Nadir Altimeter Research Articles

Improved Inland Water Level Estimates with Sentinel-6 Fully Focused SAR Processing: A Case Study in the Ebre River Basin

The observation of small to medium inland water targets with nadir radar altimeters is currently limited by the along-track resolution of UnFocused SAR (UFSAR) altimetry, which is approximately 300 m for Delay-Doppler processors. In this study, we analyze the benefits of the sub-meter along-track resolution provided by Fully Focused SAR (FFSAR) altimetry applied to Sentinel-6 Michael Freilich data over a collection of small to medium targets in the Ebre Basin, Spain. The obtained water level estimations over a 2-year period are compared to in situ data to evaluate the long-term accuracy of the algorithm. The proposed FFSAR altimetry methodology achieves an average MAD precision of roughly 4 cm, and allows for a full operational implementation as it can be processed in a totally unsupervised manner. The precision improvement with respect to Delay-Doppler products over the same targets is essentially attributed to the FFSAR capabilities to better filter out waveforms contaminated by off-nadir scatterers. Moreover, we evaluate the application of extended water masks, which exploit nadir–altimeter measurements where water is at nadir or up to 250 m across-track from nadir to increase the number of acquisitions while maintaining the same level of accuracy, increasing by an average of 48% the number of valid measurements per pass, while maintaining the same level of accuracy as nadir measurements over water. We thus demonstrate the potential of FFSAR altimetry to monitor the water level of small to medium inland water targets.

SWOT Cross‐Track Error Characteristics Estimated From Observations

AbstractThe Surface Water and Ocean Topography (SWOT) observatory is a complex system and contains unique systematic errors not in historical nadir altimeter observations. The errors contain expected shapes in the cross‐track direction, and functional coefficients describing the shapes are correlated in the along‐track direction. Existing nadir altimeter observations enable comparison to the SWOT observations. In the approach here, the SWOT error power spectral density in the along‐track direction indicates the SWOT residual systematic errors are larger than nadir observed signal down to scales of 1,430 km in the PIC data and 2,500 km in the PGC data. The results guide considerations in SWOT processing and error removal.

Integrating wide-swath altimetry data into Level-4 multi-mission maps

Abstract. Real-time observation of ocean surface topography is essential for various oceanographic applications. Historically, these observations have mainly relied on satellite nadir altimetry data, which were limited to observation scales greater than approximately 60 km. However, the recent launch of the wide-swath Surface Water Ocean Topography (SWOT) mission in December 2022 marks a significant advancement, enabling the two-dimensional global observation of finer-scale oceanic scales (∼ 15 km). While the direct analysis of the two-dimensional content of these swaths can provide valuable insights into ocean surface dynamics, integrating such data into mapping systems presents several challenges. This study focuses on integrating the SWOT mission into multi-mission mapping systems. Specifically, it examines the contribution of the SWOT mission to both the current nadir altimetry constellation (six/seven nadirs) and a reduced nadir altimetry constellation (three nadirs). Our study indicates that within the current nadir altimetry constellation, SWOT's impact is moderate, as existing nadir altimeters effectively constrain surface dynamics. However, in a hypothetical scenario where a reduced nadir altimetry constellation is envisioned to be operational by 2030, the significance of wide-swath data in mapping becomes more pronounced. Alternatively, we found that data-driven and dynamical mapping systems can significantly participate in refining the resolution of the multi-mission gridded products. Consequently, integrating high-resolution ocean surface topography observations with advanced mapping techniques can enhance the resolution of satellite-derived products, providing promising solutions for studying and monitoring sea-level variability at finer scales. However, to fully exploit SWOT's capabilities, future research will need to focus on innovations in data gridding and assimilation to extend mapping beyond geostrophically balanced flows.

Assessing the impact of future altimeter constellations in the Met Office global ocean forecasting system

Abstract. Satellite altimeter measurements of sea surface height (SSH) are a crucial component of current operational ocean forecasting systems. The launch of the Surface Water and Ocean Topography (SWOT) wide-swath altimeter (WiSA) mission is bringing a step change in our observing capacity with 2D mesoscale structures now able to be observed over the global ocean. Proposals are now being considered for the make-up of the future altimeter constellation. In this study we use Observing System Simulation Experiments (OSSEs) to compare the impact of additional altimeter observations from two proposed future satellite constellations. We focus on the expected impact on the Met Office operational ocean analysis and forecasting system of assimilating an observation network including either 12 nadir altimeters or 2 wide-swath altimeters. Here we show that an altimeter constellation of 12 nadir altimeters produces greater reductions in the errors for SSH, surface currents, temperature, and salinity fields compared to a constellation of 2 wide-swath altimeters. The impact is greatest in the dynamic western boundary current (WBC) regions where the nadir altimeters can reduce the SSH RMS (root-mean-square) error by half, while the wide-swath altimeter only reduces this by one-quarter. A comparison of the spatial scales resolved in daily SSH fields also highlights the superiority of the nadir constellation in our forecasting system. We also highlight the detrimental impact spatially correlated errors could have on the immediate use of wide-swath altimeter observations. However, we still achieve promising impacts from the assimilation of wide-swath altimetry, and work is ongoing to develop improved methods to account for spatially correlated observation errors within our data assimilation scheme.

Analysis of High-Frequency Sea-State Variability Using SWOT Nadir Measurements and Application to Altimeter Sea State Bias Modelling

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.

Assimilation of synthetic and real SWOT observations for the North Atlantic Ocean and Canadian east coast using the regional ice ocean prediction system

The Surface Water Ocean Topography (SWOT) mission significantly improves on the capabilities of current nadir altimeters by enabling two-dimensional mapping. Assimilating this advanced data into high-resolution models poses challenges. To address this, Observing System Simulation Experiments (OSSEs) were conducted to evaluate the effects of both simulated and actual SWOT data on the Regional Ice Ocean Prediction System (RIOPS). This study examines the OSSEs’ design, focusing on the simulated observations and assimilation systems used. The validity of the OSSE designs is confirmed by ensuring the deviations between the assimilation system and the Nature Run (NR) align with discrepancies observed between actual oceanic data and OSSE simulations. The study measures the impact of assimilating SWOT and two nadir altimeters by calculating root mean square forecast error for sea surface height (SSH), temperature, and velocities, along with performing wave-number spectra and coherence analyses of SSH errors. The inclusion of SWOT data is found to reduce RMS SSH errors by 16% and RMS velocity errors by 6% in OSSEs. The SSH error spectrum shows that the most notable improvements are for scales associated with the largest errors in the range of 200-400 km, with a 33% reduction compared to traditional data assimilation. Additionally, spectral coherence analysis shows that the limit of constrained scales is reduced from 280 km for conventional observations to 195 km when SWOT is assimilated as well. This study also represents our first attempt at assimilating early-release SWOT data. A set of Observing System (data denial) experiments using early-release SWOT measurements shows similar (but smaller) responses to OSSE experiments in a two nadir-altimeter context. In a six-altimeter constellation setup, a positive impact of SWOT is also noted, but of significantly diminished amplitude. These findings robustly advocate for the integration of SWOT observations into RIOPS and similar ocean analysis and forecasting frameworks.

Description and In-Flight Assessment of the POSEIDON-3C Altimeter of the SWOT Mission

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.

Accuracy and Resolution of SWOT Altimetry: Foundation Seamounts

AbstractWe assess the accuracy and spatial resolution of the surface water and ocean topography (SWOT) swath altimeter for deriving marine gravity anomalies. The analysis is performed at the Foundation Seamounts in the South Pacific where we developed a highly accurate gravity field by combining the long‐wavelength (>40 km) gravity field derived from previous nadir altimeters with the shorter wavelength gravity field from the seafloor topography as constrained by the ship gravity. In this region, the sea surface slope (SSS) of the ocean variability is 50–100 times smaller than the slope signal of the seamounts so can be ignored in the analysis. Each SWOT cycle can deliver SSS accurately with a standard deviation of 2.6 µrad and a spatial resolution of 14 km at typical sea state (significant wave height 4 m), with accuracy diminishing at high significant wave heights (e.g., exceeds 6 m). Averaging repeated SWOT measurements improves the accuracy and resolution. For example, we expect that averaging just 10 repeats (7 months) results in accuracy/resolution that matches the best marine gravity maps based on 230 months of nadir altimetry. With a mission lasting over a year, SWOT promises a substantial leap in marine gravity accuracy and resolution, uncovering previously uncharted details of the seafloor, including thousands of uncharted seamounts.

Inversion method of deflection of the vertical based on SWOT wide-swath altimeter data

The deflection of the vertical (DOV) is the key information in the study of ocean gravity field. However, in most areas, the precision of the prime component of DOV is significantly lower than that of the meridian component. To obtain higher accuracy and resolution of ocean gravity information, researchers have proposed a novel altimeter called the wide-swath altimeter. This altimeter allows for the simultaneous acquisition of high-precision and high-resolution two-dimensional measurements of sea surface height (SSH). In this paper, the Surface Water and Ocean Topography (SWOT) mission with a wide-swath altimeter on board is selected for research. One cycle of SWOT sea surface height data is simulated to inverse the DOV in the Arabian Sea (45°E—80°E, 0°–30°N), and the inversion results are compared with those of conventional altimeter data. The results demonstrate that the difference between the meridian and prime components derived from the inversion of SWOT wide-swath data is minimal, significantly outperforming the inversion results of conventional nadir altimeter data. The advantage of SWOT wide-swath altimeter lies in its ability to use the multi-directional geoid slope at any sea surface measurement point to invert the components in the meridian and prime directions. To investigate the impact of this advantage on inversion precision, this paper employs a method to calculate the gradient of the geoid in multiple directions to invert DOV components. The improvement effect of calculating the gradient of the geoid in multiple directions on the precision of DOV component is analyzed. It is found that the accuracy of DOV inversion has significantly improved with the increase of geodetic gradient calculation direction. In addition, the effects of various errors and grid spacing in SWOT wide sea surface height data on the precision of DOV inversion are also analyzed.

The Effect of Spatially Correlated Errors on Sea Surface Height Retrieval from SWOT Altimetry

The upcoming technology of wide-swath altimetry from space will enable monitoring the ocean surface at 4–5 times better spatial resolution and 2–3 times better accuracy than traditional nadir altimeters. This development will provide a chance to directly observe submesoscale sea surface height (SSH) variations that have a typical magnitude of a few centimeters. Taking full advantage of this opportunity requires correct treatment of the correlated SSH errors caused by uncertainties in environmental conditions beneath the satellite and in the geometry and orientation of the on-board interferometer. These observation errors are highly correlated both along and across the surface swath scanned by the satellite, and this presents a significant challenge for accurate processing. In particular, the SWOT precision matrix has off-diagonal elements that are too numerous to allow standard approaches to remain tractable. In this study, we explore the utility of a block-diagonal approximation to the SWOT precision matrix in order to reconstruct SSH variability in the region east of Greenland. An extensive set of 2dVar assimilation experiments demonstrates that the sparse approximation proposed for the precision matrix provides accurate SSH retrievals when the background-to-observation error ratio ν does not exceed 3 and significant wave height is below 2.5 m. We also quantify the range of ν and significant wave heights over which the retrieval accuracy of the exact spatially correlated SWOT error model will outperform the uncorrelated model. In particular, the estimated range is found to be substantially wider (ν<10 with significant wave heights below 8–10 m), indicating the potential benefits of further improving the accuracy of approximations for the SWOT precision matrix.

Improved global sea surface height and current maps from remote sensing and in situ observations

Abstract. We present a new gridded sea surface height and current dataset produced by combining observations from nadir altimeters and drifting buoys. This product is based on a multiscale and multivariate mapping approach that offers the possibility to improve the physical content of gridded products by combining the data from various platforms and resolving a broader spectrum of ocean surface dynamic than in the current operational mapping system. The dataset covers the entire global ocean and spans from 1 July 2016 to 30 June 2020. The multiscale approach decomposes the observed signal into different physical contributions. In the present study, we simultaneously estimate the mesoscale ocean circulations as well as part of the equatorial wave dynamics (e.g. tropical instability and Poincaré waves). The multivariate approach is able to exploit the geostrophic signature resulting from the synergy of altimetry and drifter observations. Sea-level observations in Arctic leads are also used in the merging to improve the surface circulation in this poorly mapped region. A quality assessment of this new product is proposed with regard to an operational product distributed in the Copernicus Marine Service. We show that the multiscale and multivariate mapping approach offers promising perspectives for reconstructing the ocean surface circulation: observations of leads contribute to improvement of the coverage in delivering gap-free maps in the Arctic and observations of drifters help to refine the mapping in regions of intense dynamics where the temporal sampling must be accurate enough to properly map the rapid mesoscale dynamics. Overall, the geostrophic circulation is better mapped in the new product, with mapping errors significantly reduced in regions of high variability and in the equatorial band. The resolved scales of this new product are therefore between 5 % and 10 % finer than the Copernicus product (https://doi.org/10.48670/moi-00148, Pujol et al., 2022b).

Ensemble-based 4DVarNet uncertacinty quantification for the reconstruction of sea surface height dynamics

Abstract Uncertainty quantification (UQ) plays a crucial role in data assimilation (DA) since it impacts both the quality of the reconstruction and near-future forecast. However, traditional UQ approaches are often limited in their ability to handle complex datasets and may have a large computational cost. In this paper, we present a new ensemble-based approach to extend the 4DVarNet framework, an end-to-end deep learning scheme backboned on variational DA used to estimate the mean of the state along a given DA window. We use conditional 4DVarNet simulations compliant with the available observations to estimate the 4DVarNet probability density function. Our approach enables to combine both the efficiency of 4DVarNet in terms of computational cost and validation performance with a fast and memory-saving Monte-Carlo based post-processing of the reconstruction, leading to the so-called En4DVarNet estimation of the state pdf. We demonstrate our approach in a case study involving the sea surface height: 4DVarNet is pretrained on an idealized Observation System Simulation Experiment (OSSE), then used on real-world dataset (OSE). The sampling of independent realizations of the state is made among the catalogue of model-based data used during training. To illustrate our approach, we use a nadir altimeter constellation in January 2017 and show how the uncertainties retrieved by combining 4DVarNet with the statistical properties of the training dataset lead to a relevant information providing in most cases a confidence interval compliant with the Cryosat-2 nadir alongtrack dataset kept for validation.

Contribution of a constellation of two wide-swath altimetry missions to global ocean analysis and forecasting

Abstract. Swath altimetry is likely to revolutionize our ability to monitor and forecast ocean dynamics. To meet the requirements of the EU Copernicus Marine Service, a constellation of two wide-swath altimeters is envisioned for the long-term (post-2030) evolution of the Copernicus Sentinel 3 topography mission. A series of observing system simulation experiments (OSSEs) is carried out to quantify the expected performances. The OSSEs use a state-of-the-art high-resolution (1/12∘) global ocean data assimilation system similar to the one used operationally by the Copernicus Marine Service. Flying a constellation of two wide-swath altimeters will provide a major improvement of our capabilities to monitor and forecast the oceans. Compared to the present situation with three nadir altimeters flying simultaneously, the sea surface height (SSH) analysis and 7 d forecast error are globally reduced by about 50 % in the OSSEs. With two wide-swath altimeters, the quality of SSH 7 d forecasts is equivalent to the quality of SSH analysis errors from three nadir altimeters. Our understanding of ocean currents is also greatly improved (30 % improvements at the surface and 50 % at 300 m depth). The resolution capabilities will be drastically improved and will be closer to 100 km wavelength compared to about 250 km today. Flying a constellation of two wide-swath altimeters thus looks to be a very promising solution for the long-term evolution of the Sentinel 3 constellation and the Copernicus Marine Service.

Success Stories of Satellite Radar Altimeter Applications

Abstract For nearly three decades, satellite nadir altimeters have provided essential information to understand primarily ocean but also inland water dynamics. A variety of parameters can be inferred via altimeter measurements, including sea surface height, sea surface wind speeds, significant wave heights, and topography of land, sea ice, and ice sheets. Taking advantage of these parameters with the long record of altimeter data spanning multiple decades has allowed a diverse range of societal applications. As the constellation of altimeter satellites grows, the proven value of the missions to a diverse user community can now be demonstrated by highlighting a selection of verifiable success stories. In this paper, we review selected altimeter success stories that incorporate altimetry data, alone or in conjunction with numerical models or other Earth observations, to solve a key societal problem. First, we define the problem or the key challenge of each use case, and then we articulate the uptake of the successful altimeter-based solution. Our review revealed steady progress by scientific and stakeholder communities in bridging the gap between data availability and their actual uptake to address a variety of applications. Highlighting these altimeter-based success stories can serve to further promote the widespread adoption of future satellite missions such as the Surface Water and Ocean Topography (SWOT) mission scheduled for launch in 2022. Knowledge of the breadth of current utility of altimeter observations can help the scientific community to demonstrate the value in continuing radar altimeter and similar missions, particularly those with expanded capabilities, such as SWOT.

Cross-Track Error Correction and Evaluation of the Tiangong-2 Interferometric Imaging Radar Altimeter

The Interferometric Imaging Radar Altimeter (InIRA) carried on the Tiangong-2 Space Laboratory can observe three-dimensional sea surface topography over a swath tens of kilometers wide. The InIRA represents a test mission that will provide valuable experience for the design and data processing technology of future wide-swath altimeters. In addition to the tropospheric delay, ionospheric delay, and sea state bias that affect traditional altimeters, InIRA was also affected by the cross-track error derived from roll error, baseline length error, and interference phase error, which had to be properly corrected. In this paper, range error correction based on correction models and cross-track error correction based on the reference topography data method were applied to a 15-day InIRA dataset and evaluated using the Jason-2, Jason-3, Saral/AltiKa, and Sentinel-3A. The results showed that the standard deviation between corrected InIRA and the combined dataset was 7.96 cm after eliminating the influence of tides and dynamic atmospheric correction, which was comparable to nadir altimeter measurement accuracy.

Characterizing Rain Cells as Measured by a Ka-Band Nadir Radar Altimeter: First Results and Impact on Future Altimetry Missions

The impact of large atmospheric attenuation events on data quality and availability is a critical aspect for future altimetry missions based on Ka-band altimetry. The SARAL/AltiKa mission and its Ka-band nadir altimeter offer a unique opportunity to assess this impact. Previous publications (Tournadre et al., 2009, 2015) already analyzed the impact of rain on the waveforms at Ka-band and proposed a definition of an elaborate rain flag. This notion tends to give a simpler black and white view of the atmospheric attenuation when the effect on the altimeter measurement is intense. However, in practice, there is a continuum of measurements that may be partially distorted or corrupted by rain events. The present study proposes a wider point of view, directly using the timeseries of the Ka-band altimeter backscattering coefficient for the first time, when previous studies relied on microwave radiometer (MWR) observations or model analyses with coarser resolutions. As guidelines for future Ka-band missions concerning the impact of the atmosphere, the Attenuation CElls Characterization ALgorithm (ACECAL) approach not only provides more representative statistics on rain cells (occurrences, amplitude, size), but also describes the internal structure of the cells. The actual atmospheric attenuation retrieved with ACECAL is about four times larger than the attenuation retrieved from the MWR. At a global scale, 1% of the measurements are affected by an attenuation larger than 23 dB and 10% of the atmospheric attenuation events have a size larger than 40 km. At regional scale, some areas of particular interest for oceanography as Gulf Stream, North Pacific and Brazil currents are more systematically affected compared with global statistics, with atmospheric attenuation up to 8 dB and cell size larger than 25 km when rain occurs. This study also opens some perspectives on the benefits that the community could be drawn from the systematic distribution of the rain cells parameters as secondary products of altimetry missions.

Synthesis Analysis of SWOT KaRIn‐Derived Water Surface Heights and Local Cross‐Calibration of the Baseline Roll Knowledge Error Over Lake Baikal

AbstractThe upcoming Surface Water and Ocean Topography (SWOT) mission provides a promising opportunity for retrieval of high spatiotemporal resolution water surface height (WSH) over inland water bodies. To investigate the accuracy of SWOT derived WSH, the observations over Lake Baikal are simulated and a comprehensive evaluation is conducted in this study. Firstly, compared with Jason‐class altimeter WSH and in situ WSHs, the accuracy of SWOT KaRIn‐derived monthly WSHs and their spatiotemporal characteristics are analyzed. Secondly, a local cross‐calibration method is used to reduce the short wavelength roll error over lakes. The results show that, though SWOT has more observations than Jason‐class altimeter, the accuracy of the SWOT KaRIn‐derived monthly WSHs is difficult to be equivalent with those from Jason‐class altimeter, and varies with the number of duplicated observations, the spatial location and the time interval due to the effect of systematic erros and random errors, but can be significantly improved by local cross‐calibration method, especially at higher spatial resolutions after cross‐calibration associate with external nadir altimeter.

Assessing the Impact of the Assimilation of SWOT Observations in a Global High-Resolution Analysis and Forecasting System – Part 2: Results

A first attempt was made to quantify the impact of the assimilation of Surface Water Ocean Topography (SWOT) swath altimeter data in a global 1/12° high resolution analysis and forecasting system through a series of Observing System Simulation Experiments (OSSEs). The OSSE framework (Nature Run and Free Run) and data assimilation scheme have been described in detail in a companion article (Benkiran et al., 2021). The impact of assimilating data from SWOT and three nadir altimeters was quantified by estimating analysis and forecast error variances for sea surface height (SSH), temperature, salinity, zonal, and meridional velocities. Wave-number spectra and coherence analyses of SSH errors were also computed. SWOT data will significantly improve the quality of ocean analyses and forecasts. Adding SWOT observations to those of three nadir altimeters globally reduces the variance of SSH and surface velocities in analyses and forecasts by about 30 and 20%, respectively. Improvements are greater in high-latitude regions where space/time coverage of SWOT is much denser. The combination of SWOT data with data from three nadir altimeters provides a better resolution of wavelengths between 50 and 200 km with a more than 40% improvement outside tropical regions with respect to data from three nadir altimeters alone. The study has also highlighted that the impact of using SWOT data is likely to be very different depending on geographical areas. Constraining smaller spatial scales (wavelengths below 100 km) remains challenging as they are also associated with small time scales. Although this is only a first step, the study has demonstrated that SWOT data could be readily assimilated in a global high-resolution analysis and forecasting system with a positive impact at all latitudes and outstanding performances.

Fine-Scale Ocean Currents Derived From in situ Observations in Anticipation of the Upcoming SWOT Altimetric Mission

After the launch of the Surface Water and Ocean Topography (SWOT) satellite planned for 2022, the region around the Balearic Islands (western Mediterranean Sea) will be the target of several in situ sampling campaigns aimed at validating the first available tranche of SWOT data. In preparation for this validation, the PRE-SWOT cruise in 2018 was conceived to explore the three-dimensional (3D) circulation at scales of 20 km that SWOT aims to resolve, included in the fine-scale range (1–100 km) as defined by the altimetric community. These scales and associated variability are not captured by contemporary nadir altimeters. Temperature and salinity observations reveal a front that separates local Atlantic Water in the northeast from recent Atlantic Water in the southeast, and extends from the surface to ~150 m depth with maximum geostrophic velocities of the order of 0.20 m s−1 and a geostrophic Rossby number that ranges between −0.24 and 0.32. This front is associated with a 3D vertical velocity field characterized by an upwelling cell surrounded by two downwelling cells, one to the east and the other to the west. The upwelling cell is located near an area with high nitrate concentrations, possibly indicating a recent inflow of nutrients. Meanwhile, subduction of chlorophyll-a in the western downwelling cell is detected in glider observations. The comparison of the altimetric geostrophic velocity with the CTD-derived geostrophic velocity, the ADCP horizontal velocity, and drifter trajectories, shows that the present-day resolution of altimetric products precludes the representation of the currents that drive the drifter displacement. The Lagrangian analysis based on these velocities demonstrates that the study region has frontogenetic dynamics not detected by altimetry. Our results suggest that the horizontal component of the flow is mainly geostrophic down to scales of 20 km in the study region and during the period analyzed, and should therefore be resolvable by SWOT and other future satellite-borne altimeters with higher resolutions. In addition, fine-scale features have an impact on the physical and biochemical spatial variability, and multi-platform in situ sampling with a resolution similar to that expected from SWOT can capture this variability.

Assessing the Impact of the Assimilation of SWOT Observations in a Global High-Resolution Analysis and Forecasting System Part 1: Methods

The future Surface Water Ocean Topography (SWOT) mission due to be launched in 2022 will extend the capability of existing nadir altimeters to enable two-dimensional mapping at a much higher effective resolution. A significant challenge will be to assimilate this kind of data in high-resolution models. In this context, Observing System Simulation Experiments (OSSEs) have been performed to assess the impact of SWOT on the Mercator Ocean and Copernicus Marine Environment Monitoring Service (CMEMS) global, high-resolution analysis and forecasting system. This paper focusses on the design of these OSSEs, in terms of simulated observations and assimilation systems (ocean model and data assimilation schemes). The main results are discussed in a companion paper. Two main updates of the current Mercator Ocean data assimilation scheme have been made to improve the assimilation of information from SWOT data. The first one is related to a different parametrisation of the model error covariance, and the second to the use of a four-dimensional (4D) version of the data assimilation scheme. These improvements are described in detail and their contribution is quantified. The Nature Run (NR) used to represent the “truth ocean” is validated by comparing it with altimeter observations, and is then used to simulate pseudo-observations required for the OSSEs. Finally, the design of the OSSEs is evaluated by ensuring that the differences between the assimilation system and the NR are statistically consistent with the misfits between real ocean observations and real-time operational systems.