An up‐to‐date map of the Antarctic Circumpolar Current (ACC) fronts is constructed from the latest version of mean dynamic topography (MDT) from satellite altimetry and reveals the narrowest ACC width in the Udintsev Fracture Zone (UFZ), with the strongest concentration of the three major ACC fronts within a limited distance as short as 170 km, about 40% narrower than that at Drake Passage. At 144°W, at the entrance of the UFZ, which lies between the Pacific‐Antarctic Ridge (PAR) and its eastwardly offset segment (offset PAR segment), there is a triple confluence of the Subantarctic Front, Polar Front, and Southern ACC Front . Downstream of this longitude, the Subantarctic Front progressively meanders northward over the relatively shallow offset PAR segment before channeling through the Eltanin Fracture Zone, thus diverging from the Polar Front which proceeds through the UFZ. In situ observations from two recent cruises at 144°W confirm the satellite altimetry‐derived frontal circulation in the UFZ region and yield a baroclinic transport relative to the bottom of 113 × 10⁶ m³/s, comparable to that through Drake Passage. The hydrographic sections show no Antarctic bottom water colder than 0.2 °C. Characteristics of major water masses are described, and the implications for their potential downstream modifications at Drake Passage are discussed in terms of the meridional overturning circulation across the ACC. Mesoscale eddy activity with periods shorter than 90 days is predominantly concentrated in the immediate downstream area of the offset PAR segment, suggesting a substantial poleward eddy heat flux there.

This paper presents an assessment and comparison of recent mean sea surface (MSS) models. Using a new approach and independent altimeter data sets, we quantify the major improvement of the CNES_CLS15 and the DTU15 models. We observe a reduction in the amplitude of omission errors thanks to the use of new geodetic altimeter data sets (i.e., Cryosat‐2 and Jason‐1 geodetic): they are reduced by a factor of 2 compared with previous generations (CNES_CLS11). We also quantify commission errors resulting from the leakage of residual ocean variability and altimeter noise into the MSS models. For wavelengths shorter than 250 km, the error is of the order of 1–2 cm², i.e., ∼10% to 20% of the sea level anomaly (SLA) variance. The global error of both 2015 models has similar orders of magnitude and spectral power densities, although the commission errors of the CNES_CLS15 model are about half as large as those of the DTU15 model. Its absolute error is also slightly smaller than for the DTU15 model in coastal regions and at high latitudes. Conversely, the DTU15 model produces smaller omission errors, especially in the open ocean over strong bathymetric features. More importantly, the MSS errors still have a substantial impact on altimetry products for wavelengths ranging from 30 to 100 km: the error explains ∼30% of the global SLA variance, and the error can be 2.5 times higher on uncharted ground tracks (e.g., Sentinel‐3) over rugged bathymetry.

A new mean sea surface (MSS) was determined by focusing on the accuracy provided by exact-repeat altimetric missions (ERM) and the high spatial coverage of geodetic (or drifting) missions. The goal was to obtain a high-resolution MSS that would provide centimeter-level precision. Particular attention was paid to the homogeneity of the oceanic content of this MSS, and specific processing was also carried out, particularly on the data from the geodetic missions. For instance, CryoSat-2 and SARAL/AltiKa data sampled at high frequencies were enhanced using a dedicated filtering process and corrected from oceanic variability using the results of the objective analysis of sea-level anomalies provided by DUACS multi-missions gridded sea-level anomalies fields (MSLA). Particular attention was also paid to the Arctic area by combining traditional sea-surface height (SSH) with the sea levels estimated within fractures in the ice (leads). The MSS was determined using a local least-squares collocation technique, which provided an estimation of the calibrated error. Furthermore, our technique takes into account altimetric noises, ocean-variability-correlated noises, and along-track biases, which are determined independently for each observation. Moreover, variable cross-covariance models were fitted locally for a more precise determination of the shortest wavelengths, which were shorter than 30 km. The validations performed on this new MSS showed an improvement in the finest topographic structures, with amplitudes exceeding several cm, while also continuing to refine the correction of the oceanic variability. Overall, the analysis of the precision of this new CNES_CLS 2022 MSS revealed an improvement of 40% compared to the previous model, from 2015.

Global sea surface height wave number spectra are revisited using the most recent, lower‐noise satellite altimeter missions from Saral/AltiKa and Sentinel‐3 and compared to Jason‐2 wave number spectra. Spectral preprocessing is configured to minimize the spectral slope distortion in the mesoscale wavelength range. A geographically variable wavelength range is used to calculate the spectral slopes, taking into account the regional eddy length scales based on the local Rossby radius. This dynamical wavelength range increases the spectral slope by 0.5 in middle to high latitudes, compared to a fixed wavelength range, and by ‐1.0 to 1.0 in different regions of the intertropical band. Using this dynamical wavelength range, mean sea surface height wave number spectra for these lower‐noise missions exhibit low slope values (k^‐2) in the intertropical band, values of k^‐11/3 in the midlatitudes, and reaches k^‐5 in the subpolar regions and the Antarctic circumpolar current. An important seasonality is also revealed, with mesoscale spectral slope amplitudes decreasing in winter by 0.5 to 1.5 compared to summer, for the middle‐ to high‐energy regions. A phase‐locked internal tide correction is tested but has only a small impact on the spectral slope estimates when using the dynamical wavelength range.

The India–France SARAL/AltiKa mission is the first Ka-band altimetric mission dedicated primarily to oceanography. The mission objectives were firstly the observation of the oceanic mesoscales but also global and regional sea level monitoring, including the coastal zone, data assimilation, and operational oceanography. SARAL/AltiKa proved also to be a great opportunity for inland waters applications, for observing ice sheet or icebergs, as well as for geodetic investigations. The mission ended its nominal phase after three years in orbit and began a new phase (drifting orbit) in July 2016. The objective of this paper is to highlight some of the most remarkable achievements of the SARAL/AltiKa mission in terms of scientific applications. Compared to the standard Ku-band altimetry measurements, the Ka-band provides substantial improvements in terms of spatial resolution and data accuracy. We show here that this leads to remarkable advances in terms of observation of the mesoscale and coastal ocean, waves, river water levels, ice sheets, icebergs, fine scale bathymetry features as well as for the many related applications.

An Ocean System Simulation Experiment is used to quantify the observing capability of the Surface Water and Ocean Topography (SWOT) mission and its contribution to higher-quality reconstructed sea level anomaly (SLA) fields using optimal interpolation. The paper focuses on the potential of SWOT for mesoscale observation (wavelengths larger than 100 km and time periods larger than 10 days) and its ability to replace or complement altimetry for classical mesoscale applications. For mesoscale variability, the wide swath from SWOT provides an unprecedented sampling capability. SWOT alone would enable the regional surface signal reconstruction as precisely as a four-altimeter constellation would, in regions where temporal sampling is optimum. For some specifics latitudes, where swath sampling is degraded, SWOT capabilities are reduced and show performances equivalent to the historical two-altimeter constellation. In this case, merging SWOT with the two-altimeter constellation stabilizes the global sampling and fully compensates the swath time sampling limitations. Benefits of SWOT measurement are more important within the swath. It would allow a precise local reconstruction of mesoscale structures. Errors of surface signal reconstruction within the swath represent less than 1% (SLA) to 5% (geostrophic velocities reconstruction) of the signal variance in a pessimistic roll error reduction. The errors are slightly reduced by merging swath measurements with the conventional nadir measurements.