The elevations of water surfaces hold important information on the earth's oceans and land surface waters. Ocean sea surface height is related to the internal change of the ocean's density and mass associated with ocean circulation and its response to climate change. The flow rates of rivers and volume changes of lakes are crucial to freshwater supplies and the hazards of floods and drought resulting from extreme weather and climate events. The Surface Water and Ocean Topography (SWOT) Mission is a new satellite using advanced radar technology to make headway in observing the variability of the elevation of water surfaces globally, providing fundamentally new information previously not available to the study of earth's waters. Here, we provide the first results of SWOT over oceans, rivers, and lakes. We demonstrate the potential of the mission to address science questions in oceanography and hydrology.

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.

The Surface Water and Ocean Topography (SWOT) mission will be affected by various sources of systematic errors, which are correlated in space and in time. Their amplitude before calibration might be as large as tens of centimeters, i.e., able to dominate the mission error budget. To reduce their magnitude, we developed so-called data-driven (or empirical) calibration algorithms. This paper provided a summary of the overall problem, and then presented the calibration framework used for SWOT, as well as the pre-launch performance simulations. We presented two complete algorithm sequences that use ocean measurements to calibrate KaRIN globally. The simple and robust Level-2 algorithm was implemented in the ground segment to control the main source of error of SWOT’s hydrology products. In contrast, the more sophisticated Level-3 (multi-mission) algorithm was developed to improve the accuracy of ocean products, as well as the one-day orbit of the SWOT mission. The Level-2 algorithm yielded a mean inland error of 3–6 cm, i.e., a margin of 25–80% (of the signal variance) with respect to the error budget requirements. The Level-3 algorithm yielded ocean residuals of 1 cm, i.e., a variance reduction of 60–80% with respect to the Level-2 algorithm.

This paper describes the demonstration of a regional high-resolution level-3 (L3) altimeter data unification and altimeter combination system (DUACS) developed with support from the French space agency (CNES). Deduced from full-rate (20 Hz to 40 Hz) level-2 (L2) altimeter measurements, this product provides sea level anomalies (SLA) and other essential physical variables at a spatial resolution of one sample every ~1 km over the North Atlantic Ocean. This allows us to resolve wavelengths from ~35 km to ~55 km depending on the altimeter considered. This was made possible by recent advances in radar altimeter processing for both synthetic aperture radar (SAR) and low-resolution-mode (LRM) measurements, as well as improvements made to different stages of the DUACS processing chain. Firstly, the new adaptive and low-resolution with range migration correction (LR-RMC) processing techniques were considered for Jason and Sentinel-3 (S3A), respectively. They significantly reduce errors at short wavelengths, and the adaptive processing also reduces possible land contamination near the coast. Next, up-to-date geophysical and environmental corrections were selected for this production. This includes specific corrections intended to reduce the measurement noise on LRM measurements and thus enhance the observability at short wavelengths. Compared with the 1 Hz product, the observable wavelengths reached with the demonstration high-resolution product are reduced by up to one third, or up to half in the northeast Atlantic region. The residual noises were optimally filtered from full-rate measurements, taking into consideration the different observing capabilities of the altimeters processed. A specific data recovery strategy was applied, significantly optimizing the data availability, both in the coastal and open ocean areas. This demonstration L3 product is thus better resolved than the conventional 1 Hz product, especially near the coast, where it is defined up to ~5 km against ~10 km for the 1 Hz version. Multi-mission cross-calibration processing was also optimized with an improved long-wavelength error (LWE) correction, leading to a better consistency between tracks, with a 9–15% reduction in SLA variance at cross-overs. The new L3 product improves the overall consistency with tide gauge measurements, with a reduction in SLA differences variance by 5 and 17% compared with the 1 Hz product from the S3A and Jason-3 (J3) measurements, respectively. Primarily intended for regional applications, this product can significantly contribute to improving high-resolution numerical model output via data assimilation. It also opens new perspectives for a better understanding of regional sea-surface dynamics, with an improved representation of the coastal currents and a refined spectral content revealing the unbalanced signal.

Nearly three years of Envisat altimetric observations over ocean are available inGeophysical Data Record (GDR) products. The quality assessment of these data is routinelyperformed at the CLS Space Oceanography Division in the frame of the CNES Segment SolAltimétrie et Orbitographie (SSALTO) and ESA French Processing and Archiving Center(F-PAC) activities. This paper presents the main results in terms of Envisat data quality:verification of data availability and validity, monitoring of the most relevant altimeter(ocean1 retracking) and radiometer parameters, assessment of the Envisat altimeter systemperformances. This includes a cross-calibration analysis of Envisat data with Jason-1, ERS-2 and T/P. Envisat data show good general quality. A good orbit quality and a low level ofnoise allow Envisat to reach the high level of accuracy of other precise missions such as T/Pand Jason-1. Some issues raised in this paper, as the gravity induced orbit errors, will besolved in the next version of GDR products. Some others, as the Envisat Mean Sea Level inthe first year, still need further investigation.