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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]

The regional sea level budget and interannual sea level changes around Taiwan and Philippines are studied using altimetry, GRACE, and in-situ hydrographic data during 1993‒2021. Results show that the average sea level trend around Taiwan and Philippines during 1993–2021 derived from the altimetric data is 3.6 ± 0.2 mm/yr. Over 2002–2021, the study shows closure of sea level budget in the eastern ocean of Taiwan and Philippines within the observed data uncertainties, and the ocean mass accounts for 88%–100% of the observed sea level rise. In contrast, the sea level budget is not closed in the western ocean of Taiwan and Philippines, probably due to the lack of complete coverage by in-situ ocean observing systems. In addition, both regional sea level anomalies and their steric component around Taiwan and Philippines exhibit pronounced interannual and decadal variabilities. The trade wind stress associated with El Niño–Southern Oscillation and Pacific Decadal Oscillation offers a compelling explanation for the interannual and decadal signals of sea level anomalies in the southern ocean of Taiwan, with negative correlations of − 0.78 to − 0.64, indicating that trade wind stress makes a negative contribution to interannual-to-decadal sea level variability. In the northwestern ocean of Taiwan, the sea level variation is strongly influenced by the local monsoon system and shallow bathymetry with an annual amplitude of 90.3 ± 2.9 mm, larger than those in other regions around Taiwan and Philippines, where ocean mass is dominant with a high correlation with the sea level (+ 0.75 to + 0.78). [ABSTRACT FROM AUTHOR]

Accurate modeling of bathymetry has a paramount importance in various marine applications, including navigation, resource exploration, and environmental studies. In this study, we present an innovative approach to enhance bathymetry modeling in the Persian Gulf and the Sea of Oman by employing data assimilation techniques with geodetic observation data. Our approach involves the integration of satellite altimetry missions, the XGM2019e gravity model, and ship-borne marine gravity data to extract the gravity anomaly. By utilizing variance component estimation (VCE), we integrate these three data sources to estimate the final gravity anomaly. Comparing ship-borne gravity anomaly control profiles with altimetry, XGM2019e and the final gravity anomaly reveals the superior accuracy of the final gravity anomaly compared to altimetry and the XGM2019e gravity model. Next, we utilize the final gravity anomaly in the Parker physical model to estimate the bathymetry. In order to modification the estimated bathymetry and achieve local calibration, we employ the 3D variational (3DVAR) data assimilation method, assimilating echo sounder observations to improve the bathymetry estimation. The assimilated bathymetry is then validated by comparing it with control points derived from echo sounder observations. The results demonstrate that data assimilation has the potential to enhance the accuracy of bathymetry estimation derived from the physical model. Following the data assimilation process in the physical model, our focus shifts to modeling the residual error between the echo sounder observations and the assimilated bathymetry. To tackle this, we propose the utilization of a Multi-Layer Perceptron (MLP) algorithm to model the residual between the assimilated model and the echo sounder observations. The results indicate that employing the MLP algorithm for residual modeling leads to improved accuracy at the control points. [ABSTRACT FROM AUTHOR]

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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]

AbstractICESat-2 has made a significant contribution to polar research, although its application in oceanography is relatively limited. The precision and resolution of its sea surface height (SSH) products are crucial for ensuring their effectiveness in oceanographic applications. Therefore, this study presents a comprehensive assessment of the precision and resolution of ICESat-2 ATL12 SSH product, utilizing Cryosat-2 and Jason-3 altimeter data and tide gauge measurements as references. First, ICESat-2 exhibits significant data gaps over open oceans, with sampling distances exceeding 5 km. However, the mean sampling distance in coastal regions is only 1.2 km. Second, the sea surface height obtained by ICESat-2 has good precision, with a standard deviation of approximately 8 cm for crossover differences with Cryosat-2. Third, there is a significant negative bias compared to Cryosat-2 and Jason-3, which can be classified into systematic and time-varying biases. The systematic bias is primarily attributable to discrepancies in geophysical corrections, whereas the time-varying bias is predominantly caused by scattering. In addition, the time-varying characteristic of the bias exert a significant influence on sea surface height, with a STD of 8–9 cm. This indicates that the precision of ATL12 SSHs is inconsistence, which should be given attention when it is used. [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]

For the period of satellite altimetry observations of 1993–2018, the zonal distribution of the linear meridional shift of the jet structure and variation in intensity of currents in the sector of the Antarctic Circumpolar Current (ACC) south of Africa (9.875° W–25.125° E) are estimated. The jet structure is understood as the alternation in the meridional direction of zones of increased and decreased values of the modulus of the absolute dynamic topography (ADT) gradient . The analysis is carried out using the procedure developed earlier and supplemented in this work, based on the calculations of linear regressions, which also includes an assessment of calculation errors. To estimate the zonal distributions, the sector was divided into meridional bands, for each of which a calculation was carried out. The optimum width of the band is estimated at 2.5° longitude. The presence of a noticeable zonal inhomogeneity in the shift of the jet structure and variations in the intensity of the currents are shown. This inhomogeneity is obviously associated with quantitative discrepancies in the calculations of these parameters with division into bands, with their subsequent averaging over the zonal series, and without division into bands. The patterns of shifts in the jet structure and variations in the intensity of currents with and without division into bands are qualitatively similar. [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]

In the past few decades, satellite altimetry has surpassed tremendous achievements in examining the mesoscale of ocean dynamics. Recently, new potential of the satellite in observing the variability of climate phenomena through atmospheric medium has been unlocked. As it has been ascertained that satellite altimetry is not only outstanding in monitoring ocean dynamics but also in observing atmospheric variability, we intuitively propose a hypothesis that satellite altimetry is reliable in monitoring Bjerknes feedback: a feedback loop that involves interactions between atmosphere and oceans. Thus, the aim of this study is to determine the capability of satellite altimetry in observing Bjerknes feedback through Precipitable Water Vapour (PWV) and Sea Level Anomaly (SLA) during the anomalous climate mode of Indian Ocean Dipole (IOD). The results signify convincing arguments as both PWV and SLA indexes are highly correlated with Dipole Mode Index (DMI), particularly in the western region of the Indian Ocean, which have correlations of 0.67 and 0.62, respectively. The correlations of PWV and SLA indexes are also significantly high: 0.73 and 0.69 in western and eastern regions, respectively. The Principal Component Analysis (PCA) results are also convincing as the spatial pattern of primary (PC1) and secondary (PC2) components of both PWV and SLA are associated with positive and negative IOD, respectively. The temporal patterns of PC1 for PWV and SLA have relatively high correlation with positive IOD. The substantially high temporal correlation (0.81) between PWV and SLA PC1 has reinforced the confidence in the capability of satellite altimetry in observing the Bjerknes feedback. [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]

The conventional ocean data assimilation process typically involves assimilating hydrographic data, such as temperature and salinity measurements, obtained from both satellites and in-situ observations. This study introduces a novel approach to enhance ocean circulation modeling by assimilating surface geostrophic currents derived from satellite altimetry data using the ensemble Kalman filter. To match the time scales for the variability in the observed surface geostrophic currents and the model currents, the current velocities from the model were low-pass filtered. The optimal cut-off period for the low-pass filter was determined to be 31 days in the East Sea. Eight sensitivity experiments were then conducted to examine the effects of observation error and low-pass filtering during the assimilation of surface geostrophic current data. Assimilation experiments with surface geostrophic current data improved surface currents but had minor negative impacts on the temperature and salinity when compared with assimilation experiments without surface geostrophic current data. Notably, the experiment with an observation error of 10 cm/s for the geostrophic current outperformed the other experiments. Surface geostrophic current assimilation improved the sea surface temperature during winter and effectively modified surface current patterns during autumn in the East Sea. Assimilating satellite-derived surface geostrophic currents in the ocean circulation model thus enhanced the accuracy of surface circulation simulation. This improvement in ocean analysis data offers significant benefits for understanding ocean climate change and for developing marine management strategies. [ABSTRACT FROM AUTHOR]

The FengYun‐3E satellite (FY‐3E) is the first to feature the GNSS Occultation Sounder II (GNOS‐II). Occultation is effective for ionosphere detection, but data variations between FY‐3E and other techniques are inevitable due to differing instruments and methodologies. Evaluating the GNOS‐II performance against other techniques is imperative. We extract ionospheric parameters—the F2 layer peak height (hmF2), F2 layer critical frequency (foF2), and Vertical Total Electron Content (VTEC)—from FY‐3E's electron density profile. We use ionosonde, Global Ionospheric Maps (GIMs), and Satellite Altimetry (SA), along with FY‐3D and COSMIC‐2 to analyze FY‐3E's performance. Additionally, we use the International Reference Ionosphere (IRI‐2020) to normalize VTEC, eliminating systematic biases due to altitude differences. Results show that FY‐3E's foF2 has high consistency with ionosonde, while hmF2 shows larger differences. However, both foF2 and hmF2 from FY‐3E, FY‐3D, and COSMIC‐2 have comparable data quality. TEC differences between FY‐3E and GIMs are greater during equinoxes and in the daytime. Significant TEC deviations are observed, particularly in low‐latitude region affected by the Equatorial Ionization Anomaly (EIA) during the daytime, with underestimation at EIA crests and overestimation at EIA troughs and around ±40° geomagnetic latitude, a phenomenon also observed when compared to SA. FY‐3D and COSMIC‐2 exhibit similar patterns, but FY‐3E shows better consistency with GIMs and SA compared to FY‐3D. Compared to FY‐3D and FY‐3E, COSMIC‐2 has fewer overestimated profiles. Furthermore, FY‐3E performs poorly in observing ionospheric structure in the EIA region but performs well in the Weddell Sea Anomaly (WSA) region, similar to FY‐3E. Plain Language Summary: The FY‐3E provides a new source of data for the study of the ionosphere, but there are inevitable errors between FY‐3E and other data. In this paper, the errors between FY‐3E and ionosonde, SA, and GIMs are investigated. In addition, FY‐3E is compared with other occultations and their performance differences are discussed. Finally, the results of the FY‐3E observation of the special structure of the ionosphere are compared with other data. The results show that there are non‐negligible differences between FY‐3E and other methods in the ionospheric observations, especially near the geomagnetic equator and in the polar regions. However, after proper processing, FY‐3E is still a valuable source of data for studying the ionosphere. Key Points: For foF2, FY‐3E correlates well with ionosonde, while the performance of hmF2 is slightly inferior to foF2, particularly in high‐latitude regionFor TEC, there are differences between FY‐3E and Global Ionospheric Maps and SA, with the most pronounced deviations between −40° and 40° geomagnetic latitudeFY‐3E demonstrates good performance in observing structures in mid‐to high‐latitude region, but poorer performance in low‐latitude region [ABSTRACT FROM AUTHOR]

Seventy‐five days of sea surface height measurements made by the Surface Water and Ocean Topography (SWOT) mission from 7 September to 21 November 2023 are used to explore SWOT's capability of observing internal tides. Mode‐1 M2 ${\mathrm{M}}_{2}$ internal tides are mapped by our updated mapping technique. SWOT‐75d represents a 75‐day instantaneous model. Nadir‐30y is constructed using 30 years of nadir altimetry data from 1993 to 2022 and represents a climate normal. The nadir altimetry data in 2023 are used for model evaluation. Despite its large errors, SWOT‐75d reveals the basic features of the global mode‐1 M2 ${\mathrm{M}}_{2}$ internal tide field, and causes positive variance reduction in regions of strong internal tides. Nadir‐30y performs better overall, but SWOT‐75d performs better in the tropical South Atlantic Ocean, the central North Pacific Ocean, and the Melanesian region. Evaluation using seasonally subsetted altimetry data reveals that M2 ${\mathrm{M}}_{2}$ internal tides have significant temporal variations. SWOT‐75d performs the best in fall, because the model is constructed using data largely in fall. SWOT‐75d has large phase anomalies, which are spatially smoothed and used to adjust the phases in Nadir‐30y. The phase‐adjusted model can better make internal tide correction for SWOT and its performance is improved by 20%. Our results demonstrate that (a) mode‐1 M2 ${\mathrm{M}}_{2}$ internal tides can be extracted from 75 days of SWOT data by our mapping technique, and (b) the instantaneous internal tide model can be used to improve internal tide correction for SWOT. Plain Language Summary: Internal tides are ubiquitous in the global ocean and have drawn great research interest in recent years. Our knowledge of internal tides has been greatly improved, thanks to more than 30 years of SSH measurements made by multiple nadir altimetry missions. However, our capability of observing internal tides is severely limited by the one‐dimensional SSH from nadir‐looking altimetry missions. The new wide‐swath SWOT mission measures two‐dimensional SSH along a 120‐km swath with a spatial resolution of 2 km. We explore SWOT's capability of observing internal tides using the recently released 75 days of SWOT data from 7 September to 21 November 2023. We demonstrate that we can extract mode‐1 M2 ${\mathrm{M}}_{2}$ internal tides from such a short data record by our mapping technique. The SWOT‐derived model performs better than a 30‐year coherent model in some regions. Its phase information can be used to improve internal tide correction for SWOT. Our work demonstrates that SWOT greatly improves our capability of observing internal tides. Key Points: Models SWOT‐75d and Nadir‐30y are constructed using 75 days of SWOT data and 30 years of nadir altimetry data in 1993–2022, respectivelyComparison and evaluation of SWOT‐75d and Nadir‐30y reveal that mode‐1 M2 ${\mathrm{M}}_{2}$ internal tides are subject to significant temporal variationsPhase anomalies of SWOT‐75d with respect to Nadir‐30y are used to improve internal tide correction for SWOT [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]

Changes in water level serve as crucial indicators of dynamic variations in lake systems, significantly impacting lake ecological environments and water resource management. This study employs data from ICESat-1, CryoSat-2, EnviSat, and ICESat-2 multi-source altimetry satellites to analyze water levels of Aksai Chin Lake, Ayagkumu Lake, Aqqikkol Lake, Jingyu Lake, Changhong Lake, and Surigh Yilganing Kol Lake on the northern slope of Kunlun Mountains. It also incorporates data on lake watershed areas, temperature, precipitation, and land use from 2003 to 2022. Quantitative analyses of lake water level changes were conducted using trend analysis, Mann-Kendall test, Pearson correlation, and other methods to explore the influencing mechanisms of these changes. The findings are as follows: (1) The accuracy of water levels derived from multiple altimetry satellites was validated against the water level dataset, showing consistent trends and passing the significance F test in all correlation analyses. (2) Over the past 20 years, water levels of the lakes, except for Surigh Yilganing Kol Lake, have shown a significant upward trend, with Changhong Lake exhibiting the highest rate of increase at 0.71 m·a-1, while Aksai Chin Lake has the lowest rate of increase at 0.29 m·a-1. (3) Climatic factors differ significantly across lake catchment areas, with temperatures showing a consistent rising trend and precipitation varying across regions. A positive correlation exists between water levels and precipitation for Aqqikkol Lake, Ayagkumu Lake, and Jingyu Lake, while water levels of typical lakes show a positive correlation with temperature, except for Surigh Yilganing Kol Lake. This study leverages data from multiple altimetry satellites to analyze lake water level changes, aiming to elucidate the hydrological variations of lakes on the northern slope of the Kunlun Mountains. The findings provide a scientific basis for the management of lake ecological environments. [ABSTRACT FROM AUTHOR]

This study investigates the influence of ocean currents on wave modeling and satellite observations using in situ wave measurements from the One Ocean Expedition 2021–2023. In January 2023, six OpenMetBuoy drifters were deployed in the Agulhas Current region. Their high immersion ratio minimized wind effects, allowing them to follow the current and return to the Indian Ocean by the Agulhas retroflection, collecting data for about 2 months. Comparing surface current velocities from both the Mercator model and Globcurrent product with drifter data reveals underestimation for velocities over 0.5ms−1 $0.5\,\mathrm{m}\,{\mathrm{s}}^{-\mathrm{1}}$ with Mercator showing greater variability. Significant wave height and Stokes drift parameters from MFWAM and ERA5 were also evaluated against drifters. Both models tend to overestimate Stokes drift more noticeable in ERA5, indicating sensitivity to wind seas. For significant wave height, both models agree well with drifter measurements with correlations of 0.90 for MFWAM and 0.83 for ERA5. However, ERA5's lack of surface current data combined with its coarse resolution (0.5° ${}^{\circ}$) lead to underestimation of wave heights exceeding 2.5 m. MFWAM products including and excluding currents exhibit root mean square errors of 0.39 and 0.45 m, respectively, when compared to drifter measurements. This confirms that neglecting currents introduces additional errors particularly in areas with sharp current gradients. Analyzing MFWAM wave spectra, including and excluding currents, reveals wave energy transfer attributed to wave‐current interactions. The spatial extent of these interactions is captured by satellite altimeters, revealing wave modulations with considerable wave height variations when waves cross eddies and the current core. Plain Language Summary: Our study explores how ocean waves interact with surface currents in the Agulhas Current region, an important western boundary current of the global ocean circulation, reaching velocities up to 3 ms−1 $\mathrm{m}\,{\mathrm{s}}^{-\mathrm{1}}$. In 2023, we deployed six drifters with the goal to assess the performance of wave models and satellite observations in this dynamic environment. We found that two commonly used ocean current products, Mercator and Globcurrent, often underestimate current speeds above 0.5ms−1 $0.5\,\mathrm{m}\,{\mathrm{s}}^{-\mathrm{1}}$ compared to the drifters. We also evaluated wave height predictions from two models: the Météo‐France Wave Model (MFWAM), which considers surface currents, and the European Center for Medium‐Range Weather Forecasts Reanalysis v5 (ERA5), which does not. Our results showed that ERA5 often underestimates waves higher than 2.5m $2.5\,\mathrm{m}$, indicating that not accurately modeling ocean conditions can lead to significant errors. Wave height comparisons between drifters and satellite altimeters revealed good agreement. Additionally, using satellite data, we showcased how currents affect wave heights, especially around swirling waters (eddies) and when waves cross the current. Overall, our research highlights the need for more work in the area of wave‐current interactions and the importance of including these processes in wave modeling using multisource data. Key Points: Drifters show Mercator and Globcurrent underestimate current speeds, a trend increasing with stronger currents and higher sea statesNeglecting current data in wave modeling leads to significant underestimation of wave heightsSatellite altimetry data reveal wave height modulations around the Agulhas Current, indicating signatures of wave‐current interactions [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 empirical formula (EF) method, which do not rely on topographic data, stands as the prevailing technique for estimating lake water storage variation (LWSV). However, for smaller lakes, the sporadic monitoring frequency of satellite altimetry fails to adequately support this method, presenting a challenge in accurately gauging LWSV. Using Lake Chahannur, a lake in China with an area smaller than 50 km2, as a case study, seven schemes based on the EF method and the Area-Volume-Height (A-V-H) curve method were designed to estimate the LWSV of this undersized lake. The efficacy and precision of each scheme were evaluated against field-measured elevations. Findings reveal that due to the limited satellite altimetry monitoring, both the EF method and the H-driven A-V-H curve schemes struggle to provide consistent and comprehensive estimations. In the A-driven A-V-H curve schemes, terrain data from SRTM DEM suffers from mask processing and substantial errors, with the former posing challenges for shrinking lakes and the latter significantly compromising estimation accuracy. While field-measured elevations boast high precision, the interpolation process leads to terrain maps lacking in detail, with site density becoming a crucial factor influencing the accuracy of LWSV estimation. The combination of terrain reconstruction and A-driven pattern emerges as the most promising, boasting high accuracy, rich detail, and significantly reduced reliance on satellite altimetry monitoring, making it particularly suitable for small lakes. Chahannur's bottom elevation ranges between 1271.71 and 1273.44 m, and the lake shows a downward trend in water volume from 1991 to 2020, with fluctuations totaling approximately 35 million m3. This study serves as a vital addition to the field of LWSV estimation, potentially broadening the scope of estimation from large-scale lakes to a wider array of global surface water bodies. [ABSTRACT FROM AUTHOR]

AbstractElevation changes are crucial input data for mass balance assessment based on satellite altimetry. However, due to the accuracy limitations of altimetry data and mass conversion models, a significant uncertainty remains in estimating the mass balance of the Antarctic ice sheet, especially in East Antarctica. The ICESat-2 photon altimetry satellite enhances the precision of ice sheet surface elevation measurements to an accuracy of 2–4 cm. This improvement is particularly beneficial for detecting subtle elevation changes in East Antarctica. The ATL11 product from ICESat-2 offers a time series of ice surface elevations across Antarctica, enabling direct calculation of elevation change rates. To evaluate the capability of the ATL11 product in accurately depicting detailed elevation changes within the local terrain, we selected the Vostok Subglacial Lake as the validation region. Our research involves comparing fitted surface elevation change rates with in-situ data, while also considering surface mass balance, wind, and surface elevation to analyze the factors contributing to small differences in elevation changes within the local lake area. This analysis aims to identify the factors contributing to the minor variations in elevation changes within the local lake area. According to our analysis, the Vostok Lake surface elevation change rate is 2.00 ± 0.77 cm yr−1 from April 2019 to June 2023, with an average period of 356 ± 81 days. The results demonstrate that the ATL11 elevation product sequence has the potential to accurately characterize subtle elevation changes and seasonal variations in the Antarctic ice sheet. [ABSTRACT FROM AUTHOR]

Lake level, area and volume are sensitive indicators of climate change. At present, many studies have focused on the interannual water balance of lakes, but lake level and area can change remarkably with seasons, especially for lakes with seasonal ice cover. Zhari Namco, a seasonal frozen lake, was selected as an example to investigate its seasonal water balance. Multi-source altimetry and Landsat data were used to obtain the seasonal lake level and area from 1992 to 2019, and seasonal lake volume variations were also estimated. The results indicated the average lake level, area and volume in autumn were the largest. The lake level, area, and volume experienced three turning points approximately in 2000, 2010, and 2016, and showed an overall increasing trend from 1992 to 2019, with slopes of 0.15 m/year, 2.17 km2/year, and 0.14 km3/year, respectively. The lake area expanded significantly in autumn, which was related to the abundant precipitation. Delay time of land surface runoff, increased temperature, and evaporation may be the reason for the low lake level and volume in summer. The precipitation was the dominant factor of water balance, which explained 62.09%, 62.43%, and 62.10% of the variations in lake level, area, and volume, respectively. [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]

The photon-counting laser altimeter on the Ice, Cloud and Land Elevation 2 (ICESat-2) satellite offers a solution for tracking the dynamic water level variations in medium and large inland lakes. We utilize the monthly ATL13 global inland water data of ICESat-2 satellite from 2018 to 2020 to estimate and analyze the water level change in Poyang Lake. The measured data from Hukou, Xingzi and Kangshan hydrological stations are used for verification and error correction, and the water level and rainfall data of each station are combined to analyze the dynamic variation of Poyang Lake water level and reveal the underlying drivers. The results show that, the annual water level of Poyang Lake varied sharply with obvious seasonal variations and an overall upward trend;the high water level period was from June to October, which peaked from July to September. The linear correlation coefficient of water levels between ICESat-2 and measured data is above 0. 846, rising to 0. 974 after error correction. The Root Mean Square Error (RMSE) is 1. 660 m, 1. 073 m, and 0. 836 m for Hukou, Xingzi, and Kangshan stations, respectively;error correction and recalculation can decrease the RMSE to 0. 663 m, 0. 659 m, and 0. 440 m for Hukou, Xingzi, and Kangshan stations, respectively, enhancing the measurement accuracy by nearly one meter. The variation of water level in Poyang Lake is highly correlated with the change of rainfall, the reduced precipitation during periods from January to February and October to December corresponds to the declining water level in dry season, while the increased rainfall from March to October corresponds to the water level rise in wet season, and the precipitation concentration period from July to September aligns with the peak of water level in Poyang Lake. [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.