We present data collected in the framework of the Algerian BAsin Circulation Unmanned Survey (ABACUS) project. The main objective of ABACUS is the monitoring of the basin circulation and of the surface and intermediate water masses' physical and biological properties in a key region of the Mediterranean Sea circulation. Data presented here have been collected through deep glider cruises in the Western Mediterranean Sea during the autumns of 2014, 2015 and 2016; activities at sea are expected to be repeated during the coming years, so that the dataset will be extended. Glider missions were conducted in the Algerian Basin, between the island of Mallorca and the Algerian coast. Across the three glider missions, eight repeated transects were completed which enabled us to investigate the basin-scale circulation and the presence of mesoscale structures, utilising both the adaptive sampling capabilities of the gliders and the higher resolution of the data. After collection, all data passed a quality control procedure and were then made available through an unrestricted repository host by the SOCIB Data Centre at https://doi.org/10.25704/b200-3vf5. The actual dataset spans three autumn seasons, providing an important contribution to the data collection in the chronically undersampled Algerian Basin.
Temperature and salinity data collected in the first 975¿m of the water column allowed us to identify the main water masses and describe their characteristics, improving the understanding of the dynamics of the region. On the timescale of the project, data show a large variability in the surface layer and reduced variability in the intermediate and deep layers. Our measurements have been successfully compared to data previously collected in the area from 1909 to 2011. Results showed similar overall distribution, ranges and variability to the historical data, with no outliers in the surface or deep layers., The ABACUS 1 missions (2014) were supported by the Joint European Research Infrastructure network for Coastal Observatories (JERICO) TransNational Access (TNA) third call (grant agreement no. 262584). The research leading to ABACUS 3 (2016) was supported by the European Union's H2020 Framework Programme (h2020-INFRAIA-2014-2015) (JERICO-NEXT grant agreement no. 654410). Additional EU funding (PERSEUS grant agreement no. 287600) is acknowledged. The activities described in this paper were developed in the framework of the Italian Flagship Project RITMARE. Ananda Pascual wishes to acknowledge support from the PRE-SWOT project (CTM2016-78607-P) funded by the Spanish National Research Program.

Eight years of glider data are used to characterize the temporal and spatial variability of a region in the western Mediterranean that will constitute one of the targets for the calibration phase of the Surface Water and Ocean Topography (SWOT) satellite mission. The characteristic horizontal dimension of mesoscale instabilities in the Mallorca channel is 6.0 km. The temporal evolution of intermediate water masses is dominated by an increase over time of the characteristic temperature values. Western Mediterranean and Levantine Intermediate waters display an increase of the temperature extrema of 0.064 ± 0.002 and 0.044 ± 0.002 °C/year between 2011 and 2018, respectively. At the layer of Levantine Intermediate water the salinity temporal regression reveals a mean trend of 0.010 year. Temperature annual cycle shows an averaged temperature gradient of ∼6 °C in 6 months at the upper layer, with a disconnection with the annual cycle at 100-m depth. The circulation across the channel is dominated by high-frequency variability. The signature of eddies with radius ranging from 5 to 18 km is apparent in 16% of the transects analyzed and mainly in spring and summer, with a dominance of subsurface cyclonic eddies. Two-way flow controls the annual cycle of the water transport through the channel with prevalence of the inflow of Atlantic water. Variations of water transport over timescales of weeks to months can be similar to those identifiable as seasonal changes., This study is a contribution to the PRE‐SWOT project (CTM2016‐78607‐P) funded by the Spanish National Research Program and the European Regional Development Fund (MINECO‐FEDER). Glider data are freely available at the SOCIB website (https://doi.org/10.25704/jd07-sv9).

The complex structure of the vertical velocity field inside an anticyclonic eddy located just south of the Canary Islands is analyzed through a high-resolution ocean model. Based on the flow divergence, vertical velocity is decomposed into various forcing components. The analysis reveals that advection and stretching of vorticity are the most important forcing contributions to the vertical velocity within the eddy. In the mixed layer, a small-scale multipolar vertical velocity pattern dominates. This is the result of vertical mixing effects that enhance the surface vertical velocity by increasing the ageostrophic velocity profile. As a result, an ageostrophic secondary circulation arises that acts to restore thermal-wind balance, inducing strong vertical motions. Nonlinear Ekman pumping/ suction patterns resemble the small-scale vertical velocity field, suggesting that nonlinear Ekman effects are important in explaining the complex vertical velocity, despite an overestimate of its magnitude. In the eddy thermocline, the vertical velocity is characterized by a dipolar pattern, which experiences changes in intensity and axisymmetrization with time. The dipolar vertical velocity distribution arises from the imbalance between the advection and stretching of the vorticity forcing terms. A vertical velocity dipole is also obtained by solving a generalized omega equation from density and horizontal velocity fields, which also shows a preponderance of the ageostrophic term. The ubiquity of dipolar vertical velocity distributions inside isolated anticyclones is supported by recent observational findings in the same oceanic region., This work has been supported by the FLUXES (CTM2015-69392-C3-3-R) project funded by the Spanish National Research Program and the European Regional Development Fund (MINECO-FEDER). Thanks to the essential support of Pablo Sangrà, from now on always in our memories. Sheila Estrada-Allis is supported by a post-doctoral contract from the National Council of Science and Technology of Mexico–Mexican Ministry of Energy–Hydrocarbon Trust, project 201441. Evan Mason is supported by the Copernicus Marine Environment Monitoring Service (CMEMS) MedSUB project; CMEMS is implemented by Mercator Ocean in the framework of a delegation agreement with the European Union. Bàrbara Barceló-Llull is supported by a post-doctoral contract from the Spanish National Research Program associated to the PRE-SWOT project (CTM2016-78607-P).

A coupled physical-biogeochemical model (ROMS-PISCES) forced by climatological fields is used to examine the role of upwelling filaments in the offshore exchange of particulate (POC) and dissolved (DOC) organic carbon in the Canary Current eastern boundary upwelling system (CanC EBUS). In this region, mesoscale filaments at Capes Ghir ( °N) and Juby ( °N) have been frequently described using both observational and numerical data. Due to their semi-permanent presence and unique dynamical characteristics, studies focusing on filaments often provide an incomplete picture of the physical and biological processes at work, and their effects on coast-to-ocean export. The present model experiment confirms the complex three-dimensional structure of the filaments that comprises both offshore and onshore flow components. The model shows strong seasonal variability in the offshore transport mediated by the filaments. Recirculation at the edges of the filaments returns water towards the shore, especially in autumn when they are diverted northwards by the large scale boundary circulation. By contrast, offshore transport peaks during late spring - early summer when onshore recirculation is limited. Overall, the estimated net annual offshore flux of excess total organic carbon (e-TOC, the non-refractory pools of DOC and POC) averages 2.0 kg C y−1, and may increase up to 4.3 kg C y−1 during the peak upwelling season, each filament contributing to export of up to 22.6% of the organic carbon within the first 100 km from shore along the CanC EBUS (between 9.5 and 32 ° N). These results strongly support the inclusion of offshore transport estimates by coastal filaments in regional carbon budgets., This research was supported by projects CAIBEX (CTM2007-66408-CO2-02) and FLUXES (CTM2015- 69392-C3-1-R) funded by the ‘Spanish Plan Nacional de I  + D’, and by projects SUMMER (AMD-817806-5) and TRIATLAS (AMD-817578-5) financed by the 'European Commission' to JA. EM acknowledges support from the Spanish Research Agency and the European Regional Development Fund (Award no. CTM2016-78607-P)., Peer reviewed

This article belongs to the Special Issue Calibration and Validation of Satellite Altimetry., In the near future, the Surface Water Ocean Topography (SWOT) mission will provide images of altimetric data at kilometric resolution. This unprecedented 2-dimensional data structure will allow the estimation of geostrophy-related quantities that are essential for studying the ocean surface dynamics and for data assimilation uses. To estimate these quantities, i.e., to compute spatial derivatives of the Sea Surface Height (SSH) measurements, the uncorrelated, small-scale noise and errors expected to affect the SWOT data must be smoothed out while minimizing the loss of relevant, physical SSH information. This paper introduces a new technique for de-noising the future SWOT SSH images. The de-noising model is formulated as a regularized least-square problem with a Tikhonov regularization based on the first-, second-, and third-order derivatives of SSH. The method is implemented and compared to other, convolution-based filtering methods with boxcar and Gaussian kernels. This is performed using a large set of pseudo-SWOT data generated in the western Mediterranean Sea from a 1/60 ∘ simulation and the SWOT simulator. Based on root mean square error and spectral diagnostics, our de-noising method shows a better performance than the convolution-based methods. We find the optimal parametrization to be when only the second-order SSH derivative is penalized. This de-noising reduces the spatial scale resolved by SWOT by a factor of 2, and at 10 km wavelengths, the noise level is reduced by factors of 104 and 103 for summer and winter, respectively. This is encouraging for the processing of the future SWOT data., L.G.-N acknowledges Ph.D. funding from CNES. The contributions of L.G.-N, E.C., J.L.S. and N.P. are also funded by CNES (SWOT Science Team project) and ANR (BOOST-SWOT project, ANR-17-CE01-0009-01). A.P. is supported by the PRE-SWOT project (CTM2016-78607-P)., Peer reviewed

This article belongs to the Special Issue Calibration and Validation of Satellite Altimetry., The quality of the Data Unification and Altimeter Combination System (DUACS) Sentinel-3A altimeter data in the coastal area of the European seas is investigated through a comparison with in situ tide gauge measurements. The comparison was also conducted using altimetry data from Jason-3 for inter-comparison purposes. We found that Sentinel-3A improved the root mean square differences (RMSD) by 13% with respect to the Jason-3 mission. In addition, the variance in the differences between the two datasets was reduced by 25%. To explain the improved capture of Sea Level Anomaly by Sentinel-3A in the coastal band, the impact of the measurement noise on the synthetic aperture radar altimeter, the distance to the coast, and Long Wave Error correction applied on altimetry data were checked. The results confirmed that the synthetic aperture radar altimeter instrument onboard the Sentinel-3A mission better solves the signal in the coastal band. Moreover, the Long Wave Error processing contributes to reduce the errors in altimetry, enhancing the consistency between the altimeter and in situ datasets., This study was funded by the Copernicus Marine Environment Monitoring Service (CMEMS) Sea Level Thematic Assembly Centre (SL-TAC). A.P. acknowledges support from the Spanish Research Agency and the European Regional Development Fund (Award no. CTM2016-78607-P). M.M. acknowledges a grant funded by Ministerio de Ciencia e Innovación and Agencia Estatal de Investigación (grant number IED2019-000985-I).

This article belongs to the Special Issue Calibration and Validation of Satellite Altimetry., In the near future, the Surface Water Ocean Topography (SWOT) mission will provide images of altimetric data at kilometric resolution. This unprecedented 2-dimensional data structure will allow the estimation of geostrophy-related quantities that are essential for studying the ocean surface dynamics and for data assimilation uses. To estimate these quantities, i.e., to compute spatial derivatives of the Sea Surface Height (SSH) measurements, the uncorrelated, small-scale noise and errors expected to affect the SWOT data must be smoothed out while minimizing the loss of relevant, physical SSH information. This paper introduces a new technique for de-noising the future SWOT SSH images. The de-noising model is formulated as a regularized least-square problem with a Tikhonov regularization based on the first-, second-, and third-order derivatives of SSH. The method is implemented and compared to other, convolution-based filtering methods with boxcar and Gaussian kernels. This is performed using a large set of pseudo-SWOT data generated in the western Mediterranean Sea from a 1/60 ∘ simulation and the SWOT simulator. Based on root mean square error and spectral diagnostics, our de-noising method shows a better performance than the convolution-based methods. We find the optimal parametrization to be when only the second-order SSH derivative is penalized. This de-noising reduces the spatial scale resolved by SWOT by a factor of 2, and at 10 km wavelengths, the noise level is reduced by factors of 104 and 103 for summer and winter, respectively. This is encouraging for the processing of the future SWOT data., L.G.-N acknowledges Ph.D. funding from CNES. The contributions of L.G.-N, E.C., J.L.S. and N.P. are also funded by CNES (SWOT Science Team project) and ANR (BOOST-SWOT project, ANR-17-CE01-0009-01). A.P. is supported by the PRE-SWOT project (CTM2016-78607-P).

Anticyclonic mesoscale eddies are often observed in the Balearic Sea (BS) toward the end of summer and autumn. In some years, these eddies become strong and persistent, modifying the local water mass properties. In this study, we analyze two of the most significant recent long-lived anticyclonic eddies, occurring in 2010 and 2017, using data from a high-resolution circulation model, altimetry and satellite-borne sea surface temperature observations. These eddies lasted around 2 and 4 months, respectively, with a radius varying between 40 and 75 km. The generation and intensification mechanisms of these long-lived anticyclonic eddies are studied by means of (a) energy conversion terms associated with eddy-mean flow interaction and (b) model sensitivity tests. Results show that these eddies were formed and intensified through mixed barotropic and baroclinic instabilities. The former are produced under the action of intense northwesterly (NW) winds. The latter are related to the existence of an intense summer thermal front between the BS and the Gulf of Lion, and to northward inflows of relatively lower salinity waters. Both the wind events and the presence of the thermal front are necessary for the formation of the eddies. The intensification process varied between both events. While in 2010 it was driven by significant salinity gradients produced by northwards inflows, in 2017 it was produced by additional intense NW winds. Both long-lived anticyclonic eddies created long-lasting surface temperature anomalies up to 2.5°C, which have characteristics of local marine heatwaves., This work was supported by the La Caixa foundation through the MEDCLIC project (LCF/PR/PR14/110900). A. Pascual acknowledges support from the Spanish Research Agency and the European Regional Development Fund (Award no. CTM2016-78607-P). The authors thank AEMET, the Spanish Meteorological Agency, for providing the HIRLAM wind fields and CMEMS for satellite altimetry and satellite sea surface temperature products (https://marine.copernicus.eu/).

Intensive hydrographic and horizontal velocity measurements collected in the Alboran Sea enabled us to diagnose the three-dimensional dynamics of a frontal system. The sampled domain was characterized by a 40 km diameter anticyclonic eddy, with an intense front on its eastern side, separating the Atlantic and Mediterranean waters. Here, we implemented a multi-variate variational analysis (VA) to reconstruct the hydrographic fields, combining the 1-km horizontal resolution of the Underway Conductivity-Temperature-Depth (CTD) system with information on the flow shape from the Acoustic Doppler Current Profiler velocities. One advantage of the VA is given by the physical constraint, which preserves fine-scale gradients better than the classical optimal interpolation (OI). A comparison between real drifter trajectories and virtual particles advected in the mapping quantified the improvements in the VA over the OI, with a 15% larger skill score. Quasi-geostrophic (QG) and semi-geostrophic (SG) omega equations enabled us to estimate the vertical velocity (w) which reached 40 m/day on the dense side of the front. How nutrients and other passive tracers leave the mixed-layer and subduct is estimated with 3D advection from the VA, which agreed with biological sampling from traditional CTD casts at two eddy locations. Downwelling warm filaments are further evidence of subduction, in line with the w from SG, but not with QG. SG better accounted for the along-isopycnal component of w in agreement with another analysis made on isopycnal coordinates. The multi-platform approach of this work and the use of variational methods improved the characterization and understanding of (sub)-mesoscale frontal dynamics., This research was supported by the Office of Naval Research Departmental Research Initiative CALYPSO under program officers Terri Paluszkiewicz and Scott Harper. The authors' ONR Grant are as follows: N000141613130 (AP, SR and AM), N000141812418 (PMP), S. Johnston N000141812416 (TMSJ), N000141812138 (TO), N000141712517 and N00014191269 (LRC), N000141812139 and N000141812420 (AS) and N000141812139and (EDA). This article is also a contribution to the PRE-SWOT project funded by the Spanish Research Agency and the European Regional Development Fund (AEI/FEDER, UE) under grant agreement (CTM2016-78607-P).

© 2024 Cutolo, Pascual, Ruiz, Zarokanellos and Fablet. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms., Combining remote-sensing data with in-situ observations to achieve a comprehensive 3D reconstruction of the ocean state presents significant challenges for traditional interpolation techniques. To address this, we developed the CLuster Optimal Interpolation Neural Network (CLOINet), which combines the robust mathematical framework of the Optimal Interpolation (OI) scheme with a self-supervised clustering approach. CLOINet efficiently segments remote sensing images into clusters to reveal non-local correlations, thereby enhancing fine-scale oceanic reconstructions. We trained our network using outputs from an Ocean General Circulation Model (OGCM), which also facilitated various testing scenarios. Our Observing System Simulation Experiments aimed to reconstruct deep salinity fields using Sea Surface Temperature (SST) or Sea Surface Height (SSH), alongside sparse in-situ salinity observations. The results showcased a significant reduction in reconstruction error up to 40% and the ability to resolve scales 50% smaller compared to baseline OI techniques. Remarkably, even though CLOINet was trained exclusively on simulated data, it accurately reconstructed an unseen SST field using only glider temperature observations and satellite chlorophyll concentration data. This demonstrates how deep learning networks like CLOINet can potentially lead the integration of modeling and observational efforts in developing an ocean digital twin., The author(s) declare financial support was received for the research, authorship, and/or publication of this article. EC acknowledges support from the Spanish Ministerio de Ciencia e Innovacion (grant BES-2017-080763). This article is also a contribution to the PRE-SWOT and FAST-SWOT projects funded by the Spanish Research Agency and the European Regional Development Fund (AEI/FEDER, UE) under grant agreements (CTM2016-78607-P) and (PID2021-122417NB-I00) respectively. Furthermore AP and SR were funded by the CALYPSO project Office of Naval Research grant N0014-21-1-2702., Peer reviewed