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.

Satellite-based radar altimetry enables the long-term and global monitoring of inland water bodies. Recent progress of these altimeters concerning the tracking and acquisition mode allows to monitor an increasing number of water bodies, including lakes of small size or located in a complex orograhpy environment. As a consequence of these more demanding situations, the current operational radar processing techniques need to get improved in order to provide accurate water level retrievals. A numerical processing technique that simulates the satellite-observed scene was proposed in [1], taking into account all these challenges. In this work, the performance of such processing technique is assessed from Sentinel-3 mission data. It concerns 1000 lakes and reservoirs worldwide with a great variety of situations, looking for the current limits and potential future improvements, including about thirty water bodies with publicly available in-situ measurements allowing to determine the current accuracy attained.

Access to fresh water is a key issue for the next decades in the context of global warming. The water level of lakes is a fundamental variable that needs to be monitored for this purpose. The radar altimetry constellation brings a worldwide means to this question. Recent advances in radar altimeter onboard tracking modes have allowed monitoring thousands of lakes and rivers. Now, measurements are widely available with better resolution: it is time to drastically improve the processing. The altimetry waveforms over lakes are difficult to analyze and very different from the ocean ones. We face a large variety of signals due to surface roughness, lake geometry, and environment. The inversion process, named retracking, shall be able to describe all these components. We propose here a retracking based on physical simulations taking as inputs the lake contour and the instrument characteristics. Fitting the simulation on the waveforms gives the water surface height. The algorithm has been tested on the Sentinel-3A and Sentinel-3B time series over Occitan reservoirs (France) and Swiss lakes and compared toin situreferences. Over small Occitan reservoirs (few ha to few km2), the unbiased root-mean-square error (ub-RMSE) is better than 14 cm. Over the medium-size Swiss lakes, the ub-RMSE is better than 10 cm for most of them.

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.

Altimetry missions provide very valuable measurements on hydrological bodies, although they have initially been built for ocean topography. The extension of their acquisition modes provides tens of thousands of lake and river observations thanks to recent OLTC table upgrades. The inversion of the waveforms is yet tricky because of mixed soil/water response, highly variable dynamics and surface roughness variations. In this paper, a physical retracking based on a priori simulation is proposed for Water Surface Height (WSH) estimation over lakes. The method is applied on Sentinel-3 SAR data. The results are illustrated and discussed over the Constance lake which is covered by three S3 tracks. Consistent estimations are obtained between the three with an unbiased RMSE better than 6cm. Extensive validation over Swiss lakes (19 tracks) has also been made leading to a median unbiased RMSE of 6cm.

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 accuracy of sea surface parameters retrieved from altimeter missions is predominantly governed by the choice of the so-called “retracking” algorithm, i.e., the model and inversion method implemented to obtain the surface parameters from the backscattered waveform. For continuity reasons, the choice of space agencies is usually to apply the same retracker from one satellite mission to the other to ensure long-time homogeneous series. In this article, taking the opportunity of a new configuration of the nadir pointing measurements onboard the recently launched China France Oceanography Satellite (CFOSAT) with the Surface Waves Investigation and Monitoring (SWIM) instrument (Hauseret al.,2020), the retracking method was upgraded, by implementing a novel algorithm, called “Adaptive” retracker. It combines the improvements brought by Poissonet al.,(2018) for the estimation of surface parameters from peaked waveforms over sea ice, improvements in the way the instrumental characteristics are considered in the model (mispointing, point target response) and a more accurate consideration of speckle statistics. In this article, we first show from simulations carried out in the instrumental configuration of SWIM that the Adaptive algorithm has better accuracy and performance than the classical MLE4 algorithm. Then, the geophysical parameters obtained with real data from SWIM are analyzed with comparisons to reference data sets (model and products from altimeters). We show that this new algorithm has several benefits with respect to the classical MLE4 method: no need of lookup tables to correct biases, significant noise reduction on all geophysical variables especially the significant wave height, and performance of inversion over a large set of echo shapes, resulting from standard oceanic scenes as well as highly specular conditions such as over bloom or sea ice.

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.

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.

Delay/Doppler altimetry (DDA) aims at reducing the measurement noise and increasing the along-track resolution in comparison with conventional pulse-limited altimetry. In a previous paper, we have proposed a semi-analytical model for DDA, which considers some simplifications as the absence of mispointing antenna. This paper first proposes a new analytical expression for the flat surface impulse response (FSIR), considering antenna mispointing angles, a circular antenna pattern, no vertical speed effect, and uniform scattering. The 2-D delay/Doppler map is then obtained by a numerical computation of the convolution between the proposed analytical function, the probability density function of the heights of the specular scatterers, and the time/frequency point target response of the radar. The approximations used to obtain the semi-analytical model are analyzed, and the associated errors are quantified by analytical bounds for these errors. The second contribution of this paper concerns the estimation of the parameters associated with the multilook semi-analytical model. Two estimation strategies based on the least squares procedure are proposed. The proposed model and algorithms are validated on both synthetic and real waveforms. The obtained results are very promising and show the accuracy of this generalized model with respect to the previous model assuming zero antenna mispointing.

This paper introduces a new model for delay/Doppler altimetry, taking into account the effect of antenna mispointing. After defining the proposed model, the effect of the antenna mispointing on the altimetric waveform is analyzed as a function of along-track and across-track angles. Two least squares approaches are investigated for estimating the parameters associated with the proposed model. The first algorithm estimates four parameters including the across-track mispointing (which affects the echo's shape). The second algorithm uses the mispointing angles provided by the star-trackers and estimates the three remaining parameters. The proposed model and algorithms are validated via simulations conducted on both synthetic and real data.

The concept of delay/Doppler (DD) altimetry (DDA) has been under study since the mid-1990s, aiming at reducing the measurement noise and increasing the along-track resolution in comparison with the conventional pulse-limited altimetry. This paper introduces a new model for the mean backscattered power waveform acquired by a radar altimeter operating in synthetic aperture radar mode, as well as an associated least squares (LS) estimation algorithm. As in conventional altimetry (CA), the mean power can be expressed as the convolution of three terms: the flat surface impulse response (FSIR), the probability density function of the heights of the specular scatterers, and the time/frequency point target response of the radar. An important contribution of this paper is to derive an analytical formula for the FSIR associated with DDA. This analytical formula is obtained for a circular antenna pattern, no mispointing, no vertical speed effect, and a uniform scattering. The double convolution defining the mean echo power can then be computed numerically, resulting in a 2-D semi-analytical model called the DD map (DDM). This DDM depends on three altimetric parameters: the epoch, the sea surface wave height, and the amplitude. A multi-look model is obtained by summing all the reflected echoes from the same along-track surface location of interest after applying appropriate delay compensation (range migration) to align the DDM on the same reference. The second contribution of this paper concerns the estimation of the parameters associated with the multi-look semi-analytical model. An LS approach is investigated by means of the Levenberg-Marquardt algorithm. Simulations conducted on simulated altimetric waveforms allow the performance of the proposed estimation algorithm to be appreciated. The analysis of Cryosat-2 waveforms shows an improvement in parameter estimation when compared to the CA.

Much attention has been recently devoted to the analysis of coastal altimetric waveforms. When approaching the coast, altimetric waveforms are sometimes corrupted by peaks caused by high reflective areas inside the illuminated land surfaces or by the modification of the sea state close to the shoreline. This paper introduces a new parametric model for these peaky altimetric waveforms. This model assumes that the received altimetric waveform is the sum of a Brown echo and an asymmetric Gaussian peak. The asymmetric Gaussian peak is parameterized by a location, an amplitude, a width, and an asymmetry coefficient. A maximum-likelihood estimator is studied to estimate the Brown plus peak model parameters. The Cramér-Rao lower bounds of the model parameters are then derived providing minimum variances for any unbiased estimator, i.e., a reference in terms of estimation error. The performance of the proposed model and the resulting estimation strategy are evaluated via many simulations conducted on synthetic and real data. Results obtained in this paper show that the proposed model can be used to retrack efficiently standard oceanic Brown echoes as well as coastal echoes corrupted by symmetric or asymmetric Gaussian peaks. Thus, the Brown with Gaussian peak model is useful for analyzing altimetric measurements closer to the coast.