North Pacific. Discrepancies in mean significant wave height (Hs, 0.01 m) and root-mean-square deviation (0.06 m) between J3 and S6-MF LR are found to be small compared to differences with buoy data (0.04, 0.29 m). S6-MF HR data are found to be highly correlated with LR data (0.999) but affected by a nonlinear sea state-dependent bias. However, the bias can be explained robustly through regression modelling based on Hs. Subsequent triple collocation analysis (TCA) shows very little difference in measurement error (0.18 ± 0.03 m) for the three altimetry datasets, when analysed with buoy data (0.22 ± 0.02 m) and ERA5 reanalysis (0.27 ± 0.02 m), although statistical precision, limited by total collocations (N = 535), both obscures interpretation and motivates the use of a larger dataset. However, we identify uncertainties in the collocation methodology, with important consequences for methods such as TCA. Firstly, data from some commonly used buoys are found to be statistically questionable, possibly linked to erroneous buoy operation. Secondly, we develop a methodology based on altimetry data to show how statistically outlying data also arise due to sampling over local sea state gradients. This methodology paves the way for accurate collocation closer to the coast, bringing larger collocation sample sizes and greater statistical robustness. [ABSTRACT FROM AUTHOR]

Satellite altimetry offers a unique approach for direct sea surface current observation, but it is limited to measuring the surface‐constrained geostrophic component. Ageostrophic dynamics, prevalent at horizontal scales below 100 km and time scales below 10 days, are often underestimated by ocean reanalyzes employing data assimilation schemes. To address this limitation, we introduce a novel deep learning scheme, rooted in a variational data assimilation formulation with trainable observations and a priori terms, that harnesses the synergies between satellite‐derived sea surface observations, namely sea surface height (SSH) and sea surface temperature (SST), to enhance sea surface current reconstruction. Numerical experiments, conducted using realistic simulations, in a case study area of the Gulf Stream, demonstrate the potential of the proposed scheme to capture ageostrophic dynamics at time scales of 2.5–3.0 days and horizontal scales of 0.5°–0.7°. The analysis of diverse observation configurations, encompassing nadir along‐track altimetry, wide‐swath SWOT (Surface Water and Ocean Topography) altimetry, and SST data, highlights the pivotal role of SST features in retrieving a significant portion of the ageostrophic dynamics (approximately 47%). These findings underscore the potential of deep learning and 4DVarNet schemes in improving ocean reanalyzes and enhancing our understanding of ocean dynamics. Plain Language Summary: Satellite altimetry provides a unique means for direct observation of sea surface currents, but it is confined to the geostrophic component, limiting the recovery of a substantial portion of mesoscale sea surface currents in operational products. To address this limitation, we present a novel deep learning framework, rooted in a variational data assimilation paradigm, that unlocks new avenues for leveraging the synergistic relationships between satellite‐derived sea surface observations, namely sea surface height and sea surface temperature. This innovative scheme demonstrates its remarkable potential to enhance sea surface current reconstruction and recover a substantial portion of the elusive ageostrophic dynamics. Numerical experiments, employing realistic simulations, in a case study area along the Gulf Stream, underscore the efficacy of our proposed approach. These findings support the pivotal role of physics‐informed deep learning in maximizing the utilization of available multimodal observation data sets and numerical simulations to elucidate partially observed sea surface dynamics. Key Points: We present end‐to‐end deep learning schemes to improve the reconstruction of total sea surface currents from satellite‐derived observationsExperiments in a region of the Gulf Stream support the synergistic analysis of sea surface temperature and sea surface height dataThe strain of sea surface dynamics is a proxy of the uncertainty of the retrieved estimation [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]

“Synergistic Observing Network for Ocean Prediction (SynObs)” was launched in 2022 as a project of the United Nations Decade of Ocean Science for Sustainable Development to evaluate the importance of ocean observation systems and co-design the future evolution of the ocean observing network. SynObs is currently leading the flagship OSEs/OSSEs, an internationally coordinated activity in which observing system experiments (OSEs) and observing system simulation experiments (OSSEs) are conducted using a variety of ocean and coupled atmosphere–ocean prediction systems to evaluate ocean observation impacts consistent across most prediction systems. The flagship OSEs/OSSEs comprises the ocean prediction (OP) OSEs for high-resolution ocean predictions, the subseasonal-to-seasonal (S2S) OSEs for long-term lead-time coupled ocean–atmosphere predictions, and the OP OSSEs for evaluating new and future observing systems. SynObs plans to use the results of the flagship OSEs to contribute to the reports on the ocean observing network design made by international organizations and projects. Here, we introduce this initiative, and we report on some initial results. Some observation impacts consistent across four ocean prediction systems are found by a preliminary analysis of the analysis runs for the OP OSEs. For example, impacts of the altimetry data on the assimilated sea surface height (SSH) field are generally large in the westerly boundary current regions and around Antarctic Circumpolar Currents where SSH has large variability but are small in the tropical regions, despite the relatively large SSH variability there. The analysis also indicates the possibility that there are some characteristic differences in the observation impacts between low-resolution and eddy-resolving ocean prediction systems. Although OSE outputs of only four ocean prediction systems are available now, we will make further investigation, adding OSE outputs of other prediction systems that will be submitted in the near future.

Polar sea surface height observation by radar altimeters requires missions with high-latitude orbit and specific processing to observe the sea-ice-covered region within fractures in the ice. Here, we combine sea surface height estimates from different radar satellites over the ice-free and ice-covered polar oceans to create cross-calibrated along-tracks and gridded products over the Arctic Ocean (2011–2021) and the Southern Ocean (2013–2021). The sea surface height from our regional polar products is in great agreement with tide gauges and bottom pressure recorders at monthly timescales in seasonally to year-round ice-covered regions. Thanks to the use of several missions and the mapping strategy, our multi-mission products have a greater resolution than mono-mission products. Part of the sea level variability of the Arctic Ocean product is related to the Arctic Oscillation atmospheric circulation. At long term, the Arctic altimetry sea level is coherent with in-situ steric height evolution in the Beaufort gyre, and negative sea level trends over the 10-year period are observed in the East Siberian slope region, which may be related to the local freshwater decrease observed by other studies. Our regional polar sea level products are limited by current understanding of the sea-ice lead measurements, and homogenization of these polar products with global sea level products needs to be tackled.

The Loop Current is the main mesoscale feature of the Gulf of Mexico oceanic circulation. With peak velocities above 1.5 m s–1, the Loop Current and its mesoscale eddies are of interest to fisheries, hurricane prediction and of special concern for the security of oil rig operations in the Gulf of Mexico, and therefore understanding their predictability is not only of scientific interest but also a major environmental security issue. Combining altimetric data and an eddy detection algorithm with 8 years of deep flow measurements through the Yucatan Channel, we developed a predictive model for the Loop Current extension in the following month that explains 74% of its variability. We also show that 4 clusters of velocity anomalies in the Yucatan Channel represent the Loop Current dynamics. A dipole with positive and negative anomalies towards the western side of the Channel represents the growing and retracted phases respectively, and two tripole shape clusters represent the transition phases, the one with negative anomalies in the center associated with 50% of the eddy separation events. The transition between these clusters is not equally probable, therefore adding predictability. Finally, we show that eddy separation probability begins when the Loop Current extends over 1800 km (~27.2°N), and over 2200 km of extension, eddy detachment and reattachment is more frequent than separation. These results represent a step forward towards having the best possible operational Loop Current forecast in the near future, incorporating near real-time data transmission of deep flow measurements and high resolution altimetric data.

A decade-long pronounced increase in temperatures in the Arctic resulted in a global warming hotspot over the Greenland ice sheet (GrIS). Associated changes in the cryosphere were the consequence and led to a demand for monitoring glacier changes, which are one of the major parameters to analyze the responses of the GrIS to climate change. Long-term altimetry data (e.g. ICESat, CryoSat-2, and ICESat-2) can provide elevation changes over different periods, and many methods have been developed for altimetry alone to obtain elevation changes. In this work, we provided the long-term elevation change rate data of the GrIS in three different periods using ICESat data (from February 2003 to October 2009), Cryosat-2 data (from August 2010 to October 2018) and ICESat-2 data (from October 2018 to December 2020). Optimal methods were applied to the datasets collected by three different altimeters: crossover analysis for ICESat/ICESat-2 and the surface fit method for Cryosat-2. The data revealed that the elevation change rates of the GrIS were –12.19 ± 3.81 cm/yr, –19.70 ± 3.61 cm/yr and –23.39 ± 3.06 cm/yr in the three different periods, corresponding to volume change rates of –210.20 ± 25.34 km3/yr, –339.11 ± 24.01 km3/yr and –363.33 ± 20.37 km3/yr, respectively. In general, the obtained results agree with the trends discovered by other studies that were also derived from satellite altimetry data. This dataset provides the basic data for research into the impact of climate change over the GrIS. The dataset is available at https://doi.org/10.57760/sciencedb.j00076.00121.

The dynamic optimal interpolation (DOI) method is a technique based on quasi-geostrophic dynamics for merging multi-satellite altimeter along-track observations to generate gridded absolute dynamic topography (ADT). Compared with the linear optimal interpolation (LOI) method, the DOI method can improve the accuracy of gridded ADT locally but with low computational efficiency. Consequently, considering both computational efficiency and accuracy, the DOI method is more suitable to be used only for regional applications. In this study, we propose to evaluate the suitable region for applying the DOI method based on the correlation between the absolute value of the Jacobian operator of the geostrophic stream function and the improvement achieved by the DOI method. After verifying the LOI and DOI methods, the suitable region was investigated in three typical areas: the Gulf Stream (25°N-50°N, 55°W-80°W), the Japanese Kuroshio (25°N-45°N, 135°E−155°E), and the South China Sea (5°N-25°N, 100°E−125°E). We propose to use the DOI method only in regions outside the equatorial region and where the absolute value of the Jacobian operator of the geostrophic stream function is higher than 1 × 10−11.

Satellite altimetry observations are checked against in situ measurements to assess the capability of this remote sensing technique to describe the surface circulation in the Ligurian Sea. CTD profiles were collected during five oceanographic campaigns from 2017 and 2024 along the satellite track Jason 044, crossing the Ligurian Sea from the Corsica Channel to the coast close to Genoa. Eight months of ADCP surface currents from a fixed mooring were also used for the comparison with altimetric-derived geostrophic currents. Moreover, the possible contribution of ICESat-2 to oceanographic studies in the area is investigated. Altimetric measurements successfully reproduce the basic circulation features of the region and their seasonal variation and, despite the different nature of the used systems, can be well integrated with in situ observations. The results from the direct comparison with daily mean values of ADCP surface currents reported an RMSD of the same order as the standard deviation, which is consistent with similar investigations in other areas but evidences the need to define more appropriate metrics and methods.

The ocean circulation is typically constrained in operational analysis and forecasting systems through the assimilation of sea level anomaly (SLA) retrievals from satellite altimetry. This approach has limited benefits in the Arctic Ocean and surrounding seas due to data gaps caused by sea ice coverage. Moreover, assimilation of SLA in seasonally ice-free regions may be negatively affected by the quality of the Mean Sea Surface (MSS) used to derive the SLA. Here, we use the Regional Ice Ocean Prediction System (RIOPS) to investigate the impact of assimilating Absolute Dynamic Topography (ADT) fields on the circulation in the Arctic Ocean. This approach avoids the use of a MSS and additionally provides information on sea level in ice covered regions using measurements across leads (openings) in the sea ice. RIOPS uses a coupled ice-ocean model on a 3-4 km grid-resolution pan-Arctic domain together with a multi-variate reduced-order Kalman Filter. The system assimilates satellite altimetry and sea surface temperature together with in situ profile observations. The background error is modified to match the spectral characteristics of the ADT fields, which contain less energy at small scales than traditional SLA due to filtering applied to reduce noise originating in the geoid product used. A series of four-year reanalyses demonstrate significant reductions in innovation statistics with important impacts across the Arctic Ocean. Results suggest that the assimilation of ADT can improve circulation and sea ice drift in the Arctic Ocean, and intensify volume transports through key Arctic gateways and resulting exchanges with the Atlantic Ocean. A reanalysis with a modified Mean Dynamic Topography (MDT) is able to reproduce many of the benefits of the ADT but does not capture the enhanced transports. Assimilation of SLA observations from leads in the sea ice appears to degrade several circulation features; however, these results may be sensitive to errors in MDT. This study highlights the large uncertainties that exist in present operational ocean forecasting systems for the Arctic Ocean due to the relative paucity and reduced quality of observations compared to icefree areas of the Global Ocean. Moreover, this underscores the need for dedicated and focused efforts to address this critical gap in the Global Ocean Observing System. [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]

Sentinel-3 is the first satellite altimetry mission that operates exclusively in SAR (Synthetic Aperture Radar) mode providing an along-track spatial resolution of 300 m. The number of reliable observations close to the coast may be hampered due to complicated waveforms that are difficult to interpret or from inaccurate geophysical corrections. In order to make use of altimetry data with a better spatial resolution and as close to the coast as possible, several specialized altimetry products have been developed. One such product is based on the Adaptive Leading Edge Subwaveform (ALES) retracker, which aims to provide more accurate sea level observations in coastal areas. In this study, which serves as a preparatory step for the determination of an updated mean sea surface model for Norway, we have tested the performance of Sentinel-3 observations along the Norwegian coast retracked using both the ALES-retracker as well as the standard open-ocean SAR retracker (SAMOSA2). Both datasets were compared with observations from the Norwegian network of permanent and temporary tide gauges as well as with the numerical ocean model NorKyst-800 to test their temporal and spatial variability, respectively. From the validation in terms of temporal variability we found that the SAMOSA2 dataset provides more observations closer to the coast than data retracked with ALES because lower-quality observations (most of which are located inside fjords) are excluded from ALES during the retracking process. Subsequently, this leads to increased accuracy for the ALES data. In comparison to observations from tide gauges, ALES shows standard deviations of differences of 10.8 cm (permanent tide gauges) and 14.2 cm (temporary tide gauges) while the original Sentinel-3 data show standard deviations of differences of 18.8 cm (permanent) and 17.8 cm (temporary). Regarding spatial variability, we found that the performance of these two datasets depends on a chosen area for investigation. Compared to a group of tide gauges towards the open sea, ALES outperforms the original dataset, which is possibly linked to the many bright-target radar echoes in this area. For the tide gauge group in the fjords and at permanent tide gauges, however, the original dataset outperforms the ALES dataset, likely due to the sparsity of observations in the latter dataset. Centered root-mean-square differences (RMSDs) to the tide gauges range between 4.0 cm and 7.0 cm for the ALES dataset, and between 3.6 cm and 7.0 cm for the original dataset, depending on the tide gauge group considered. Compared to NorKyst-800 over its whole domain, both datasets give an RMSD of 7.2 cm, while in a coastal subarea, the ALES dataset and the original dataset give RMSDs of 6.4 cm and 5.8 cm, respectively. A future updated coastal MSS for Norway could rely on a combination of the two datasets in an optimal interpolation scheme taking the external quality measures obtained in the present study into account. [ABSTRACT FROM AUTHOR]