In the early phase of the Pleiades program, the CNES (the French Space Agency) specified and developed a fully automatic mosaicing processing unit, in order to generate satellite image mosaics under operational conditions. This tool can automatically put each input image in a common geometry, homogenize the radiometry, and generate orthomosaics using stitching lines. As the image quality commissioning phase of Pleiades1A is on-going, this mosaicing process is being tested for the first time under operational conditions. The French newly launched high resolution satellite can acquire adjacent images for French Civil and Defense User Ground Segments. This paper presents the very firsts results of mosaicing Pleiades1A images. Beyond Pleiades’ use, our mosaicing tool can process a significant variety of images, including other satellites and airborne acquisitions, using automatically-taken or external ground control points, offering time-based image superposition, and more. This paper also presents the design of the mosaicing tool and describes the processing workflow and the additional capabilities and applications.

Surface wind speed measurements from a satellite radar altimeter are used to adjust altimeter sea level measurements via sea state bias range correction. We focus here on previously neglected ocean radar backscatter and subsequent wind speed variations due to sea surface temperature (SST) change that may impact these sea level estimates. The expected error depends on the radar operating frequency and may be significant at the Ka band (36 GHz) frequency chosen for the new Surface Water and Ocean Topography (SWOT) satellite launched in December 2022. SWOT is expected to revolutionize oceanography by providing wide-swath Ka band observations and enhanced spatial resolution compared to conventional Ku band (14 GHz) altimetry. The change to the Ka band suggests a reconsideration of SST impact on wind and sea level estimates, and we investigate this in advance of SWOT using existing long-term Ku and Ka band satellite altimeter datasets. This study finds errors up to 1.5 m/s in wind speed estimation and 1.0 cm in sea level for AltiKa altimeter data. Future SWOT data analyses may require consideration of this dependence prior to using its radar backscatter data in its sea level estimation.

The 1-day fast-sampling orbit phase of the Surface Water Ocean Topography (SWOT) satellite mission provides a unique opportunity to analyze high-frequency sea-state variability and its implications for altimeter sea state bias (SSB) model development. Time series with 1-day repeat sampling of sea-level anomaly (SLA) and SSB input parameters—comprising the significant wave height (SWH), wind speed (WS), and mean wave period (MWP)—are constructed using SWOT’s nadir altimeter data. The analyses corroborate the following key SSB modelling assumption central to empirical developments: the SLA noise due to all factors, aside from sea state change, is zero-mean. Global variance reduction tests on the SSB model’s performance using corrected SLA differences show that correction skill estimation using a specific (1D, 2D, or 3D) SSB model is unstable when using short time difference intervals ranging from 1 to 5 days, reaching a stable asymptotic limit after 5 days. It is proposed that this result is related to the temporal auto- and cross-correlations associated with the SSB model’s input parameters; the present study shows that SSB wind-wave input measurements take time (typically 1–4 days) to decorrelate in any given region. The latter finding, obtained using unprecedented high-frequency satellite data from multiple ocean basins, is shown to be consistent with estimates from an ocean wave model. The results also imply that optimal time-differencing (i.e., >4 days) should be considered when building SSB model data training sets. The SWOT altimeter data analysis of the temporal cross-correlations also permits an evaluation of the relationships between the SSB input parameters (SWH, WS, and MWP), where distinct behaviors are found in the swell- and wind-sea-dominated areas, and associated time scales are less than or on the order of 1 day. Finally, it is demonstrated that computing cross-correlations between the SLA (with and without SSB correction) and the SSB input parameters offers an additional tool for evaluating the relevance of candidate SSB input parameters, as well as for assessing the performance of SSB correction models, which, so far, mainly rely on the reduction in the variance of the differences in the SLA at crossover points.

We present the validation of the latest version F Geophysical Data Records (GDR-F) for the TOPEX/POSEIDON (T/P) altimetry satellite mission. The GDR-F products represent a major evolution with respect to the preceding version B Merged Geophysical Data Records (MGDR-B) that were released more than two decades ago. Specifically, the numerical retracking of the altimeter waveforms significantly mitigates long-standing issues in the TOPEX altimeter measurements, such as drifts and hemispherical biases in the altimeter range and significant wave height. Additionally, GDR-F incorporates updated geophysical model standards consistent with current altimeter missions, improved sea state bias corrections, end-of-mission calibration for the microwave radiometer, and refined orbit ephemeris solutions. These enhancements notably decrease the variance of the Sea Surface Height Anomaly (SSHA) measurements, with along-track SSHA variance reduced by 26 cm² compared to MGDR-B and crossover SSHA variance lowered by 1 cm². GDR-F products also demonstrate improved consistency with Jason-1 measurements during their tandem mission phase, reducing the standard deviation of differences from 6 cm to 4 cm when compared to Jason-1 GDR-E data. These results confirm that GDR-F products offer a more accurate and consistent T/P data record, enhancing the quality of long-term sea level studies and supporting inter-mission altimetry continuity.

The Surface Water and Ocean Topography (SWOT) mission was launched on 16 December 2022 to measure water levels over both open ocean and inland waters. To achieve these objectives, the SWOT Payload contains an innovative Ka-band radar interferometer, called KaRIn, completed with a nadir altimeter called POSEIDON-3C that was switched on a month after launch and a few days before KaRIn. POSEIDON-3C measurements provide a link between large-scale phenomena and high resolution. The POSEIDON-3C design is based on POSEIDON-3B, its predecessor on board JASON-3. It is also a dual-frequency radar altimeter operating in C- and Ku-bands, but with some improvements to enhance its performance. Even though it is a Low Resolution Mode altimeter, its performance over open ocean, inland waters and coastal zones are indeed excellent. This paper first describes the POSEIDON-3C design and its modes with a focus on its new features and the Digital Elevation Model that drives its open-loop tracking mode. Then, we assess the in-flight performances of the altimeter from an instrumental point of view. For that purpose, special and routine calibrations have been realized. They show the good performance and stability of the radar. In-flight assessments thus provide confidence when it comes to ensuring excellent altimeter measurement stability throughout the mission duration.

Over the past three decades, five satellites have succeeded one another on the reference orbit, building the longest continuous climate record of global sea level measurements. Its continuity is ensured thanks to tandem flights between consecutive satellites. In this paper, we demonstrate that the first satellite of the Sentinel-6 series (Sentinel-6 Michael Freilich) has enabled the detection of a processing anomaly in the Jason-1/2/3 ground segment. An inconsistency in the altimeter range reconstruction has been identified, causing its underestimation by 3.65 mm. At certain latitudes, determined by the satellite’s orbital velocity, the altimeter range shows no effect from the anomaly. For the reference orbit, the range is not affected at the poles, around the equator and, for ascending tracks, at 40° S. All Jason Geophysical Data Record (GDR) versions prior to GDR-G are impacted by the described processing anomaly. While a full reprocessing of the Jason data with the GDR-G standard is pending, this paper presents a latitudinal empirical correction to be applied to Jason datasets generated with GDR-F and earlier ground segments. This correction, to be applied on the altimeter range, is derived from one month of patched Jason-3 data and is intended for reference orbit only. Additionally, SWOT Nadir ground processing is also affected by the same processing error and has been corrected from the GDR-S2 version onward. Finally, our analysis shows a negligible impact of this processing anomaly on Jason Level-2-derived products, models and metrics.