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An accurate knowledge of the ocean mean dynamic topography (MDT) is mandatory for the optimal use of altimetric data, including their assimilation into operational ocean forecasting systems. A new global 1/4° resolution MDT was computed for the 1993–1999 time period with improved data and methodology compared to the previous RIO05 MDT field. First, a large‐scale MDT is obtained from the CLS01 altimetric Mean Sea Surface and a recent geoid model computed from 4.5 years of GRACE (Gravity Recovery and Climate Experiment) data. Altimetric sea level anomalies and in situ measurements are then combined to compute synthetic estimates of the MDT and the corresponding mean currents. While the RIO05 MDT was based on 10 years of in situ dynamic heights and drifting buoy velocities, the new field benefits from an enlarged data set of in situ measurements ranging from 1993 to 2008 and includes all hydrological profiles from the Argo array. Moreover, the processing of the in situ data has been updated. A new Ekman model was developed to extract the geostrophic velocity component from the drifting buoy measurements. The handling of hydrologic measurements has also been revisited. Compared to the previous RIO05 solution, the new global MDT resolves much stronger gradients in western boundary currents, with mean velocities being doubled in some places. Moreover, in comparison to several other recent MDT estimates, we find that the new CNES‐CLS09 MDT is in better agreement with independent in situ observations. Key Points Computation of a new mean dynamic topography Development of a new Ekman model Optimal filtering of MSS‐Geoid

Absolute dynamic topography (ADT) obtained from satellite altimeter data mapping is widely used in marine environment monitoring and research. Traditional numerical ADT prediction models exhibit high computational demands and low operational efficiency. This study proposes a deep learning framework integrating U‐Net architecture with a self‐attention convolutional long short‐term memory network (SA‐ConvLSTM) to develop a high‐precision ADT forecasting model for the South China Sea. The approach utilizes 0.08° high resolution multi‐source satellite data. Training optimization incorporating teacher forcing and scheduled sampling enhanced model capability in representing complex ocean dynamics. The SA‐ConvLSTM is shown to outperform the traditional ConvLSTM model and several existing models in terms of both forecast accuracy and computational efficiency. This framework is demonstrated significant potential for high‐resolution marine forecasting and disaster early warning systems, offering an efficient alternative to traditional numerical models for regional ocean dynamic monitoring.

Sea level and sea surface temperature inter-annual variability and trends in the Mediterranean Sea were investigated during the period 1993–2017. These were carried out using gridded absolute dynamic topography from satellite altimetry, tide gauge (TG) time series from 25 stations and gridded sea surface temperature (SST) from advanced very-high-resolution radiometer (AVHRR) data. The coastal TG data were used to verify the satellite derived sea level. Moreover, the contributions of atmospheric pressure and North Atlantic Oscillation (NAO) to sea level changes were also examined. The results revealed that the Mediterranean Sea exhibits inter-annual spatiotemporal coherent variability in both sea level and SST. The spatial variability in sea level is more significant over the Adriatic and Aegean Seas, most of the Levantine basin, and along the Tunisian shelf. Marked spatial variability in SST occurs over the central part of the Mediterranean Sea with maximum amplitude in the Tyrrhenian Sea. The highest temporal variability of sea level and SST was found in 2010 and 2003, respectively. The inter-annual variability of sea level and SST accounts for about 32% and 3% of the total variance of sea level and SST, respectively. An analysis of sea level anomaly reveled large negative values during the extended winter of 2011–2012, which may be attributed to the strong positive phase of NAO index. Satellite altimetry indicated a significant positive sea level trend of 2.7 ± 0.41 mm/year together with a significant warming of 0.036 ± 0.003 °C/year over the whole Mediterranean Sea for the period 1993–2017.

The direct method of vertical datum unification requires estimates of the ocean’s mean dynamic topography (MDT) at tide gauges, which can be sourced from either geodetic or oceanographic approaches. To assess the suitability of different types of MDT for this purpose, we evaluate 13 physics-based numerical ocean models and six MDTs computed from observed geodetic and/or ocean data at 32 tide gauges around the Australian coast. We focus on the viability of numerical ocean models for vertical datum unification, classifying the 13 ocean models used as either independent (do not contain assimilated geodetic data) or non-independent (do contain assimilated geodetic data). We find that the independent and non-independent ocean models deliver similar results. Maximum differences among ocean models and geodetic MDTs reach >150 mm at several Australian tide gauges and are considered anomalous at the 99% confidence level. These differences appear to be of geodetic origin, but without additional independent information, or formal error estimates for each model, some of these errors remain inseparable. Our results imply that some ocean models have standard deviations of differences with other MDTs (using geodetic and/or ocean observations) at Australian tide gauges, and with levelling between some Australian tide gauges, of ∼ ± 50 mm . This indicates that they should be considered as an alternative to geodetic MDTs for the direct unification of vertical datums. They can also be used as diagnostics for errors in geodetic MDT in coastal zones, but the inseparability problem remains, where the error cannot be discriminated between the geoid model or altimeter-derived mean sea surface.

This paper combines gravity data collected from airborne, shipborne and terrestrial surveys and those derived from satellite altimetry to determine a high-resolution gravimetric and hybrid geoid model (on a 30” × 30″ grid) in and around Taiwan. Some 6000 new land gravity values at a 0.03-mGal precision make a notable contribution to the geoid modeling. Shipborne gravity data in waters 20 km offshore Taiwan were collected to improve the coastal geoid precision. In a circular area of 50 km around each of the five major tide gauges in Taiwan, gravity data were measured to improve vertical datum connections between Taiwan and its four offshore islands. Height anomalies were computed first and then converted to geoid heights. At > 2000 benchmarks, we obtained measured geoid heights to assess the gravimetric-only geoid and to create a hybrid geoid. Our assessments and formal errors from least-squares collocation indicate few cm of standard deviations for both geoid models, but the gravimetric geoid has mean differences of up to 20 cm with the measured geoidal heights. The hybrid geoid is used in RTK-VBS orthometric heighting, achieving a 5-cm precision. The gravimetric geoid is used to determine the relative differences in the ocean’s mean dynamic topography (MDT) between Taiwan and the four offshore islands, which are also compared with those from oceanic and altimetric methods for estimating MDT. Differences in MDT help to identify 41.7 cm and 54.1 cm offsets in the current vertical datums of Penghu and Lanyu islands. In a low-lying, flood-prone region of southern Taiwan, the hybrid geoid improves LiDAR mapping of sub-zero elevation zones by 20 cm, corresponding to 70 years of sea level rise at an assumed rate of 0.286 cm/yr.

Current feedback affects surface motions and the numerical experiments presented in this paper highlight its importance when modeling the Gulf Stream. This is not a new notion, but its implementation in the high-resolution 1/50° North and Equatorial Atlantic HYCOM model configuration not only allows us to quantify its impact on the Gulf Stream pathway and variability via detailed comparisons to in-situ and altimetry data, but also to evaluate the latest mean dynamic topography derived from combining altimeter and satellite gravity data, drifters, and hydrological profiles. Introduction of the current feedback induces an “eddy-killing” effect that can reduce the level of eddy kinetic energy (EKE) in the model by as much as 30%, but this drop in EKE can also be compensated by decreasing the model’s explicit viscosity accordingly. The current feedback is most effective at damping energy at scales above 50–60 km while the reduction in explicit viscosity leads to an increase in small-scale energy. Addition of the current feedback also does result in a much more realistic distribution of the sea surface height variability and the resulting mean field. The detailed comparison of the model results to altimeter data and in-situ measurements leads us to state that the latest mean dynamic topography from CNES-CLS underestimates the maximum Gulf Stream velocity by approximately 10% and that the representation of the shelf circulation may be underestimated.

With the improvements in the density and quality of satellite altimetry data, a high-precision and high-resolution mean sea surface model containing abundant information regarding a marine gravity field can be calculated from long-time series multi-satellite altimeter data. Therefore, in this study, a method was proposed for determining marine gravity anomalies from a mean sea surface model. Taking the Gulf of Mexico (15°–32°N, 80°–100°W) as the study area and using a removal-recovery method, the residual gridded deflections of the vertical (DOVs) are calculated by combining the mean sea surface, mean dynamic topography, and XGM2019e_2159 geoid, and then using the inverse Vening-Meinesz method to determine the residual marine gravity anomalies from the residual gridded DOVs. Finally, residual gravity anomalies are added to the XGM2019e_2159 gravity anomalies to derive marine gravity anomaly models. In this study, the marine gravity anomalies were estimated with mean sea surface models CNES_CLS15MSS, DTU21MSS, and SDUST2020MSS and the mean dynamic topography models CNES_CLS18MDT and DTU22MDT. The accuracy of the marine gravity anomalies derived by the mean sea surface model was assessed based on ship-borne gravity data. The results show that the difference between the gravity anomalies derived by DTU21MSS and CNES_CLS18MDT and those of the ship-borne gravity data is optimal. With an increase in the distance from the coast, the difference between the gravity anomalies derived by mean sea surface models and ship-borne gravity data gradually decreases. The accuracy of the difference between the gravity anomalies derived by mean sea surface models and those from ship-borne gravity data are optimal at a depth of 3–4 km. The accuracy of the gravity anomalies derived by the mean sea surface model is high.

The spatial distribution and seasonal variability of mesoscale eddies in the Sea of Japan have been investigated based on the regional database created from the AVISO Mesoscale Eddies Trajectory Atlas (1993–2020). The database contains information about the trajectories and parameters of mesoscale eddies in the Sea of Japan. The eddy detection method is based on the analysis of altimetric maps of absolute dynamic topography. A total of 578 eddies with a lifetime of more than 90 days have been identified (273 anticyclonic and 305 cyclonic). The average lifetime of eddies is 202 days for anticyclonic and 143 days for cyclonic and mean radius of 58 km for anticyclonic and 61 km for cyclonic. The mean speed of anticyclones and cyclones along their trajectories is 2.8 and 3.7 cm/s; the mean orbital velocities of geostrophic currents are 19.0 and 15.1 cm/s, respectively. The maximum number of cases of formation and destruction of anticyclones falls in July–September during the period with high values of water inflow through the Korea Strait. Most of the cyclonic eddies are generated between January and June and decay during the cold half of the year (October–March). A joint analysis of maps of the mean surface circulation in the Sea of Japan (satellite altimetry data) and the spatial distribution of mesoscale eddy shows that the stable eddies of the Sea of Japan are associated with the quasi-stationary meanders of the East Korea East Korea Warm Curent, Subpolar Front, and Tsushima current. The position of meanders is mainly determined by the interaction of the currents with the bottom topography.

Satellite altimeters provide continuous information of the sea level variability and mesoscale processes for the global ocean. For estimating the sea level above the geoid and monitoring the full ocean dynamics from altimeters measurements, a key reference surface is needed: The Mean Dynamic Topography (MDT). However, in coastal areas, where, in situ measurements are sparse and the typical scales of the motion are generally smaller than in the deep ocean, the global MDT solutions are less accurate than in the open ocean, even if significant improvement has been done in the past years. An opportunity to fill in this gap has arisen with the growing availability of long time-series of high-resolution HF radar surface velocity measurements in some areas, such as the south-eastern Bay of Biscay. The prerequisite for the computation of a coastal MDT, using the newly available data of surface velocities, was to obtain a robust methodology to remove the ageostrophic signal from the HF radar measurements, in coherence with the scales resolved by the altimetry. To that end, we first filtered out the tidal and inertial motions, and then, we developed and tested a method that removed the Ekman component and the remaining divergent part of the flow. A regional high-resolution hindcast simulation was used to assess the method. Then, the processed HF radar geostrophic velocities were used in synergy with additional in situ data, altimetry, and gravimetry to compute a new coastal MDT, which shows significant improvement compared with the global MDT. This study showcases the benefit of combining satellite data with continuous, high-frequency, and synoptic in situ velocity data from coastal radar measurements; taking advantage of the different scales resolved by each of the measuring systems. The integrated analysis of in situ observations, satellite data, and numerical simulations has provided a further step in the understanding of the local ocean processes, and the new MDT a basis for more reliable monitoring of the study area. Recommendations for the replicability of the methodology in other coastal areas are also provided. Finally, the methods developed in this study and the more accurate regional MDT could benefit present and future high-resolution altimetric missions.

Mean Dynamic Ocean Topography (MDT) is the difference between the time‐averaged sea surface height and the geoid. Combining sea level and geoid measurements, which are both attained primarily by satellite, is complicated by ocean variability and differences in resolved spatial scales. Accurate knowledge of the MDT is particularly difficult in the Southern Ocean as this region is characterized by high temporal variability, relatively short spatial scales, and a lack of in situ gravity observations. In this study, four recent Southern Ocean MDT products are evaluated along with an MDT diagnosed from a Southern Ocean state estimate. MDT products differ in some locations by more than the nominal error bars. Attempts to decrease this discrepancy by accounting for temporal differences in the time period each product represents were unsuccessful, likely due to issues regarding resolved spatial scales. The mean mass transport of the Antarctic Circumpolar Current (ACC) system can be determined by combining the MDT products with climatological ocean density fields. On average, MDT products predict higher ACC transports than inferred from observations. More importantly, the MDT products imply an unrealistic lack of mass conservation that cannot be explained by the a priori uncertainties. MDT estimates can possibly be improved by accounting for an ocean mass balance constraint. Key Points MDT products differ by more than their nominal errors in some locations MDT products imply an unrealistic lack of mass conservation MDT products predict higher ACC transports than inferred from observations