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Horizontal velocity gradients of a flow field and the related kinematic properties (KPs) of divergence, vorticity, and strain rate can be estimated from dense drifter deployments, e.g., the spatiotemporal average divergence (and other KPs) over a triangular area defined by three drifters and over a given time interval can be computed from the initial and final areas of said triangle. Unfortunately, this computation can be subject to large errors, especially when the triangle shape is far from equilateral. Therefore, samples with small aspect ratios are generally discarded. Here we derive the thresholds on two shape metrics that optimize the balance between retention of good and removal of bad divergence estimates. The primary tool is a high-resolution regional ocean model simulation, where a baseline for the average divergence can be established, so that actual errors are available. A value of 0.2 for the scaled aspect ratio Λ and a value of 0.86π for the largest interior angle θ are found to be equally effective thresholds, especially at scales of 5 km and below. While discarding samples with low Λ or high θ values necessarily biases the distribution of divergence estimates slightly toward positive values, this bias is small compared to (and in the opposite direction of) the Lagrangian sampling bias due to drifters preferably sampling convergence regions. Errors due to position uncertainty are suppressed by the shape-based subsampling. The subsampling also improves the identification of the areas of extreme divergence or convergence. An application to an observational dataset demonstrates that these model-derived thresholds can be effectively used on actual drifter data. Significance Statement Divergence in the ocean indicates how fast floating objects in the ocean spread apart, while convergence (negative divergence) captures how fast they accumulate. Measuring divergence in the ocean, however, remains challenging. One method is to estimate divergence from the trajectories of drifting buoys. This study provides guidance under what circumstances these estimates should be discarded because they are too likely to have large errors. The criteria proposed here are less stringent than some of the ad hoc criteria previously used. This will allow users to retain more of their estimates. We consider how position uncertainty affects the reliability of the divergence estimates. An observational dataset collected in the Mediterranean is used to illustrate an application of these reliability criteria.

The diurnal cycling of submesoscale circulations in vorticity, divergence, and strain is investigated using drifter data collected as part of the Lagrangian Submesoscale Experiment (LASER) experiment, which took place in the northern Gulf of Mexico during winter 2016, and ROMS simulations at different resolutions and degree of realism. The first observational evidence of a submesoscale diurnal cycle is presented. The cycling is detected in the LASER data during periods of weak winds, whereas the signal is obscured during strong wind events. Results from ROMS in the most realistic setup and in sensitivity runs with idealized wind patterns demonstrate that wind bursts disrupt the submesoscale diurnal cycle, independently of the time of day at which they happen. The observed and simulated submesoscale diurnal cycle supports the existence of a shift of approximately 1–3 h between the occurrence of divergence and vorticity maxima, broadly in agreement with theoretical predictions. The amplitude of the modeled signal, on the other hand, always underestimates the observed one, suggesting that even a horizontal resolution of 500 m is insufficient to capture the strength of the observed variability in submesoscale circulations. The paper also presents an evaluation of how well the diurnal cycle can be detected as function of the number of Lagrangian particles. If more than 2000 particle triplets are considered, the diurnal cycle is well captured, but for a number of triplets comparable to that of the LASER analysis, the reconstructed diurnal cycling displays high levels of noise both in the model and in the observations.

The Mediterranean Sea is a prominent climate-change hot spot, with many socioeconomically vital coastal areas being the most vulnerable targets for maritime safety, diverse met-ocean hazards and marine pollution. Providing an unprecedented spatial and temporal resolution at wide coastal areas, high-frequency radars (HFRs) have been steadily gaining recognition as an effective land-based remote sensing technology for continuous monitoring of the surface circulation, increasingly waves and occasionally winds. HFR measurements have boosted the thorough scientific knowledge of coastal processes, also fostering a broad range of applications, which has promoted their integration in coastal ocean observing systems worldwide, with more than half of the European sites located in the Mediterranean coastal areas. In this work, we present a review of existing HFR data multidisciplinary science-based applications in the Mediterranean Sea, primarily focused on meeting end-user and science-driven requirements, addressing regional challenges in three main topics: (i) maritime safety, (ii) extreme hazards and (iii) environmental transport process. Additionally, the HFR observing and monitoring regional capabilities in the Mediterranean coastal areas required to underpin the underlying science and the further development of applications are also analyzed. The outcome of this assessment has allowed us to provide a set of recommendations for future improvement prospects to maximize the contribution to extending science-based HFR products into societally relevant downstream services to support blue growth in the Mediterranean coastal areas, helping to meet the UN's Decade of Ocean Science for Sustainable Development and the EU's Green Deal goals., peer-reviewed

16 pages, 4 figures, 2 tables, Increasing interest in the acquisition of biotic and abiotic resources from within the deep sea (e.g., fisheries, oil–gas extraction, and mining) urgently imposes the development of novel monitoring technologies, beyond the traditional vessel-assisted, time-consuming, high-cost sampling surveys. The implementation of permanent networks of seabed and water-column-cabled (fixed) and docked mobile platforms is presently enforced, to cooperatively measure biological features and environmental (physicochemical) parameters. Video and acoustic (i.e., optoacoustic) imaging are becoming central approaches for studying benthic fauna (e.g., quantifying species presence, behavior, and trophic interactions) in a remote, continuous, and prolonged fashion. Imaging is also being complemented by in situ environmental-DNA sequencing technologies, allowing the traceability of a wide range of organisms (including prokaryotes) beyond the reach of optoacoustic tools. Here, we describe the different fixed and mobile platforms of those benthic and pelagic monitoring networks, proposing at the same time an innovative roadmap for the automated computing of hierarchical ecological information on deep-sea ecosystems (i.e., from single species’ abundance and life traits to community composition, and overall biodiversity), This work was developed within the framework of the Tecnoterra (ICM-CSIC/UPC) and the following project activities: ARIM (Autonomous Robotic sea-floor Infrastructure for benthopelagic Monitoring; MartTERA ERA-Net Cofound), ARCHES (Autonomous Robotic Networks to Help Modern Societies; German Helmholtz Association), RESBIO (Grant TEC2017-87861-R; Ministerio de Ciencia, Innovación y Universidades), RESNEP (Grant CTM2017-82991-C2-1-R; Ministerio de Ciencia, Innovacion y Universidades), MERCES (Marine Ecosystem Restoration in Changing European Seas - GA No. 689518), and IDEM (Implementing the MSFD to the Deep Mediterranean Sea, GA No. 11.0661/2017/750680/SUB/ENV.C2)

Due to the semi-enclosed nature of the Mediterranean Sea, natural disasters and anthropogenic activities impose stronger pressures on its coastal ecosystems than in any other sea of the world. With the aim of responding adequately to science priorities and societal challenges, littoral waters must be effectively monitored with high-frequency radar (HFR) systems. This land-based remote sensing technology can provide, in near-real time, fine-resolution maps of the surface circulation over broad coastal areas, along with reliable directional wave and wind information. The main goal of this work is to showcase the current status of the Mediterranean HFR network and the future roadmap for orchestrated actions. Ongoing collaborative efforts and recent progress of this regional alliance are not only described but also connected with other European initiatives and global frameworks, highlighting the advantages of this cost-effective instrument for the multi-parameter monitoring of the sea state. Coordinated endeavors between HFR operators from different multi-disciplinary institutions are mandatory to reach a mature stage at both national and regional levels, striving to do the following: (i) harmonize deployment and maintenance practices; (ii) standardize data, metadata, and quality control procedures; (iii) centralize data management, visualization, and access platforms; and (iv) develop practical applications of societal benefit that can be used for strategic planning and informed decision-making in the Mediterranean marine environment. Such fit-for-purpose applications can serve for search and rescue operations, safe vessel navigation, tracking of marine pollutants, the monitoring of extreme events, the investigation of transport processes, and the connectivity between offshore waters and coastal ecosystems. Finally, future prospects within the Mediterranean framework are discussed along with a wealth of socioeconomic, technical, and scientific challenges to be faced during the implementation of this integrated HFR regional network., This study has been partially developed in the framework of the Interreg MED Strategic Project SHAREMED, co-financed by the European Regional Development Fund under the funding program Interreg MED 2014–2020. Website: https://sharemed.interreg-med.eu/ (last access: 31 March 2022). We are also grateful for the partial support of the (i) the project PO FEAMP 2014/2020 (Misura 2.51) funded by Regione Campania (Italy), (ii) the 2017 PRIN project EMME (Exploring the fate of Mediterranean microplastic: from distribution pathways to biological effects) funded by the Italian Ministry for Research (grant agreement no. 2017WERYZP), and (iii) the CMEMS-INSTAC phase II, which provides the context of the activities for HFR data harmonization, standardization, and distribution. Collaborative discussion on data management harmonization at the European level has also been carried out thanks to the contribution of the projects INCREASE (CMEMS Service Evolution Call for Tenders 21-SE-CALL1) and SeaDataCloud (EU-H2020 GA no. 730960).

The Mediterranean Sea is a prominent climate change hot spot, being their socio-economically vital coastal areas the most vulnerable targets for maritime safety, diverse met-ocean hazards and marine pollution. Providing an unprecedented spatial and temporal resolution at wide coastal areas, High-frequency radars (HFRs) have been steadily gaining recognition as an effective land-based remote sensing technology for a continuous monitoring of the surface circulation, increasingly waves and occasionally winds. HFR measurements have boosted the thorough scientific knowledge of coastal processes, also fostering a broad range of applications, which has promoted their integration in the Coastal Ocean Observing Systems worldwide, with more than half of the European sites located in the Mediterranean coastal areas. In this work, we present a review of existing HFR data multidisciplinary science-based applications in the Mediterranean Sea, primarily focused on meeting end-users and science-driven requirements, addressing regional challenges in three main topics: i) maritime safety; ii) extreme hazards; iii) environmental transport process. Additionally, the HFR observing and monitoring regional capabilities in the Mediterranean region required to underpin the underlying science and the further development of applications are also analyzed. The outcome of this assessment has allowed us to finally provide a set of recommendations for the future improvement prospects to maximize the contribution in extending the science-based HFR products into societal relevant downstream services to support the blue growth in the Mediterranean coastal areas, helping to meet the UN’s Decade of Ocean Science for Sustainable Development and the EU’s Green Deal goals.

Due to the semi-enclosed nature of the Mediterranean Sea, natural disasters and anthropogenic activities impose stronger pressures on its coastal ecosystems than in any other sea of the world. With the aim of responding adequately to science priorities and societal challenges, littoral waters must be effectively monitored with High-Frequency radar (HFR) systems. This land-based remote sensing technology can provide, in near real-time, fine-resolution maps of the surface circulation over broad coastal areas, along with reliable directional wave and wind information. The main goal of this work is to showcase the current status of the Mediterranean HFR network and the future roadmap for orchestrated actions. Ongoing collaborative efforts and recent progress of this regional alliance are not only described but also connected with other European initiatives and global frameworks, highlighting the advantages of this cost-effective instrument for the multi-parameter monitoring of the sea state. Coordinated endeavours between HFR operators from different multi-disciplinary institutions are mandatory to reach a mature stage at both national and regional levels, striving to: i) harmonize deployment and maintenance practices; ii) standardize data, metadata and quality control procedures; iii) centralize data management, visualization and access platforms; iv) develop practical applications of societal benefit, that can be used for strategic planning and informed decision-making in the Mediterranean marine environment. Such fit-for-purpose applications can serve for search and rescue operations, safe vessel navigation, tracking of marine pollutants, the monitoring of extreme events or the investigation of transport processes and the connectivity between offshore waters and coastal ecosystems. Finally, future prospects within the Mediterranean framework are discussed along with a wealth of socio-economic, technical and scientific challenges to be faced during the implementation of this integrated HFR regional network.

In this paper, a high-frequency (HF) coastal radar network is described, which is established and maintained by the Institute of Marine Sciences (ISMAR) of the National Research Council of Italy (CNR) for the measurement of surface current velocities in the Gulf of Manfredonia, located in the semienclosed Adriatic Sea (Mediterranean Sea), during 2013–2015. The network consisted of four HF radars (HFRs) that provided hourly sea surface velocity data in real-time mode in a netCDF format compliant to the Climate and Forecast Metadata Conventions CF-1.6 and the INSPIRE directive. The hourly netCDF files are disseminated via a Thematic Real-time Environmental Distributed Data Services catalog supporting OGC compliant distributions and protocols for data visualization, metadata interrogation, and data download. HFR velocity data were compared with in situ velocity measurements by Global Positioning System tracked surface drifters deployed within the radar footprint. The results show a good agreement, with the root mean square (rms) of the difference between radial velocities from HFR and drifters ranging between $20\%$ and $50\%$ of the drifter velocity rms. The HFR data have also been compared with subsurface velocity profiles from an upward looking acoustic Doppler current profiler (ADCP) during winter 2015, to gain information on the correlation between surface and water column velocities. This information is especially relevant for fishery and coastal management applications, where transport of larvae, sediments, and pollutants in the water column are considered. Results show that, at least in the considered period, the velocity in the water column is well correlated, and there is a good agreement between surface HFR and ADCP data (correlations between 0.95 and 0.75). The Gulf of Manfredonia network has been instrumental to the set up of a core of quality control practices and interoperable data and metadata formats that have been subsequently adopted within the Italian RITMARE network and that are presently discussed and refined at the European level through the projects Jerico-NEXT and INCREASE.

Submesoscale instabilities along oceanic fronts can cause water mass intrusions from the surface mixed layer into the stratified pycnocline. These are important drivers of vertical exchange that have a potentially significant impact on the transfer of physical properties and biological tracers.The CALYPSO (Coherent Lagrangian Pathways from the Surface Ocean to Interior) ONR research initiative focuses on observing and understanding coherent vertical pathways by which vertical exchange occurs. The Alboran Sea (located in the south-western Mediterranean, east of Gibraltar) is well known for its strong density fronts and eddies. During a research cruise, onboard R/V Pourquoi Pas? in early April 2019, we found that fronts in this area support the generation of subducting filaments. Several types of observations (using CTD, uCTD, microstructure profiles, drifters and floats) were collected along numerous cross-front transects over a period of two weeks.The analysis of the temperature profiles highlighted the presence of several intruding filaments moving along isopycnal surfaces in the proximity of the frontal area. The intrusion signal was also clearly visible in biophysical properties with elevated Chlorophyll-a concentrations, well below the deep chlorophyll maximum, in conjunction with high dissolved oxygen values. From a microstructure point of view, the upper and lower limits of the subducting filaments exhibited high turbulent dissipation rates, with values of O(10-7) W/m2. These dissipation rates are higher than what is generally observed at such depths and point to enhanced mixing activity at the boundaries of the intrusions even along isopycnal surfaces.

The dynamics of the near-surface ocean currents result from the nonlinear interaction of simultaneous mechanisms at different scales. Of these, the submesoscale range (a few hundred meters to 10 km, hours to a few days) remains particularly challenging to observe directly, due to the high variability in both time and space. In this study, the scale-dependence of kinematic properties (divergence, vorticity and strain) in the submesoscale range, as well as their response to atmospheric forcing, is investigated in two distinct geographic regions: the Ligurian (NW-Mediterranean) Sea and the Northern Gulf of Mexico. The two applications are characterized by different dynamics, and the estimates of kinematic properties are derived from distinctly different observational approaches: in situ GPS drifters observations and remote HF radar data. The Ligurian Sea application is based on HF radar measurements obtained for the JERICO-NEXT (Joint European Research Infrastructure network for Coastal Observatory – Novel European eXpertise for coastal observaTories) and IMPACT (Port Impact on Protected Marine Areas: Cooperative Cross-Border Actions) projects. Surface current measurements span 40 km off the coast with 1.5 km resolution, available every hour. The velocity fields are used to estimate the kinematic properties with an Eulerian approach, which allows the identification of structures such as eddies and jets of the order of a few km. We focus in particular on the response of the submesoscales to an extreme wind event that was captured by the observations. The deformation of the spatial structures suggests nonlinear interactions with the wind forcing, and the kinematic properties' magnitudes are almost doubled (exceeding the Coriolis parameter, f). In the Gulf of Mexico, velocity observations are available from a series of massive, nearly simultaneous drifter releases conducted by CARTHE (Consortium for Advanced Research of Transport of Hydrocarbons in the Environment). Drifter triplets are analysed to estimate the kinematic properties of the flow at scales between 100 m and 5 km over a time scale of a day. Results show that the mean kinematic properties increase in magnitude with decreasing scales, with winter values generally higher than summer ones. For winter flows, vorticity and divergence distributions have more substantial tails of values multiple times the Coriolis paramater f at scales up to 2 km, while in the summer such large values are restricted to smaller scales (100-500 m). The Lagrangian estimates of kinematic properties obtained in the Gulf of Mexico were also compared to Eulerian estimates from concurrent X-band radar measurements, showing good correlation and validating the comparison across observational methods. Moreover, the scale-dependence of the kinematic properties from drifter triplets was found to be consistent with turbulence scaling laws evaluated as two-particle statistics. We conclude that the kinematic properties metric provides a robust complementary methodology to characterize submesoscales and can be used both with Lagrangian and Eulerian observations.

High Frequency Radar (HFR) technology refers to land based remote sensing instruments capable of measuring surface currents and ocean waves at ranges up to 200 km or more. HFR technology is widely acknowledged as a cost-efficient tool to monitor coastal regions and has potential use to monitor coastal regions all over the world. Globally, the number of HFR stations is steadily increasing. Regional networks provide real-time data in support of operational activities such as search and rescue operations, fast response in case of maritime accidents and spill of pollutants, and resource management. Each operator needs a general understanding of the working principles in order to ensure that instruments are managed properly. A set of harmonized quality assurance and quality control procedures is recommended, along with an effective approach to HFR data discovery and dissemination, to provide high quality measurements to the end users. Different documents providing best practices for operation and maintenance have emerged in the past years. They are oriented either to Direction Finding (DF) or Beam Forming (BF) systems, or to specific manufacturer’s radar systems. The main objective of this paper is to offer a comprehensive “Best Practices” document in an effort of ensuring consistency between different deployments and harmonized operations of HFR systems. This, regardless of system manufacturer, antenna design and setup. A homogeneous approach is given when possible, general concepts and definitions are introduced in order to provide a framework for both data processing and management steps. Examples are also given from the European HFR users with focus on Near Real Time data flow suitable for operational services.

The effective monitoring and understanding of the dynamics of coastal currents is crucial for the development of environmentally sustainable coastal activities in order to preserve marine ecosystems as well as to support marine and navigation safety. This need is driving the set-up of a growing number of multiplatform operational observing systems, aiming for the continuous monitoring of the coastal ocean. A significant percentage of the existing observatories is equipped with land-based high-frequency radars (HFRs), which provide real-time currents with high spatio-temporal coverage and resolutions. Several approaches have been used in the past to expand the surface current velocity measurements provided by HFR to subsurface levels, since this can expand the application of the technology to other fields, like marine ecology or fisheries. The possibility of obtaining 3D velocity current fields from the combination of data from HFRs with complementary data, such as the velocity current profiles provided by in situ acoustic Doppler current profiler (ADCP) moorings is explored here. To that end, two different methods to reconstruct the 3D current velocity fields are assessed by a standard approach conceptually similar to OSSEs (observing system simulation experiments), where 3D numerical simulations are used as true ocean in order to evaluate the performance of the data-reconstruction methods. The observations of currents from a HFR and ADCP moorings are emulated by extracting the corresponding data from the 3D true ocean, and used as input for the methods. Then, the 3D reconstructed fields (outputs of the methods) are compared to the true ocean to assess the skills of the data-reconstruction methods. These methods are based on different approaches: on the one hand, the reduced order optimal interpolation uses an approximation to the velocity covariances (which can be obtained from historical data or a realistic numerical simulation) and on the other hand, the discrete cosine transform penalized least square is based on penalized least squares regression that balances fidelity to the data and smoothness of the solution. This study, which is based on the configuration of a real observatory located in the south-eastern Bay of Biscay (SE-BoB), is a first step towards the application of the data-reconstruction methods to real data, since it explores their skills and limitations. In the SE-BoB, where the coastal observatory includes a long-range HFR and two ADCP moorings inside the HFR footprint area, the results show satisfactory 3D reconstructions with mean spatial (for each depth level) errors between 0.55 and 7 cm s−1 for the first 150 m depth and mean relative errors of 0.07–1.2 times the rms value for most of the cases. The data-reconstruction methods perform better in well-sampled areas, and both show promising skills for the 3D reconstruction of currents as well as for the computation of new operational products integrating complementary observations, broadening the applications of the in situ observational data in the study area.

Statistical properties of near‐surface horizontal velocity gradients are obtained from four drifter experiments conducted in the Gulf Mexico during Summer 2012 and Winter 2016. The data density provided by the near‐simultaneous deployments of 90‐326 surface drifters in each allows direct, drifter‐based estimates of the scale dependence of velocity gradients at separation scales ranging from 200 m to 5 km. The robustness of these estimates, derived from uniquley sampled, nearly equilateral triplets, is confirmed by comparisons with estimates produced from larger drifter clusters, and with estimates based on concurrent Eulerian X‐band radar observations. The winter launches were deployed above a ~80 m deep mixed layer, one in a region with nearly homogeneous horizontal density structure, the other in a region of strong surface density gradients associated with filaments of fresh Mississippi River water. The summer launches occurred in a shallow (10m) mixed layer, one launched across a mesoscale frontal jet separating regions of horizontally homogeneous density and the other, similar to the corresponding winter launch, also in a region filamented by shallow lenses of cold, fresh water. Seasonal differences are observed, with larger velocity fluctuations and greater variance in divergence and vorticity, especially at the smallest scales, in winter. Differences between same‐season launches are, however, as large as seasonal differences. In both seasons, observations sampling regions directly impacted by fresh water fluxes show strongly skewed vorticity distributions, with cyclonic vorticity dominating strain. For the other launches, one in each season, strain dominated minimally skewed vorticity.

Editors: Karina von Schuckmann; Pierre-Yves Le Traon.-- Review Editors: Neville Smith (Chair); Ananda Pascual; Samuel Djavidnia; Jean-Pierre Gattuso; Marilaure Grégoire; Glenn Nolan., The authors would like to thank the Institut Cartogràfic i Geològic de Catalunya (ICGC) for providing data. Thanks are due to FCT/MCTES for the financial support to CESAM (UID/AMB/50017/2019), through national funds., Chapter 1: Introduction and the European Environment policy framework.-- CMEMS OSR4, Chapter 2: State, variability and change in the ocean.-- CMEMS OSR4, Chapter 3: Case studies.-- CMEMS OSR4, Chapter 4: Specific events 2018.

Monitoring and investigating the dynamics of coastal currents is crucial for the development of environmentally sustainable coastal activities, in order to preserve marine ecosystems as well as to support marine and navigation safety. This need is driving the set-up of a growing number of multiplatform operational observing systems, aiming to the continuous monitoring of the coastal ocean. A significant percent of the existing observatories is today equipped with land-based High Frequency Radars (HFR), which provide real-time currents with unprecedent coverage and resolution, limited however, to the surface layer. The combination of data from HFR with complementary data from in-situ platforms providing information of the currents at subsurface layers (ADCP moorings) is investigated here to reconstruct the 3D current velocity field from in-situ observations. For this purpose, two methods based on different approaches are used. On the one hand, the Reduced Order Optimal Interpolation which is fed, in this case, with a spatial covariance matrix extracted from a realistic numerical oceanic simulation; and on the other hand, the Discrete Cosine Transform Penalized Least Square, which is a data gap-filling method based on penalized least squares regression that balances fidelity to the data and smoothness of the solution. As a proof of concept, we test the methods’ skills by using emulated observations of currents, extracted from a numerical simulation (3D reference field). The test set-up emulates the real observatory scenario in the study area (south-eastern Bay of Biscay), which includes a long-range HFR and two ADCP moorings inside the HFR footprint area. Then, the reconstructed fields (outputs of the methods) are compared with the 3D reference fields. In general, the results show satisfactory 3D reconstructions with mean spatial (for each depth level) errors between 0.55–10.94 cm s−1 for the first 150 m depth. The methods perform better in well sampled areas, and although different performances between the methods are observed, both show promising skills for the computation of new operational products integrating complementary observations, broadening the applications of in-situ observational data.

The fundamental role of the ocean for life and well-being on Earth is more and more recognised at the highest political level. In 2015, the United Nations (UN) Sustainable Development Goals (SDGs) of the 2030 Agenda for Sustainable Development were adopted by world leaders. The SDG 14 ‘Conserve and sustainably use the oceans, seas and marine resources for sustainable development’ is dedicated to the oceans. The mention of the ocean in the Paris Agreement signed in 2016 marked a decisive milestone. In 2018, the UN Decade of Ocean Science for Sustainable Development (2021–2030) has been proclaimed (https://en.unesco.org/ocean-decade): The Intergovernmental Oceanographic Commission of UNESCO will gather ocean stakeholders worldwide behind a common framework to foster evidence-based policy-making. In fall 2019, the IPCC special report on ocean and cryosphere will be published, and will provide an opportunity to increase awareness and action before COP251 (already claimed as ‘Blue COP’).

Academic, government, and private organizations from around the globe have established High Frequency radar (hereinafter, HFR) networks at regional or national levels. Partnerships have been established to coordinate and collaborate on a single global HFR network (http://global-hfradar.org/ ). These partnerships were established in 2012 as part of the Group on Earth Observations (GEO) to promote HFR technology and increase data sharing among operators and users. The main product of HFR networks are continuous maps of ocean surface currents within 200 km of the coast at high spatial (1-6 km) and temporal resolution (hourly or higher). Cutting-edge remote sensing technologies are becoming a standard component for ocean observing systems, contributing to the paradigm shift towards ocean monitoring. In 2017 the Global HFR Network was recognized by the Joint Technical WMO-IOC Commission for Oceanography and Marine Meteorology (JCOMM) as an observing network of the Global Ocean Observing System (GOOS). In this paper we will discuss the development of the network as well as establishing goals for the future. The U.S. High Frequency Radar Network (HFRNet) has been in operation for over thirteen years, with radar data being ingested from 31 organizations including measurements from Canada and Mexico. HFRNet currently holds a collection from over 150 radar installations totaling millions of records of surface ocean velocity measurements. During the past 10 years in Europe, HFR networks have been showing steady growth with over 60 stations currently deployed and many in the planning stage. In Asia and Oceania countries, more than 110 radar stations are in operation. HFR technology can be found in a wide range of applications: for marine safety, oil spill response, tsunami warning, pollution assessment, coastal zone management, tracking environmental change, numerical model simulation of 3-dimensional circulation, and research to generate new understanding of coastal ocean dynamics, depending mainly on each country's coastal sea characteristics. These radar networks are examples of national inter-agency and inter-institutional partnerships for improving oceanographic research and operations. As global partnerships grow, these collaborations and improved data sharing enhances our ability to respond to regional, national, and global environmental and management issues.

Very-near-surface ocean currents are dominated by wind and wave forcing and have large impacts on the transport of buoyant materials in the ocean. Surface currents, however, are under-resolved in most operational ocean models due to the difficultly of measuring ocean currents close to, or directly at, the air–sea interface with many modern instrumentations. Here, observations of ocean currents at two depths within the first meter of the surface are made utilizing trajectory data from both drogued and undrogued Consortium for Advanced Research on Transport of Hydrocarbon in the Environment (CARTHE) drifters, which have draft depths of 60 and 5 cm, respectively. Trajectory data of dense, colocated drogued and undrogued drifters were collected during the Lagrangian Submesoscale Experiment (LASER) that took place from January to March of 2016 in the northern Gulf of Mexico. Examination of the drifter data reveals that the drifter velocities become strongly wind- and wave-driven during periods of high wind, with the pre-existing regional circulation having a smaller, but non-negligible, influence on the total drifter velocities. During these high wind events, we deconstruct the total drifter velocities of each drifter type into their wind- and wave-driven components after subtracting an estimate for the regional circulation, which pre-exists each wind event. In order to capture the regional circulation in the absence of strong wind and wave forcing, a Lagrangian variational method is used to create hourly velocity field estimates for both drifter types separately, during the hours preceding each high wind event. Synoptic wind and wave output data from the Unified Wave INterface-Coupled Model (UWIN-CM), a fully coupled atmosphere, wave and ocean circulation model, are used for analysis. The wind-driven component of the drifter velocities exhibits a rotation to the right with depth between the velocities measured by undrogued and drogued drifters. We find that the average wind-driven velocity of undrogued drifters (drogued drifters) is ∼3.4 %–6.0 % (∼2.3 %–4.1 %) of the wind speed and is deflected ∼5–55∘ (∼30–85∘) to the right of the wind, reaching higher deflection angles at higher wind speeds. Results provide new insight on the vertical shear present in wind-driven surface currents under high winds, which have vital implications for any surface transport problem.

Accurate knowledge of ocean surface currents at high spatial and temporal resolutions is crucial for a gamut of applications. The altimeter observing system, by providing repeated global measurements of the sea surface height, has been by far the most exploited system to estimate ocean surface currents over the past 20 years. However, it neither permits the observation of currents moving away from the geostrophic balance nor is it capable of resolving the shortest spatial and temporal scales of the currents. Therefore, to overcome these limitations, in this study the ways in which the high-spatial-resolution and high-temporal-resolution information from sea surface temperature (SST) images can improve the altimeter current estimates are investigated. The method involves inverting the SST evolution equation for the velocity by prescribing the source and sink terms and employing the altimeter currents as the large-scale background flow. The method feasibility is tested using modeled data from the Mercator Ocean system. This study shows that the methodology may improve the altimeter velocities at spatial scales not resolved by the altimeter system (i.e., below 150 km) but also at larger scales, where the geostrophic equilibrium might not be the unique or dominant process of the ocean circulation. In particular, the major improvements (more than 30% on the meridional component) are obtained in the equatorial band, where the geostrophic assumption is not valid. Finally, the main issues anticipated when this method is applied using real datasets are investigated and discussed.

Surface drifters and virtual particles are used to investigate transport between seven coastal regions in the central and southern Adriatic Sea to estimate the degree to which these regions function as a network. Alongshore coastal currents and cyclonic gyres are the primary circulation features that connected regions in the Adriatic Sea. The historical drifter observations span 25 years and, thus, provide estimates of transport between regions realized by the mean surface circulation. The virtual particle trajectories and a dedicated drifter experiment show that southeasterly Sirocco winds can drive eastward cross-Adriatic transport from the Italian coast near the Gargano Promontory to the Dalmatian Islands in Croatia. Southeasterly winds disrupt alongshore transport on the west coast. Northwesterly Mistral winds enhanced east-to-west transport and resulted in stronger southeastward coastal currents in the western Adriatic current (WAC) and export to the northern Ionian Sea. The central Italian regions showed strong connections from north to south, likely realized by alongshore transport in the WAC. Alongshore, downstream transport was weaker on the east coast, likely due to the more complex topography introduced by the Dalmatian Islands of Croatia. Cross-Adriatic connection percentages were higher for east-to-west transport. Cross-Adriatic transport, in general, occurred via the cyclonic sub-gyres, with westward (eastward) transport observed in the northern (southern) arms of the central and southern gyres. (C) 2016 Elsevier Ltd. All rights reserved.

The variability and evolution of the Northern Current (NC) in the area off Toulon is studied for two weeks in December 2011 using data from a glider, a HF radar network, vessel surveys, a meteo station, and an atmospheric model. The NC variability is dominated by a synoptic response to wind events, even though a seasonal trend is also observed, transitioning from late summer to fall-winter conditions. With weak winds the current is mostly zonal and in geostrophic balance even at the surface, with a zonal transport associated to the NC of ≈ 1 Sv. Strong westerly wind events (longer than 2–3 days) induce an interplay between the direct wind induced ageostrophic response and the geostrophic component: upwelling is observed, with offshore surface transport, surface cooling, flattening of the isopycnals and reduced zonal geostrophic transport (0.5–0.7 Sv). The sea surface response to wind events, as observed by the HF radar, shows total currents rotated at ≈ −55° to −90° to the right of the wind. Performing a decomposition between geostrophic and geostrophic components of the surface currents, the wind driven ageostrophic component is found to rotate of ≈ −25° to −30° to the right of the wind. The ageostrophic component magnitude corresponds to ≈ 2 % of the wind speed.

This study investigates the results of blending altimetry-based surface currents in the Gulf of Mexico with available drifter observations. Here, subsets of trajectories obtained from the near-simultaneous deployment of about 300 Coastal Ocean Dynamics Experiment (CODE) surface drifters provide both input and control data. The fidelity of surface velocity fields are measured in the Lagrangian frame by a skill score that compares the separation between observed and hindcast trajectories to the observed absolute dispersion. Trajectories estimated from altimetry-based velocities provide satisfactory average results (skill score > 0.4) in large (~100 km) open-ocean structures. However, the distribution of skill score values within these structures is quite variable. In the DeSoto Canyon and on the shelf where smaller-scale structures are present, the overall altimeter skill score is typically reduced to less than 0.2. After 3 days, the dataset-averaged distance between hindcast and drifter trajectories, , is about 45 km—only slightly less than the average dispersion of the observations, km. Blending information from a subset of drifters via a variational method leads to significant improvements in all dynamical regimes. Skill scores typically increase to 0.8 with reduced to less than half of . Blending available drifter information with altimetry data restores velocity field variability at scales not directly sampled by the altimeter and introduces ageostrophic components that cannot be described by simple Ekman superposition. The proposed method provides a means to improve the fidelity of near-real-time synoptic estimates of ocean surface velocity fields by combining altimetric data with modest numbers of in situ drifter observations.

This paper is an extended version of the conference paper, Marini et al., An Autonomous Imaging System for Argo Floats, IMEKO International Conference on Metrology for The Sea, 11-13 October, Naples-Italy.-- 4 pages, 4 figures, Many technologies have been developed for monitoring the ocean interior. Among them the monitoring approaches based on imaging devices are capable to disclose important data on species behaviour and spatio-temporal variations of richness and evenness. In this context, the Argo programme (http://doi.org/10.17882/42182) is a valuable instrument for monitoring the deep sea at global scale in space and time. Argo floats equipped with imaging devices are candidate to become a new monitoring tool for studying macro- and mega-fauna in large areas and for extended time periods, potentially providing monitoring results never attained before. This work summarises the results obtained on the automated fish recognition task performed on the images acquired by the GUARD1 imaging device, This work was partially supported by the TISANA project within the Argo Italy programme and by the project FixO3 (FP7/2013-2017) under the grant agreement nº 312463, through the TNA project FISHAUT

To develop methodologies to maximize the information content of Lagrangian data subject to position errors, synthetic trajectories produced by both a large-eddy simulation (LES) of an idealized submesoscale flow field and a high-resolution Hybrid Coordinate Ocean Model simulation of the North Atlantic circulation are analyzed. Scale-dependent Lagrangian measures of two-particle dispersion, mainly the finite-scale Lyapunov exponent [FSLE; λ(δ)], are used as metrics to determine the effects of position uncertainty on the observed dispersion regimes. It is found that the cumulative effect of position uncertainty on λ(δ) may extend to scales 20–60 times larger than the position uncertainty. The range of separation scales affected by a given level of position uncertainty depends upon the slope of the true FSLE distribution at the scale of the uncertainty. Low-pass filtering or temporal subsampling of the trajectories reduces the effective noise amplitudes at the smallest spatial scales at the expense of limiting the maximum computable value of λ. An adaptive time-filtering approach is proposed as a means of extracting the true FSLE signal from data with uncertain position measurements. Application of this filtering process to the drifters with the Argos positioning system released during the LatMix: Studies of Submesoscale Stirring and Mixing (2011) indicates that the measurement noise dominates the dispersion regime in λ for separation scales δ < 3 km. An expression is provided to estimate position errors that can be afforded depending on the expected maximum λ in the submesoscale regime.

The general aim of this paper is to present a possible multidisciplinary approach to the problem of connectivity among marine protected areas (MPAs) describing some of the mechanisms and vectors that control the dispersal of propagules among spatially distributed marine communities of MPAs in the Southern Adriatic Sea. A joint approach is described that focuses on (a) measurements of surface water current and model data integrated with a dedicated software (LAVA, LAgrangian Variational Analysis), (b) measurements of rafting objects and their evaluation as an alternative way to species dispersal, and (c) a tool to automatically monitor propagules and plankton species in the water column. Studies on the dynamics of water currents demonstrated that the Gargano area has the potential to supply dispersal propagules to the Southern Adriatic both along the Italian coastline and offshore across the basin, thus providing important services to the dispersal processes and the connectivity routes among MPAs. The natural dispersion is however enhanced by floating objects, on which entire marine communities are living and travelling. The number of these objects has greatly increased with the introduction of human litter: in the Adriatic, man-made litter composes nowadays the majority (79 %) of all floating objects, with this corresponding to an almost fourfold increase in the abundance of floating objects since pre-industrial times. Such enhanced dispersion may benefit transmission of propagules from MPAs along biodiversity corridors, but may also enhance the arrival of invasive species. The direct observation of organisms can provide information on the species distribution and mobility. New technology (GUARD-1 system) has been developed to automatically identify spatial or temporal distributions of selected species in the water column by image analysis. The system has so far successfully detected blooms of ctenophores in the water column and is now being tested for identification of other zooplankton groups, such as copepods, as well as marine litter. This low-cost, long-lasting imaging system can be hosted on mobile devices such as drifters, which makes it very suitable for biological dispersal studies.

Ocean prediction systems rely on an array of assumptions to optimize their data assimilation schemes. Many of these remain untested, especially at smaller scales, because sufficiently dense observations are very rare. A set of 295 drifters deployed in July 2012 in the north-eastern Gulf of Mexico provides a unique opportunity to test these systems down to scales previously unobtainable. In this study, background error covariance assumptions in the 3DVar assimilation process are perturbed to understand the effect on the solution relative to the withheld dense drifter data. Results show that the amplitude of the background error covariance is an important factor as expected, and a proposed new formulation provides added skill. In addition, the background error covariance time correlation is important to allow satellite observations to affect the results over a period longer than one daily assimilation cycle. The results show the new background error covariance formulations provide more accurate placement of frontal positions, directions of currents and velocity magnitudes. These conclusions have implications for the implementation of 3DVar systems as well as the analysis interval of 4DVar systems. Published by Elsevier Ltd.

2014 International Oil Spill Conference CARTHE (http://carthe.org/) is a Gulf of Mexico Research Initiative (GoMRI) consortium established through a competitive peer-reviewed selection process. CARTHE comprises 26 principal investigators from 14 universities and research institutions distributed across four Gulf of Mexico states and other four states. It fuses into one group investigators with unique scientific and technical knowledge and extensive publications related to oil fate/transport processes, oceanic and atmospheric turbulence, air-sea interactions, tropical cyclones and winter storms, and coastal and nearshore modeling and observations. Our primary goal is to accurately predict the fate of hydrocarbons released into the environment. Achieving this goal is particularly challenging since petroleum releases into the environment interact with natural processes across six orders of magnitude of time and space scales. We are developing a multi-scale modeling tool by incorporating state-of-the-art hydrophysical models, each applicable for a restricted range of scales, into a single, interconnected modeling system to predict the physical dispersal of hydrocarbons across scales ranging from the microscale at the wellhead to oceanic and atmospheric mesoscales. CARTHE is also conducting novel in-situ observations and laboratory experiments specifically designed for quantifying submesoscale dispersion as well as for both model validation and parameterization. Finally, we are providing a robust set of uncertainty metrics and analysis tools to assess model performance and quantify predictive uncertainty. This research was made possible by a grant from BP/The Gulf of Mexico Research Initiative. This research was made possible by a grant from BP/The Gulf of Mexico Research Initiative.

Barrier layers are generated when the surface mixed layer is shallower than the layer where temperature is well mixed, in geographical regions where salinity plays a key role in setting up upper-ocean density stratification. In the tropical oceans, thick barrier layers are also found in a latitude range where spiraling trajectories from surface in situ drifters suggest the presence of predominantly cyclonic submesoscale-like vortices. The authors explore these dynamical processes and their interplay in the present paper, focusing on the tropical South Atlantic Ocean and using a high-resolution modeling approach. The objective is threefold: to investigate the mean dynamics contributing to barrier-layer formation in this region, to study the distribution and seasonality of submesoscale features, and to verify whether and how the submesoscale impacts barrier-layer thickness. The model used is the Regional Ocean Modeling System (ROMS) in its Adaptive Grid Refinement in Fortran (AGRIF) online-nested configuration with a horizontal resolution ranging between 9 and 1 km. The simulated circulation is first described in terms of mean and submesoscale dynamics, and the associated seasonal cycle. Mechanisms for barrier-layer formation are then investigated. The results confirm previous hypotheses by Mignot et al. on the relevance of enhanced winter mixing deepening the isothermal layer, whereas the salinity stratification is sustained by advection of surface fresh waters and subsurface salinity maxima. Finally, submesoscale effects on barrier-layer thickness are studied, quantifying their contribution to vertical fluxes of temperature and salinity. Submesoscale vortices associated with salinity fronts are found to have a significant effect, producing thicker barrier layers (by ~20%–35%) and a shallower mixed layer because of their restratifying effect on salinity.

International audience; High Frequency Radar (HFR) is a land-based remote sensing instrument offering a unique insight to coastal ocean variability, by providing synoptic, high frequency and high resolution data at the ocean atmosphere interface. HFRs have become invaluable tools in the field of operational oceanography for measuring surface currents, waves and winds, with direct applications in different sectors and an unprecedented potential for the integrated management of the coastal zone. In Europe, the number of HFR networks has been showing a significant growth over the past 10 years, with over 50 HFRs currently deployed and a number in the planning stage. There is also a growing literature concerning the use of this technology in research and operational oceanography. A big effort is made in Europe toward a coordinated development of coastal HFR technology and its products within the framework of different European and international initiatives. One recent initiative has been to make an up-to-date inventory of the existing HFR operational systems in Europe, describing the characteristics of the systems, their operational products and applications. This paper offers a comprehensive review on the present status of European HFR network, and discusses the next steps toward the integration of HFR platforms as operational components of the European Ocean Observing System, designed to align and integrate Europe’s ocean observing capacity for a truly integrated end-to-end observing system for the European coasts.

Ocean model fields are being routinely used for forecasting the spreading of pollutants, oil spills, and for biogeochemical transport. Recent observations and advances in our understanding of ocean processes indicate there is an explosion of flow instabilities in the submesoscale range. While submesoscale flows have a significant impact on transport at their own scales, they require much more extensive data sets and numerical computations. Therefore, transport carried out by submesoscale flows is quite challenging to approach deterministically. In this study, we put forward a hybrid approach by combining deterministic Lagrangian coherent structures (LCS) to compute transport over the mesoscale range with statistical Lagrangian subgridscale (LSGS) models for the underresolved submesoscale motions. We apply this approach to particle transport in the Gulf Stream region, which exhibits indications of submesoscale activity from both models and observations. We consider HYCOM solutions at two resolutions. In the 1/12° computation, mesoscale features are well resolved but submesoscales are not resolved, while the 1/48° computation captures some of the submesoscale flow instabilities as well. By using metrics of relative dispersion, we investigate three LSGS models and demonstrate that they can be useful in correcting the underestimation of submesoscale dispersion in the 1/12° solution, with respect to relative dispersion obtained from the 1/48° solution and an observational result.

Relative dispersion in the Liguro-Provencal basin (a subregion of the Mediterranean Sea) is investigated using clusters of surface drifters deployed during two Marine Rapid Environment Assessment (MREA) experiments covering different months in 2007 and 2008, respectively. The clusters have initial radii of less than 1 km, or an order of magnitude below a typical deformation radius (approximately 10–20 km). The data set consists of 45 original pairs and more than 50 total pairs (including chance ones) in the spatial range between 1 and 200 km. Relative dispersion is estimated using the mean square separation of particle pairs and the Finite Scale Lyapunov Exponents (FSLEs). The two metrics show broadly consistent results, indicating in particular a clear exponential behaviour with an e-folding time scale between 0.5 and 1 days, or Lyapunov exponent λ in the range of 0.7–1 days−1. The exponential phase extends for 4–7 days in time and between 1 and 10–20 km in separation space. To our knowledge, this is only the third time that an exponential regime is observed in the world ocean from drifter data. This result suggests that relative dispersion in the Liguro-Provencal basin is nonlocal, namely controlled mainly by mesoscale dynamics, and that the effects of the sub-mesoscale motions are negligible in comparison. NCOM model results are used to complement the data and to quantify errors arising from the sparse sampling in the observations.

This numerical study focuses on the response of the Western Adriatic Current to wind forcing. The turbulent buoyant surface current is induced by the Po river outflow in the Adriatic Sea. Idealized and realistic wind conditions are considered by retaining the complex geomorphology of the middle Adriatic basin. In the absence of wind, the Adriatic Promontories force the current to separate from the coast and induce instabilities. Persistent 7-m s-1 downwelling favorable northwesterly winds thicken and narrow the current. Instabilities whose size is similar to 10 km develop but ultimately vanish, since there is not enough across-shore space to grow. On the contrary, 7-m s-1 upwelling favorable southeasterly winds thin and widen the current, and instabilities can grow to form mesoscale (~ 35 km) features. When realistic winds are considered, the same trends are observed, but the state of the sea set up by previous wind events also plays a crucial role. The turbulent regimes set up by different winds affect mixing and the WAC meridional transport. With downwelling winds, the transport is generally southward and mixing happens mostly between the fresher (S 38) waters. In all cases, mixing is enhanced when a finer 0.5-km horizontal resolution is employed.

Triangle shape metrics are analyzed to quantify the evolution of submesoscale (100-500 m initial separation) surface drifter triplets released in the northern Gulf of Mexico. The observations are compared to synthetic drifters advected by geostrophic velocity fields derived from satellite altimetry. Observed submesoscale triads evolve rapidly, reaching highly-elongated configurations on timescales of 6 hours to 2 days, in contrast to 6 days or longer for altimetry-derived synthetic data. Estimates of horizontal divergence and strain rate from the drifter triplets indicate the relative importance of divergence in the evolution of triangle shape. Horizontal divergence is scale-dependent, on the order of the local Coriolis parameter, and 2 to 3 times larger for initial 100-m scales compared to initial 500-m scales.

In this paper, a method to analyze historical surface drifter data is presented that is aimed at investigating particle evolution as a function of initial conditions. Maps of drifter concentration at different times are built and interpreted as maps of the probability of finding a particle at a given time in the neighborhood of a given point in the domain. A case study is considered in a coastal area of the middle Adriatic Sea (a subbasin of the Mediterranean Sea) around the Gargano Cape, which is the focus of a newly planned experiment, the Dynamics of the Adriatic in Real Time (DART). A specific application is considered that seeks to improve the DART Lagrangian sampling planning. The results indicate that the analysis of historical drifters can provide very valuable information on statistical particle prediction to be used in experiment design. In the DART region, particle dynamics appear mostly controlled by the upstream properties of the boundary current as well as by the presence of a stagnation point located offshore of the tip of Gargano and separating two cross-basin recirculations. A significant seasonal dependence is observed, with drifters being more likely to leave the boundary current in winter and fall, when the current is wider and more connected to the cross-basin recirculations. Future developments are discussed, including joint analyses with numerical model results.

Lucio Bellomo et al., High-frequency (HF) coastal radars measure current velocity at the ocean surface with a 30-100 km range and 1-3 km resolution, every 0.25-1 h. HF radars are well suited to many applications, such as search and rescue (SaR), oil-spill mitigation and ecosystem management. Here we present a first organized core of 12 HF radars installed in five sites in four countries (Greece, Italy, France and Spain) within the European MED project, the Tracking Oil Spill and Coastal Awareness (TOSCA) network. Dedicated experiments tested radar capabilities to estimate transport driven by currents, which is the key feature for all the above applications. Experiments involved the deployment of drifters, i.e., floating buoys, acting as proxies for substances passively advected by currents. Using HF radars the search range is reduced by a factor of 1.6 to 5.3 after 24 h. The paper also underlines the importance of sharing common tools for HF radar data processing and the need to mitigate radio frequency interference. The effort can be regarded as an initial step toward the creation of a Mediterranean or European HF radar network, crucial for any European integrated ocean observing system (IOOS)., This work was supported by the Tracking Oil Spills and Coastal Awareness (TOSCA) Network project [grant number 2G-MED09-425], co-financed by the European Regional Development Fund in the framework of the MED programme

A method for the reconstruction of the mesoscale Eulerian velocity field based on Lagrangian data at given sampling period is presented. A variational approach is used, where information on the float positions are combined with a simple model constraint describing the motion of particles advected in a velocity field. The velocity field of a priori specified space scale is estimated minimizing a cost function which measures the distance between the observed float positions and the model predicted ones for each sampling period. The method is first implemented considering the time-independent approximation of the velocity correction during a time interval shorter than the typical time scale of the mesoscale field. In a second step, this approximation is relaxed to consider inertial oscillations superimposed on the mesoscale field. The method is tested on a numerical regional circulation on the Northwestern Mediterranean Sea, characterized by an Eulerian time scale significantly longer than the inertial period. The observational coverage of the region varies between 80% and 16% and the corresponding error in the velocity reconstruction varies from less than 10% to approximately 50%, with a sampling period of the day. For smaller sampling intervals, the reconstruction is further improved in the time-dependent approximation. Finally, the method is used to combine information from Lagrangian data and General Circulation Models. The results suggest the useful application of the method for assimilation studies.

A study of the mesoscale eddy field in the presence of coherent vortices, by means of Lagrangian trajectories released in a high-resolution ocean model, is presented in this paper. The investigation confirms previous results drawn from real float data statistics (Veneziani et al., 2004) that the eddy field characteristics are due to the superposition of two distinct regimes associated with strong coherent vortices and with a typically more quiescent background eddy flow. The former gives rise to looping trajectories characterized by subdiffusivity properties due to the trapping effect of the vortices, while the latter produces nonlooping floats characterized by simple diffusivity features. Moreover, the present work completes the study by Veneziani et al. (2004) in regard to the nature of the spin parameter , which was used in the Lagrangian stochastic model that best described the observed eddy statistics. The main result is that the spin obtained from the looping trajectories not only represents a good estimate of the relative vorticity of the vortex core in which the loopers are embedded, but it is also able to follow the vortex temporal evolution. The Lagrangian parameter is then directly connected to the underlying Eulerian structure and could be used as a proxy for the relative vorticity field of coherent vortices.

Because of the increases in the realism of OGCMs and in the coverage of Lagrangian datasets in most of the world's oceans, assimilation of Lagrangian data in OGCMs emerges as a natural avenue to improve ocean state forecast with many potential practical applications, such as environmental pollutant transport, biological, and naval-related problems. In this study, a Lagrangian data assimilation method, which was introduced in prior studies in the context of single-layer quasigeostrophic and primitive equation models, is extended for use in multilayer OGCMs using statistical correlation coefficients between velocity fields in order to project the information from the data-containing layer to the other model layers. The efficiency of the assimilation scheme is tested using a set of twin experiments with a three-layer model, as a function of the layer in which the floats are launched and of the assimilation sampling period normalized by the Lagrangian time scale of motion. It is found that the assimilation scheme is effective provided that the correlation coefficient between the layer that contains the data and the others is high, and the data sampling period Δt is smaller than the Lagrangian time scale TL. When the assimilated data are taken in the first layer, which is the most energetic and is characterized by the fastest time scale, the assimilation is very efficient and gives relatively low errors also in the other layers (≈ 40% in the first 120 days) provided that Δt is small enough, Δt << TL. The assimilation is also efficient for data released in the third layer (errors < 60%), while the dependence on Δt is distinctively less marked for the same range of values, since the time scales of the deeper layer are significantly longer. Results for the intermediate layer show a similar insensitivity to Δt, but the errors are higher (exceeding 70%), because of the lower correlation with the other layers. These results suggest that the assimilation of deep-layer data with low energetics can be very effective, but it is strongly dependent on layer correlation. The methodology also remains quite robust to large deviations from geostrophy.

Results from visual sightings of large floating debris are presented, taken in the Ligurian Sea, a sub-basin of the north-western Mediterranean Sea which belongs to the recently stated ‘‘Cetacean Sanctuary’’. Data have been collected during three oceanographic cruises, during the summer of 1997 and 2000. Results for the 1997 data suggest a debris density of the order of 15–25 objects km � 2 , while for the 2000 data, a lower density of the order of 3–1.5 objects km � 2 is found. The difference between the two results appears statistically significant using simple tests. Possible reasons for the observed variability are discussed, including meteorological forcing, marine currents and debris input variability. 2003 Elsevier Ltd. All rights reserved.

In the summer and fall of 2012, during the GLAD experiment in the Gulf of Mexico, the Consortium for Advanced Research on Transport of Hydrocarbon in the Environment (CARTHE) used several ocean models to assist the deployment of more than 300 surface drifters. The Navy Coastal Ocean Model (NCOM) at 1 km and 3 km resolutions, the US Navy operational NCOM at 3 km resolution (AMSEAS), and two versions of the Hybrid Coordinates Ocean Model (HYCOM) set at 4 km were running daily and delivering 72-h range forecasts. They all assimilated remote sensing and local profile data but they were not assimilating the drifter’s observations. This work presents a non-intrusive methodology named Multi-Model Ensemble Kalman Filter that allows assimilating the local drifter data into such a set of models, to produce improved ocean currents forecasts. The filter is to be used when several modeling systems or ensembles are available and/or observations are not entirely handled by the operational data assimilation process. It allows using generic in situ measurements over short time windows to improve the predictability of local ocean dynamics and associated high-resolution parameters of interest for which a forward model exists (e.g. oil spill plumes). Results can be used for operational applications or to derive enhanced background fields for other data assimilation systems, thus providing an expedite method to non-intrusively assimilate local observations of variables with complex operators. Results for the GLAD experiment show the method can improve water velocity predictions along the observed drifter trajectories, hence enhancing the skills of the models to predict individual trajectories.