Laboratory for Ocean Physics and Satellite Remote Sensing

Abstract Medicanes are cyclones with tropical characteristics in the Mediterranean basin. They typically show an eye with neighboring spiraling bands, but the surrounding region of maximum winds is not well documented, especially near the sea surface, due to limited available observational data. Estimating such characteristics accurately is essential for a better understanding of the specific fine‐scale wind structures and their relationship with the development mechanisms of medicanes. Here we first demonstrate the capacity of synthetic aperture radar (SAR) spaceborne instruments to diagnose important medicane structural characteristics. Building on an unprecedented collection of SAR high‐resolution observations and subsequent sea‐surface wind‐speed estimates, the eye patterns, heavy rainfall, convective cells, and boundary‐layer roll vortices are evidenced, with attributes comparable with those of tropical cyclones of similar intensities. Motivated by this resemblance, we estimate parameters characterizing the cyclone surface wind structure (the intensity, inner and outer size, and Rossby number) from high‐resolution observations of medicanes. We show that their inner size is of magnitude comparable with that of tropical cyclones of similar intensities. Conversely, typical outer sizes and Rossby numbers are found to be smaller. The misrepresentation of these characteristics in medium‐resolution global reanalyses brings into question their suitability and the application of diagnostic tools to these data to monitor the life cycles of medicanes. This invites us to develop dedicated observation‐based monitoring frameworks. Medium‐resolution scatterometers provide more reliable structural estimates despite the small medicane size. Along with SAR surface wind‐speed estimates, and complemented by upper‐level measurements, they may support future reanalysis efforts. Further investigation is needed to understand how the high‐resolution features reported in our work connect with kilometer‐ and subkilometer‐scale physical processes.

The closure of the Sea Level Budget (SLB) is a key challenge for modern physical oceanography. First, it is essential that we ensure the proper identification and quantification of each significant contributor to sea level change through this closure. Second, it provides an efficient means to closely monitor and cross-validate the performance of intricate global observation systems, such as the satellite altimetry constellation, satellite gravimetry missions (GRACE/GRACE-FO), and the Argo in-situ network. Third, this closure reveals to be a beneficial approach for assessing how well the observed climate variables, such as sea level, barystatic sea level, temperature and salinity, land ice melt, and changes in land water storage, comply with conservation laws, in particular those related to mass and energy.In this presentation, we will discuss the state of knowledge of global mean and regional sea level budget with up-to-date observations, encompassing 1) an up-to-date assessment of the budget components and residuals, along with their corresponding uncertainties, spanning from 1993 to 2023 in global mean and throughout the GRACE and Argo era for spatial variations; 2) the identification of the periods and areas where the budget is not closed, i.e. where the residuals are significant; 3) advancements in the analysis and understanding of the spatial patterns of the budget residuals. To investigate the sea level budget (SLB) misclosure, we developed an objective solution that closes the SLB globally. This approach is based on an inverse method that optimally combines the contributions to sea level, weighted by their estimated instrumental uncertainties, and draws from publications such as those by Rodell et al. (2015) and L’Ecuyer et al. (2015).This objective method allows us to precisely identify the dates when the SLB misclosure falls outside the uncertainty estimates, as well as the contributor most likely responsible for the discrepancy. The results of this analysis will be detailed during the presentation.A focus will be made on the North Atlantic Ocean where the residuals are significantly high. We investigate the potential errors causing non-closure in each of the components (e.g., in situ data sampling for the thermosteric component, geocenter correction in the gravimetric data processing) as well as potential inconsistencies in their processing that may impact large-scale patterns (e.g., centre of reference and atmosphere corrections). This work is performed within the framework of the Sea Level Budget Closure Climate Change Initiative (SLBC_cci+) programme of the European Space Agency (https://climate.esa.int/en/projects/sea-level-budget-closure/). This project was initiated by the International Space Science Institute Workshop on Integrative Study of Sea Level Budget (https://www.issibern.ch/workshops/sealevelbudget/).

The increasing volume and diversity of Earth Observation (EO) and climate data produced by Copernicus missions and the Destination Earth (DestinE) initiative pose a major challenge for interoperability and large-scale analysis. Today, global datasets are distributed on heterogeneous spatial grids, forcing users to repeatedly perform ad-hoc regridding steps, which are costly, error-prone, and difficult to reproduce.The GRID4EARTH project addresses this issue by promoting a common Discrete Global Grid System (DGGS) as a foundation for analysis-ready Earth data. In this context, HEALPix emerges as a strong candidate due to its equal-area property, hierarchical structure, and long-standing adoption in global modelling and large-scale data analysis. These properties enable efficient multi-resolution workflows, scalable data access, and natural integration with modern cloud-native formats such as Zarr.However, a key limitation remains: HEALPix is formally defined on the sphere, whereas EO are naturally referenced to the WGS84 ellipsoid. While often ignored at coarse resolutions, this mismatch introduces non-negligible area distortions at Copernicus resolutions and may bias zonal or regional analyses.To overcome this limitation, GRID4EARTH explores anextension of HEALPix to the WGS84 ellipsoid using the authalic sphere associated with the ellipsoid. By preserving equal-area properties on the ellipsoid, this approach provides a consistent spatial framework bridging spherical climate models and ellipsoidal EO. It enables a unified representation for DestinE model outputs and Copernicus satellite data, while remaining compatible with existing HEALPix-based tools and workflows.This contribution presents the motivation, principles, and expected benefits of ellipsoidal HEALPix within GRID4EARTH, and discusses its role as a practical and scalable DGGS for next-generation Earth system data infrastructures.

Amongst the Thematic Assembly Centers (TACs) of the Copernicus Marine Service, the Wind TAC is in charge of providing L3 and L4 sea surface wind and wind stress observation products at a global and regional scale. From 2015, the Wind TAC has been successful in providing data coming from scatterometer observations both Near Real Time (NRT) and reprocessed (Multi Year, MY) data. Since the new phase of the project, starting in 2025, high-resolution (i.e. 1 km) data from C-band Synthetic Aperture Radar (SAR) Satellite have been included in the Wind TAC. As the Copernicus Marine Service evolution is mainly user-driven, we take this opportunity to announce that L3 daily products of Sentinel-1A winds are operationally processed and delivered in Near Real Time since June 2024. The associated Multi Year database of L3 daily products has also been uploaded to the Copernicus Marine Service and covers data from 2018 to 2025. To obtain wind data from SAR observations the ocean surface roughness measured by the satellite is transformed into wind speed and direction using an empirical inversion method called the "dual-pol" (Mouche et al. 2017, Mouche et al. 2019) and an a priori wind helps constrain the possible values. To this purpose, the SAR Wind Production Unit uses the L2 files produced by ESA's Mission Performance Center for Sentinel-1 (MPC-SAR) both for NRT and MY processing. Then, the only difference between the two processing chains (NRT and MY) lies in the a priori wind used to constrain the computed wind speed: while the NRT chain uses wind model from the European Center for Medium-range Weather and Forecasting (ECMWF) operational Integrated Forecast System (IFS), the MY chain uses wind model from ECMWF ReAnalysis v5 (ERA5). To quantify the impact of the input a priori wind, the NRT and MY data are compared over their common period. More generally, the SAR wind data from Wind TAC has been qualified through comparisons against Numerical Weather Forecast (NWP) models, in situ measurements from buoys and co-located measurements from scatterometer. The results of these comparisons are shown here, illustrating some limitations in the methodology and ways to overcome them. Overall, these global comparisons highlight the complementarity of high-resolution SAR wind data with other wind observations. In the near future, the integration (in 2026 and 2027 respectively) in the SAR Wind TAC of the recently launched Sentinel-1C and Sentinel-1D satellites will allow for better coverage, and the complementarity between observation should be further investigated through triple-collocation between SAR, scatterometer and buoy data.

<strong class="journal-contentHeaderColor">Abstract.</strong> Tropical cyclones are among the most destructive natural disasters. Accurately estimating wind speeds during these extreme weather events remains a challenge, but is essential for optimising the design of offshore structures, such as offshore wind turbines, which could be exposed to such phenomena. In this paper, a state-of-the-art parametric model fed with the besttrack dataset is implemented to predict wind generated by tropical cyclones at hub height. The surface wind model accounts for a parametric axisymmetric surface wind model and an asymmetric part, being both adjusted on satellite borne Synthetic Aperture Radar observations. The surface wind is then extrapolated vertically with a logarithmic law using the drag coefficient from the wave-age-dependent stress parameterisation. The performance of this extrapolation is first assessed with wind measurements of five tropical cyclones. Then, modelled wind time series and surface wind fields are compared with measurements and high-fidelity models. The consistent results confirm the ability of the model to predict extreme tropical cyclone winds. A key limitation of parametric models lies&nbsp;in their omission of large-scale orographic effects, as illustrated by the complex terrain of Taiwan.

<strong class="journal-contentHeaderColor">Abstract.</strong> The North Atlantic (NA) GO-SHIP A25 OVIDE-BOCATS section is a long-term repeat hydrographic transect extending from Portugal to Greenland. Since 2002, physical and biogeochemical measurements have been carried out biennially along the OVIDE-BOCATS section, contributing to a better understanding of water mass properties, mixing, circulation, carbon storage, and climate change impacts such as ocean acidification (OA) in the NA. In particular, the high-precision pH measurements on the total hydrogen ion scale (pH_T) from the OVIDE-BOCATS program represent a key milestone in monitoring OA in this particularly climate sensitive region. The method used for pH_T determination relies on adding meta-cresol purple (mCP) dye to the seawater sample and spectrophotometrically measuring its absorbances at specific wavelengths. The OVIDE-BOCATS program has used unpurified mCP dye, which impurities have been proven to bias pH_T values. Here we quantified the bias induced by these impurities in pH_T measurements. We found that measurements carried out using the unpurified mCP dye tend to be, on average, <strong>0.011 &plusmn; 0.002</strong> pH_T units higher than those obtained using the purified mCP dye, with this difference slightly decreasing at higher pH_T values. Moreover, we tested independent methods to correct the effect of impurities in both the historical and recent OVIDE-BOCATS pH_T data, demonstrating that the correction is consistent across methods. The long-term pH_T dataset has been updated to include newly acquired data and absorbance measurements, and to standardize corrections for mCP dye impurities. This effort results in a twenty-year dataset of pH_T corrected for mCP dye impurities, that demonstrates the possibility of a global effort to improve the reliability and coherency of spectrophotometric pH_T measurements made with unpurified mCP dye. The corrections applied to our pH_T dataset have negligible implications for the OA rates previously reported, but they do affect the depth of the aragonite saturation horizon, implying a shoaling of approximately 150 m.

Abstract A tropical cyclone (TC) can generally be divided into three regions: inner core with vigorous convection, intermediate region with intermittent convection, and far outer region with less convective activity. The different physics in these three regions suggest correspondingly different wind structure models. In this study, we combine the inner‐core wind model from Tao et al. (2023, https://doi.org/10.1029/2023gl104583 , T23), the outer wind model from Emanuel (2004, https://texmex.mit.edu/pub/emanuel/PAPERS/Energetics_Structure.pdf , E04), and a transition model of a modified Rankine vortex to create a new fast and analytical model for the complete radial structure of the TC wind field. The T23 model captures inner‐core wind variation with small errors, while the E04 model reproduces the broad outer wind structure at large radii well. The new wind model combines the strengths from both T23 and E04 models without the need for statistical fitting, showing great potential in reproducing the full range of simulated and observed TC winds.

<strong class="journal-contentHeaderColor">Abstract.</strong> We present a large-scale laboratory model of the Strait of Gibraltar that reproduces realistic topography, tidal forcing, stratification, and rotation, enabling controlled investigation of key exchange processes linking the Mediterranean Sea and Atlantic Ocean. Velocity and density measurements confirm dynamic similarity with ocean observations. Analysis of the flow near Camarinal Sill shows that bottom boundary layers are the primary source of turbulent kinetic energy, exceeding contributions from shear at the interface between Atlantic and Mediterranean waters. The enhanced role of bottom-generated turbulence is linked to separation of the Mediterranean gravity current induced by an adverse pressure gradient during outflow, providing a new explanation for the well-documented detachment of the Mediterranean plume west of the sill. This detachment intensifies during spring tides, driving diluted waters farther into the Atlantic, while during neap tides bottom-generated and interfacial turbulence coincide, offering a consistent explanation for the high dissipation rates reported in field measurements. Overall, tidal forcing promotes full-depth mixing, with up to ~20 % density reduction west of CS and oscillatory ~20 % variations east, consistent with field data, and simultaneously introducing an important phase shift between velocity and density fields, with implications for parameterizing turbulent exchange and definition of the composite internal Froude number for reliable diagnose of hydraulic control. During spring tides, hydraulic control is intermittently lost during inflow and this loss propagates eastward, while additional control points arise west of the sill. Neap tides exhibit signatures of control which persist much longer during a tidal cycle as compared to spring tides, but does not propagate to the east when the tide reverses. Transport and energy budgets reveal strong longitudinal and transverse variability, highlighting the need for fully three-dimensional diagnostics. Volume transport, dominated by transverse topographic variability, exceeds salt transport by two orders of magnitude, confirming net Atlantic inflow. A phase-lagged internal bore release between the northern and southern transects is observed, consistent with field observations, and we show that it is independent of barotropic effects or Kelvin waves. These results demonstrate that high-fidelity laboratory modeling can capture the essential three-dimensional dynamics of energetic straits and provides a powerful complement to observational and numerical approaches.

<strong class="journal-contentHeaderColor">Abstract.</strong> The North Atlantic (NA) GO-SHIP A25 OVIDE-BOCATS section is a long-term repeat hydrographic transect extending from Portugal to Greenland. Since 2002, physical and biogeochemical measurements have been carried out biennially along the OVIDE-BOCATS section, contributing to a better understanding of water mass properties, mixing, circulation, carbon storage, and climate change impacts such as ocean acidification (OA) in the NA. In particular, the high-precision pH measurements on the total hydrogen ion scale (pH_T) from the OVIDE-BOCATS program represent a key milestone in monitoring OA in this particularly climate sensitive region. The method used for pH_T determination relies on adding meta-cresol purple (mCP) dye to the seawater sample and spectrophotometrically measuring its absorbances at specific wavelengths. The OVIDE-BOCATS program has used unpurified mCP dye, which impurities have been proven to bias pH_T values. Here we quantified the bias induced by these impurities in pH_T measurements. We found that measurements carried out using the unpurified mCP dye tend to be, on average, <strong>0.011 &plusmn; 0.002</strong> pH_T units higher than those obtained using the purified mCP dye, with this difference slightly decreasing at higher pH_T values. Moreover, we tested independent methods to correct the effect of impurities in both the historical and recent OVIDE-BOCATS pH_T data, demonstrating that the correction is consistent across methods. The long-term pH_T dataset has been updated to include newly acquired data and absorbance measurements, and to standardize corrections for mCP dye impurities. This effort results in a twenty-year dataset of pH_T corrected for mCP dye impurities, that demonstrates the possibility of a global effort to improve the reliability and coherency of spectrophotometric pH_T measurements made with unpurified mCP dye. The corrections applied to our pH_T dataset have negligible implications for the OA rates previously reported, but they do affect the depth of the aragonite saturation horizon, implying a shoaling of approximately 150 m.

The coastal area of north-west (NW) Africa is a highly productive ecosystem due to the presence of a strong upwelling. This ecosystem supports large populations of small pelagic fish, such as sardinellas, which have significant socio-economic value for local populations. In this study, we analyzed the acoustic data collected during a one-month survey along the Senegalese coast at the beginning of the upwelling season. Hierarchical clusterings were performed to classify the acoustic data from the epipelagic zone (down to 120 m-depth) separately for daytime and nighttime. The analysis identified five echo-groups during the day and six at night. The resulting echo-groups were then compared to stratified midwater trawl samplings to support hypotheses about the organisms responsible for the echoes. Additionally, a remotely operated towed vehicle (called Scanfish) was used to monitor environmental variables down to 100 m depth. Two machine learning models were applied to link the classified echo-groups to the environmental data for both day and night. Each daytime echo group had a corresponding nighttime echo group, with also similar environmental preferences. Fish schools were mainly found in shallow coastal waters while dense sound-scattering layers detected at 38 kHz, likely composed of small fish or fish larvae, were observed in the temperature range of 17°-21 °C for both day and night. The other echo-groups were composed of fluid-like zooplankton or gas-bearing zooplankton. The sixth night echo-group corresponded to migrant organisms and was predominant at night. Overall, the analyses of the abiotic habitats for each echo-group allow us to better understand the organism distributions during the beginning of the NW Africa upwelling season. • A one-month acoustic survey was conducted in the north-west Africa during the beginning of the upwelling season. • A remotely operated towed vehicle was used to monitor environmental variables down to 100 m depth. • Several scattering groups were classified using a multifrequency approach. • A machine learning method was used to link these echo-groups to the environmental data. • New insights into the spatial distributions of the organisms along the Senegalese coast were provided.