Satellite radar altimetry has been used for over 30 years to measure Sea Surface Height (SSH) variations to build records of Essential Climate Variables like the Mean Sea Level (MSL) for a robust assessment of climate change. A key step of the data processing towards this goal is the retracking, that is, the statistical analysis of the radar waveforms to estimate the geophysical parameters. For a robust and optimal estimation, retracking algorithms should account for a reliable waveform model, the time-varying instrumental Point Target Response (PTR), and an accurate description of the waveform noise. However, this is not the case for the operational retracking solutions implemented in the ground segments, which specifically make use of an unweighted estimator, therefore not accounting for the waveform speckle noise. In this paper we present a novel computationally efficient retracking solution for Ku-band Low Resolution Mode (LRM) data that accounts for both, the in-flight PTR and a realistic waveform noise through a weighted estimator defined to be statistically equivalent to a Maximum Likelihood estimator.We consider two waveform models: the Adaptive model and the numerical Brown model, for a consistent comparison with operational retracking solutions. We focus on the current reference mission, Sentinel-6 MF, for which an accurate noise characterization is crucial to account for the pulse-to-pulse correlations resulting from the higher Pulse Repetition Frequency (PRF) compared to conventional configurations. We demonstrate that the novel retracking solution is optimal, providing with parameter uncertainties compatible with the Cramer-Rao bounds of minimum variance, and unbiased, while a bias up to 1 cm in the epoch estimation and sub-optimality for all parameters is found for the unweighted solutions. We validated the algorithm on realistic simulations and applied it to one cycle of Sentinel-6MF LR 20 Hz data, demonstrating significant improvements in the precision of estimated parameter: ∼60% for Significant Wave Height (SWH), ∼12% for the epoch, and ∼50% for σ0compared to current operational solutions. We report for the first time geophysical parameter uncertainties consistently computed at 20 Hz as output of the retracker. We also introduce an innovative Bayesian approach for analyzing waveform data to complement current solutions, providing with a robust method for the estimation of the parameter uncertainties and correlations. Finally, we perform a comprehensive analysis of parameter correlations, on simulations and data, compared to theoretical expectation based on Fisher matrix analysis, demonstrating the importance of optimality for a correct estimation. Specifically, we show that the unweighted, suboptimal retracking solution significantly underestimates the epoch-SWH correlation, by a factor of ∼1.5 in the correlation coefficients, compared to the optimal solution and theoretical expectations. This could significantly impact the estimation of corrections such as Sea State Bias (SSB) and High-Frequency Adjustment (HFA), warranting further assessment. Overall, optimal retracking solutions should be considered to derive robust long-term sea level records for climate research using past, current, and future altimetry missions.

SWOT is an innovative altimetry mission launched by NASA and CNES in December 2022. The data acquired by the HR mode of the principal instrument KaRIn enable precise estimation of elevation, area and related parameters for continental water surfaces, globally and repeatedly. In this article we briefly present the different science data products, with real-world examples and some preliminary results on performance. The final presentation will report on the global performance assessments which are due for the SWOT Science Validation Meeting in June 2024.

Monitoring the dynamics and surface conditions of lakes is essential for the understanding of climate change dynamics. Lake water level is one of the variables that needs a particular vigilance, requiring a global and consistent monitoring that can be achieved by spaceborne remote sensing. Satellite radar altimetry has been widely used in the monitoring of inland waters in the past decades, with recent great improvements in the spatial resolution through the new generation of Synthetic Aperture Radar (SAR) altimeters. However, current radar altimetry constellations limits the space-time sampling necessary for a systematic and regular mapping of lakes. GNSS-Reflectometry (GNSS-R) could provide complementary observations to densify the spatio-temporal coverage, allowing hydrologists to access to finer details on the lake surface evolution. In particular, grazing GNSS-R broaden the use of opportunistic GNSS signals due to the smaller elevation angles of the reflecting signals. In this letter we address this issue by comparing the altimetry profiles over Great Lakes of grazing GNSS-R data provided by Spire constellation satellites and SAR altimeter data provided by Sentinel-3 constellation satellites, as a first approach in preparation of inter-techniques hydrology lake water level products. This letter confirms the advantages of fusing observations from both types of remote sensing techniques provided that accurate regional geoid model are available. Furthermore, GNSS-R data could also provide an independent lake water level information to validate the radar altimetry measurements over sites which are not equipped with ground means.

Poseidon-4 is a dual frequency redundant radar altimeter, embarked on board the Sentinel-6 Michael Freilich European Commission Copernicus Programme satellite. In this paper, we assess Poseidon-4 main instrumental improvements and performances, with the presentation of the more important outcomes from the In-Flight internal calibration modes and from an external calibration analysis over a transponder. The instrumental performances of the radar altimeter are excellent for both radar chain sides: Poseidon-4 delivers a range/azimuth instrument impulse response with the highest quality and fidelity in the era of space-borne radar altimetry and its thermal noise response is almost just random noise. A power decay of the level of the transmitted power in Ku-Band has been detected both for the nominal and for redundant sides, which is larger than expected though will not violate the requirement of the minimum signal-to-noise ratio over ocean at the end of the satellite design lifetime. The innovative CAL1 ECHO CAL calibration mode allows to characterize very precisely the sensitivity of the instrument impulse response to the in-orbit temperature variations and thus correct for it in the science data as standard practice.

The purpose of this paper is to accompany the release of the Jason-3 GDR-F products delivered as part of the GDR-F reprocessing campaign and to explain its main benefits for the users of altimetry products. This reprocessing campaign has a twofold objective: improve the quality of the products and share common standards with Sentinel-6/Jason-CS. Illustrations of the different benefits for the users of altimetry products are provided.

The Delay-Doppler altimeter data processing (commonly called SAR altimetry) is a mature technology offering many advantages in marine radar applications compared to conventional altimetry. Here we describe the potential of SAR altimetry (both unfocused and Fully Focused) for detecting and measuring Internal Solitary Wave (ISW) amplitudes in deep water regions. Analysis of ISW SAR altimeter signatures in the tropical ocean off the Amazon shelf are presented, since their large amplitude ISWs are known to exist. Preliminary results of the dependence of Sea Level Anomalies (SLA) associated to ISWs with respect to the differenced mean square slope variations along the waves' signatures are presented for the first time.

The detection of sea ice leads is a prerequisite for the estimation of ice freeboard and thickness from altimeter data. The classification of altimeter waveforms is generally performed using statistical parameters on the echo power or machine learning approaches directly on the waveforms. The validation and optimization of such algorithms can be carried out using a set of reference cases provided by Earth Observation images. In this paper, we first developed a new lead detector based on Sentinel-1 (S-1) synthetic aperture radar (SAR) images. A robust and consistent methodology for the joint assessment of Altimeter and SAR leads detector is then provided. We propose to fully account for the 2-D geometric problem when comparing the 1-D altimeter track and 2-D SAR image. The surface of the lead intersecting the altimeter footprint and its distance to nadir are considered here. Based on collocated Sentinel-3 (S-3) altimeter data and S-1 images, the performance of our S-3 lead detector is fully assessed. A new parameterization is found resulting in a better tradeoff between good detection and false alarm rate. A similar analysis is performed using AltiKa altimeter data, showing enhanced performance for S-3 altimeter data acquired in Delay-Doppler mode with reduced off-nadir returns.

Since the beginning of the altimeter mission TOPEX/Poseidon (T/P), followed by Jason-1 and Jason-2 on similar orbits, and many other missions on different orbits (ERS, EnviSat, etc.), mean sea level (MSL) products became essential for the comprehension of global ocean circulation. Since early in the T/P mission, a suspicious signal, having a period of near 59 days and amplitude of roughly 5 mm, was apparent in the Global MSL record. Compared with the 4-5-mm amplitude of the annual signal, the 59-day signal has understandably attracted attention. Moreover, the same signal has been subsequently detected in Jason-1 and later in Jason-2 MSLs. In 2010, the Ocean Surface Topography Science Team (OSTST) concluded this signal as the aliasing of a higher frequency error inherited from the tide model correction: the semi-diurnal wave S2. The source of this error was mainly attributed to T/P measurements, which were assimilated in ocean tide models. When these models are used in the computation of T/P MSL, most of the error cancels. However, this error is communicated to Jason-1 and Jason-2 MSLs. In order to gather and publish the OSTST analyses on this matter, this paper first attempts to list the myriad possibilities for the puzzling 59-day error in MSL. Then, this paper goes deeper into the description of the main contributor to this list: the tide models error. Indeed, since 2010, considerable efforts have been undertaken within the ocean tide community in order to correct ocean tide S2-waves from this error, particularly in the Goddard Ocean Tide (GOT) and finite element solution (FES) latest versions. Comparing several GOT and FES versions and a pure hydrodynamic tide model, this paper assesses, quantifies, and describes a reduction of the MSL 59-day error thanks to the latest releases. These analyses also confirm that a large part of this error has its origins in the T/P mission and has contaminated ocean tide solutions and Jason-1 and Jason-2 MSLs. They also suggest that ocean tide is not the only possible vector. Jason-1 and Jason-2 MSLs contain additional 59-day error-though to a lesser extent-that may either come from the measurements themselves or from another vector.

Inspired by the synthetic aperture radar (SAR) technique, a nadir radar altimeter concept called the “Delay/Doppler altimeter” or “SAR mode altimeter” provides better precision and resolution capabilities than conventional pulse-limited altimeters (i.e., low-resolution mode). This concept was initially carried on board the CryoSat-2 satellite, then used on Sentinel-3, initially for user requirements on ice or inland water monitoring. This paper addresses geophysical parameter retrieval from Delay/Doppler altimetry over ocean surfaces. For the inversion of geophysical parameters (sea surface height, significant wave height, and backscatter coefficient), we developed an inversion method based on the numerical computation of the radar power-return equation, including instrument design features, such as the range and azimuth impulse responses. To compare this technique with respect to conventional altimetry, we also generated reduced SAR (RDSAR) measurements from the same input data. Geophysical parameter retrieval from low- and high-resolution techniques was then performed for cross-comparison, demonstrating consistency for both techniques, but with a constant 3-cm bias. The proposed processing strategy was then validated using two years of CryoSat-2 data over oceans. The SAR mode provides significant benefits for the observation of small-scale signals (below 50 km) and performs as accurately as conventional altimetry for basin or global scales. The results demonstrate what is expected from the upcoming Sentinel-3 and Sentinel-6/Jason-CS missions.

A NEW SET OF TOOLS FOR ALL ALTIMETRY USERS The field of satellite radar altimetry has matured to a point where it is now time to encourage a multimission approach and conceive an "all-altimeter" toolbox including a tutorial. Such an integrated approach and view is vital not only for assessing the current status of what offers altimeter products but also to show the system and consistency with the past. The Basic Radar Altimetry Toolbox (BRAT) is a collection of tools, tutorials and documents designed to facilitate the use of radar altimetry data for altimetry users, experienced as well as beginners, and particularly the users of the upcoming CryoSat mission. It is able to read most distributed radar altimetry data, from ERS-1 & 2, TOPEX/Poseidon, Geosat Follow-on, JASON-1, Envisat, and the future Cryosat missions, to perform some processing, data editing and statistic and to visualise the results. A version 2 is being developed with additional visualisation features such as waveform viewing. Also, a release for the MacOS is planned. As part of the Toolbox, a Radar Altimetry Tutorial gives general information about altimetry, the technique involved and its applications, as well as an overview of past, present and future missions, including information on how to access data and additional software and documentation. It also presents a series of data use cases, covering all uses of altimetry over ocean, cryosphere and land, showing the basic methods for some of the most frequent manners of using altimetry data.