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As part of the Copernicus Marine Service, WAVERYS is the multi-year wave reanalysis that provides global wave data with a fine grid resolution of 1/5°. This wave reanalysis covers the period 1993–2019 and disseminates 3-h integrated wave parameters describing the sea state at the ocean surface. The wave model used is the version 4 of the model MFWAM, which is driven by sea ice fraction and wind provided by the atmospheric reanalysis ERA5. The WAVERYS includes the assimilation of altimeter wave data and directional wave spectra provided by Sentinel-1. The wave reanalysis includes also wave-current interactions by using 3-h surface current forcing provided by the ocean reanalysis GLORYS. This paper highlights the assessment of wave parameters provided by the WAVERYS. The validation has been performed with independent altimeter significant wave heights and buoy wave data. The results show the good accuracy of scatter index of SWH (significant wave height) which is 8.7% in comparison with HY-2A altimeter. Moreover, we point out that scatter index of SWH from the WAVERYS is improved by about 9% with respect to the ERA5 wave dataset. We also indicate the good accuracy of swell propagation thanks to the assimilation of directional wave spectra. An analysis has been conducted for wave-current interactions and also discussions about extreme values and trend of time series are suggested.

As part of the Copernicus Marine Core service, WAVERYS is the multi-year wave reanalysis that aims to provide global wave data with a grid resolution of 1/5°. The wave reanalysis covers the period of 1993-2018 and provides 3-hourly classical integrated wave parameters describing the sea state at the ocean surface. The wave model used is the V4 version of the model MFWAM, which is driven by atmospheric forcing (winds and ice fraction) from ECMWF ERA5 reanalysis. This latter has showed a significant improvement regarding to the previous reanalysis ERA-Interim. WAVERYS includes the assimilation of altimeters wave data available during the period starting from Topex-Poseidon until Sentinel-3A missions. Directional wave spectra from Synthetic Aperture Radar (SAR) of Sentinel-1A and 1B missions are also assimilated. This is the first time that such directional wave spectra are used in a global wave reanalysis.Further, WAVERYS uses a 3 hour surface current forcing provided by ocean reanalysis GLORYS12 implemented by Mercator-Ocean in the frame of Copernicus Marine Service with a grid resolution of 1/12°. The wave reanalysis is high skilled for ocean regions with dominant wave-currents interactions. Preliminary validation tests have shown improvement by 15% in scatter index for large scale high currents areas. This paper will give detailed characteristics of the wave system and will insist on the benefits of taking into account ocean currents and a physics calibrated for realistic swell propagation.

The operational production of data-assimilated biogeochemical state of the ocean is one of the challenging core projects of the Copernicus Marine Environment Monitoring Service (hereafter CMEMS). In that framework, Mercator Ocean International is in charge of improving the realism of its global 1⁄4° coupled physical-biogeochemical simulations, analyses and re‐analyses, and to develop an effective capacity to routinely estimate the biogeochemical state of the ocean, including, amongst others, the implementation of biogeochemical data assimilation. Primary objectives are to enhance the time representation of the seasonal cycle in the real time and reanalysis systems, and to provide a better control of the production in the equatorial regions.In that framework, Mercator Ocean International has successfully updated its global biogeochemical analysis and forecasting system with an Ocean Color data assimilation capability. In this system, successfully commissioned in September 2019, the biogeochemical model (NEMO/PISCES) is offline coupled with the dynamical ocean (1/12° coarsened to 1/4° resolution) from the CMEMS global physical analysis and forecasting operational system (PSY4), at a daily frequency, and benefits from the assimilation of satellite (SSH-SST-SIC) and in situ physical data. Nevertheless, a biogeochemical climatological damping is activated in the biogeochemical model in order to mitigate the impact of some misconstrained processes (vertical velocities) from this physical data-assimilated forcing (under investigation). The dedicated assimilation of biogeochemical data relies on a simplified version of the SEEK filter, where the forecast error covariances are built from a fixed-basis - but seasonally variable - ensemble of anomalies computed from a multi-year numerical experiment (without biogeochemical data assimilation) with respect to a running mean. Regarding Ocean Colour observations, the system relies, as a first step, on the CMEMS Global Ocean surface chlorophyll concentration products, delivered in NRT.The objective of this presentation is thus to provide (1) a short description of the implementation of the aforementioned data assimilation methodology in the forecasting system; (2) a synthesis of the assessment of this global biogeochemical forecasting system, by cross-comparing the assimilated solution with various datasets, both spatial (Ocean Colour) and in situ (BGC-Argo, GLODAP), and (3) a synthetic overview of the impact/benefit of the assimilation of the Ocean Colour data.

Since 2016, the Copernicus Marine Environment Monitoring Service (CMEMS) has produced and disseminated an ensemble of four global ocean reanalyses produced at eddy-permitting resolution for the period from 1993 to present, called GREP (Global ocean Reanalysis Ensemble Product). This dataset offers the possibility to investigate the potential benefits of a multi-system approach for ocean reanalyses, since the four reanalyses span by construction the same spatial and temporal scales. In particular, our investigations focus on the added value of the information on the ensemble spread, implicitly contained in the GREP ensemble, for temperature, salinity, and steric sea level studies. It is shown that in spite of the small ensemble size, the spread is capable of estimating the flow-dependent uncertainty in the ensemble mean, although proper re-scaling is needed to achieve reliability. The GREP members also exhibit larger consistency (smaller spread) than their predecessors, suggesting advancement with time of the reanalysis vintage. The uncertainty information is crucial for monitoring the climate of the ocean, even at regional level, as GREP shows consistency with CMEMS high-resolution regional products and complement the regional estimates with uncertainty estimates. Further applications of the spread include the monitoring of the impact of changes in ocean observing networks; the use of multi-model ensemble anomalies in hybrid ensemble-variational retrospective analysis systems, which outperform static covariances and represent a promising application of GREP. Overall, the spread information of the GREP product is found to significantly contribute to the crucial requirement of uncertainty estimates for climatic datasets.

International audience; This study presents a water mass analysis along the JC150 section in the subtropical North Atlantic, based on hydrographic and nutrient data, by combining an extended optimum multiparameter analysis (OMPA) with a Lagrangian particle tracking experiment (LPTE). This combination, which was proposed for the first time, aided in better constraining the OMPA end-member choice and providing information about their trajectories. It also enabled tracing the water mass origins in surface layers, which cannot be achieved with an OMPA. The surface layers were occupied by a shallow type of Eastern South Atlantic Central Water (ESACW) with traces of the Amazon plume in the west. Western North Atlantic Central Water dominates from 100 to 500 m, while the 13 °C-ESACW contribution occurs marginally deeper (500–900 m). At approximately 700 m, Antarctic Intermediate Water (AAIW) dominates the west of the Mid-Atlantic Ridge (MAR), while Mediterranean Water dominates the east with a small but non-negligible contribution down to 3500 m. Below AAIW, Upper Circumpolar Deep Water (UCDW) is observed throughout section (900–1250 m). Labrador Sea Water (LSW) is found centered at 1500 m, where the LPTE highlights an eastern LSW route from the eastern North Atlantic to the eastern subtropical Atlantic, which was not previously reported. North East Atlantic Deep Water (encompassing a contribution of Iceland-Scotland Overflow Water) is centered at ~2500 m, while North West Atlantic Bottom Water (NWABW, encompassing a contribution of Denmark Strait Overflow Water) is principally localized in the west of the MAR in the range of 3500–5000 m. NWABW is also present in significant proportions (>25%) in the east of the MAR, suggesting a crossing of the MAR possibly through the Kane fracture zone. This feature has not been investigated so far. Finally, Antarctic Bottom Water is present in deep waters throughout the section, mainly in the west of the MAR. Source waters have been characterized from GEOTRACES sections, which enables estimations of trace elements and isotope transport within water masses in the subtropical North Atlantic.

Subtropical gyres are the oceanic regions where plastic litter accumulates over long timescales, exposing surrounding oceanic islands to plastic contamination, with potentially severe consequences on marine life. Islands’ exposure to such contaminants, littered over long distances in marine or terrestrial habitats, is due to the ocean currents that can transport plastic over long ranges. Here, this issue is addressed for the Easter Island ecoregion (EIE). High-resolution ocean circulation models are used with a Lagrangian particle-tracking tool to identify the connectivity patterns of the EIE with industrial fishing areas and coastline regions of the Pacific basin. Connectivity patterns for “virtual” particles either floating (such as buoyant macroplastics) or neutrally-buoyant (smaller microplastics) are investigated. We find that the South American shoreline between 20°S and 40°S, and the fishing zone within international waters off Peru (20°S, 80°W) are associated with the highest probability for debris to reach the EIE, with transit times under 2 years. These regions coincide with the most-densely populated coastal region of Chile and the most-intensely fished region in the South Pacific. The findings offer potential for mitigating plastic contamination reaching the EIE through better upstream waste management. Results also highlight the need for international action plans on this important issue.

The global high resolution monitoring and forecasting system PSY4 at Mercator Ocean, initialized in October 2006, has achieved 11 years of global ocean state estimation. Based on the NEMO global 1/12° configuration, PSY4 includes data assimilation of satellite and multi-instrument in situ observations. In parallel to this monitoring system, a twin-free simulation (with no assimilation) has been performed for the period 2007–2015. In this study, monthly-averaged fields of both ocean state estimates are compared with observation products for the period 2007–2015, to examine the consistency of PSY4 fields with related observations for representing large-scale variability and to provide a baseline that is mainly focused on in situ comparisons for validation/qualification of on-going system developments. Observations play a major role in correctly positioning the main energetic structures, both in space and time. In addition, data assimilation appears to overcome the other deficiencies of models by reducing SST bias in upwelling regions and by increasing the thermocline gradient in the tropics. Generally, the amplitude of the total-resolved variability in both PSY4 estimates is consistent with observation data sets. Annual cycle and longer-term variability in temperature, salinity and sea surface height are significantly improved with data assimilation, but some progress is still needed to better represent the amplitude of changes of ocean heat and freshwater contents on long timescales. Finally, the PSY4 system's ability to capture the large scale variability is further investigated by using as a case study the northward pathways of El Nino anomalies in the tropical North Pacific in 2014 and 2015 in order to illustrate how such systems can be used to answer relevant scientific questions.

A super-ensemble methodology is proposed to improve the quality of short-term ocean analyses for Sea Surface Temperature (SST) in the Mediterranean Sea. The methodology consists in a multi-linear regression technique applied to a Multi-Physics Multi-Model Super-Ensemble (MMSE) dataset. This is a collection of different operational forecasting analyses together with ad-hoc simulations, created by modifying selected numerical model parameterizations. A new linear regression algorithm based on Empirical Orthogonal Function filtering techniques is shown to be efficient in preventing overfitting problems, although the best performance is achieved when a simple spatial filter is applied after the linear regression. Our results show that the MMSE methodology improves the ocean analysis SST estimates with respect to the Best Ensemble Member (BEM) and that the performance is dependent on the selection of an unbiased operator and the length of training. The quality of the MMSE dataset has the largest impact on the MMSE analysis Root Mean Square Error (RMSE) evaluated with respect to observed satellite SST. The MMSE analysis estimates are also affected by changing the training period with the longest period leading to the smoothest estimates. Finally, lower RMSE analysis estimates result from the following: a 15 day training period, an overconfident MMSE dataset (a subset with the higher quality ensemble members), and the least square algorithm being filtered a posteriori.

Since October 19, 2016, and in the framework of Copernicus Marine Environment Monitoring Service (CMEMS), Mercator Ocean delivers in real-time daily services (weekly analyses and daily 10-day forecasts) with a new global 1/12° high resolution (eddy-resolving) monitoring and forecasting system. The model component is the NEMO platform driven at the surface by the IFS ECMWF atmospheric analyses and forecasts. Observations are assimilated by means of a reduced-order Kalman filter with a 3D multivariate modal decomposition of the forecast error. Along track altimeter data, satellite sea surface temperature, sea ice concentration and in situ temperature and salinity vertical profiles are jointly assimilated to estimate the initial conditions for numerical ocean forecasting. A 3D-VAR scheme provides a correction for the slowly-evolving large-scale biases in temperature and salinity. This paper describes the recent updates applied to the system and discusses the importance of fine tuning of an ocean monitoring and forecasting system. It details more particularly the impact of the initialization, the correction of precipitation, the assimilation of climatological temperature and salinity in the deep ocean, the construction of the forecast error covariance and the adaptive tuning of observations error on increasing the realism of the analysis and forecasts. The scientific assessment of the ocean estimations are illustrated with diagnostics over some particular years, assorted with time series over the time period 2007–2016. The overall impact of the integration of all updates on the products quality is also discussed, highlighting a gain in performance and reliability of the current global monitoring and forecasting system compared to its previous version.

Operational evolution of global and regional ocean forecasting systems has been extremely significant in recent years. Global Ocean Data Assimilation Experiment (GODAE) Oceanview supports the natio...

The availability of GODAE Oceanview-type ocean forecast systems provides the opportunity to develop high-resolution, short- to medium-range coupled prediction systems. Several groups have undertake...

Operational systems operated by Mercator Ocean provide daily ocean forecasts, and combining these forecasts we can produce ensemble forecast and uncertainty estimates. This study focuses on the mixed-layer depth in the Northeast Atlantic near the Porcupine Abyssal Plain for May 2013. This period is of interest for several reasons: (1) four Mercator Ocean operational systems provide daily forecasts at a horizontal resolution of 1/4, 1/12 and 1/36° with different physics; (2) glider deployment under the OSMOSIS project provides observation of the changes in mixed-layer depth; (3) the ocean stratifies in May, but mixing events induced by gale force wind are observed and forecast by the systems. Statistical scores and forecast error quantification for each system and for the combined products are presented. Skill scores indicate that forecasts are consistently better than persistence, and temporal correlations between forecast and observations are greater than 0.8 even for the 4-day forecast. The impact of atmospheric forecast error, and for the wind field in particular (miss or time delay of a wind burst forecast), is also quantified in terms of occurrence and intensity of mixing or stratification events.

This study is aimed at exploring the errors of a regional model of the Bay of Biscay, a regional zoom of the IBI configuration of the ocean model NEMO, with the ultimate objective of guiding the ch...

All climate models predict a freshening of the North Atlantic at high latitude that may induce an abrupt change of the Atlantic Meridional Overturning Circulation (hereafter AMOC) if it resides in the bistable regime, where both a strong and a weak state coexist. The latter remains uncertain as there is no consensus among observations and ocean reanalyses, where the AMOC is bistable, versus most climate models that reproduce a mono-stable strong AMOC. A series of four hindcast simulations of the global ocean at 1/12° resolution, which is presently unique, are used to diagnose freshwater transport by the AMOC in the South Atlantic, an indicator of AMOC bistability. In all simulations, the AMOC resides in the bistable regime: it exports freshwater southward in the South Atlantic, implying a positive salt advection feedback that would act to amplify a decreasing trend in subarctic deep water formation as projected in climate scenarios.

Since December 2010, the MyOcean global analysis and forecasting system has consisted of the Mercator Océan NEMO global 1/4° configuration with a 1/12° nested model over the Atlantic and the Mediterranean. The open boundary data for the nested configuration come from the global 1/4° configuration at 20° S and 80° N. The data are assimilated by means of a reduced-order Kalman filter with a 3-D multivariate modal decomposition of the forecast error. It includes an adaptive-error estimate and a localization algorithm. A 3-D-Var scheme provides a correction for the slowly evolving large-scale biases in temperature and salinity. Altimeter data, satellite sea surface temperature and in situ temperature and salinity vertical profiles are jointly assimilated to estimate the initial conditions for numerical ocean forecasting. In addition to the quality control performed by data producers, the system carries out a proper quality control on temperature and salinity vertical profiles in order to minimise the risk of erroneous observed profiles being assimilated in the model. This paper describes the recent systems used by Mercator Océan and the validation procedure applied to current MyOcean systems as well as systems under development. The paper shows how refinements or adjustments to the system during the validation procedure affect its quality. Additionally, we show that quality checks (in situ, drifters) and data sources (satellite sea surface temperature) have as great an impact as the system design (model physics and assimilation parameters). The results of the scientific assessment are illustrated with diagnostics over the year 2010 mainly, assorted with time series over the 2007–2011 period. The validation procedure demonstrates the accuracy of MyOcean global products, whose quality is stable over time. All monitoring systems are close to altimetric observations with a forecast RMS difference of 7 cm. The update of the mean dynamic topography corrects local biases in the Indonesian Throughflow and in the western tropical Pacific. This improves also the subsurface currents at the Equator. The global systems give an accurate description of water masses almost everywhere. Between 0 and 500 m, departures from in situ observations rarely exceed 1 °C and 0.2 psu. The assimilation of an improved sea surface temperature product aims to better represent the sea ice concentration and the sea ice edge. The systems under development are still suffering from a drift which can only be detected by means of a 5-yr hindcast, preventing us from upgrading them in real time. This emphasizes the need to pursue research while building future systems for MyOcean2 forecasting.

The Copernicus Marine Environment Monitoring Service (CMEMS) Ocean State Report (OSR) provides an annual report of the state of the global ocean and European regional seas for policy and decision-makers with the additional aim of increasing general public awareness about the status of, and changes in, the marine environment. The CMEMS OSR draws on expert analysis and provides a 3-D view (through reanalysis systems), a view from above (through remote-sensing data) and a direct view of the interior (through in situ measurements) of the global ocean and the European regional seas. The report is based on the unique CMEMS monitoring capabilities of the blue (hydrography, currents), white (sea ice) and green (e.g. Chlorophyll) marine environment. This first issue of the CMEMS OSR provides guidance on Essential Variables, large-scale changes and specific events related to the physical ocean state over the period 1993–2015. Principal findings of this first CMEMS OSR show a significant increase in global and regional sea levels, thermosteric expansion, ocean heat content, sea surface temperature and Antarctic sea ice extent and conversely a decrease in Arctic sea ice extent during the 1993–2015 period. During the year 2015 exceptionally strong large-scale changes were monitored such as, for example, a strong El Niño Southern Oscillation, a high frequency of extreme storms and sea level events in specific regions in addition to areas of high sea level and harmful algae blooms. At the same time, some areas in the Arctic Ocean experienced exceptionally low sea ice extent and temperatures below average were observed in the North Atlantic Ocean.

The feasibility of global ocean weather prediction was just emerging as the Global Ocean Data Assimilation Experiment (GODAE) began in 1997. Ocean weather includes phenomena such as meandering currents and fronts, eddies, the surface mixed layer and sea surface temperature (SST), equatorial and coastally trapped waves, upwelling of cold water, and Rossby waves, all influencing ocean variables such as temperature (T), salinity (S), currents, and sea surface height (SSH). Adequate real-time data input, computing power, numerical ocean models, data assimilation capabilities, atmospheric forcing, and bathymetric/boundary constraints are essential to make such prediction possible. The key observing systems and real-time data inputs are SSH from satellite altimetry, satellite and in situ SST, T or T and S profiles (e.g., Argo, TAO/Triton, PIRATA moored array in the Atlantic, bathythermographs), and atmospheric forcing. The ocean models dynamically interpolate data in conjunction with data assimilation, convert atmospheric forcing into oceanic responses, and forecast the ocean weather, applying bathymetric/boundary constraints in the process. The results are substantially influenced by ocean model simulation skill and it is advantageous to use an ocean model that is eddy-resolving (nominally 1/10º or finer), not just eddy-permitting. Because the most abundant ocean observations are satellite surface data, and subsurface data are very sparse in relation to the spatial scales of the mesoscale ocean features that dominate the ocean interior, downward projection of surface data is a key challenge in ocean data assimilation. The need for accurate prediction of ocean features that are inadequately observed, such as mixed layer depth, places a major burden on the ocean model, data assimilation, and atmospheric forcing. The sensitivity of ocean phenomena to atmospheric forcing and the time scale for response affect the time scale for oceanic predictive skill, sensitivity to the initial state versus the atmospheric forcing as a function of forecast length, and thus oceanic data requirements and prediction system design. Outside of surface boundary layers and shallow regions, forecast skill is about one month globally and over many subregions, and is only modestly reduced by using climatological forcing after the end of atmospheric forecasts versus using analysis-quality forcing for the duration. In addition, global ocean prediction systems must demonstrate the ability to provide initial and boundary conditions to nested regional and coastal models that enhance their predictive skill. Demonstrations of feasibility in relation to the preceding phenomena, requirements, and challenges are drawn from the following global and basin-scale ocean prediction systems: BLUElink> (Australia), the HYbrid Coordinate Ocean Model (HYCOM; USA), Mercator Ocean (France), Multivariate Ocean Variational Estimation/Meteorological Research Institute Community Ocean Model (MOVE/MRI.COM; Japan), and the Naval Research Laboratory Layered Ocean Model (NLOM; USA).

The French research community in the Mediterranean Sea modeling and the French operational ocean forecasting center Mercator Océan have gathered their skill and expertise in physical oceanography, ocean modeling, atmospheric forcings and data assimilation to carry out a MEDiterranean sea ReanalYsiS (MEDRYS) at high resolution for the period 1992-2013. The ocean model used is NEMOMED12, a Mediterranean configuration of NEMO with a 1=12° (∼7 km) horizontal resolution and 75 vertical z levels with partial steps. At the surface, it is forced by a new atmospheric-forcing data set (ALDERA), coming from a dynamical downscaling of the ERA-Interim atmospheric reanalysis by the regional climate model ALADIN-Climate with a 12 km horizontal and 3 h temporal resolutions. This configuration is used to carry a 34-year hindcast simulation over the period 1979-2013 (NM12-FREE), which is the initial state of the reanalysis in October 1992. MEDRYS uses the existing Mercator Océan data assimilation system SAM2 that is based on a reduced-order Kalman filter with a threedimensional (3-D) multivariate modal decomposition of the forecast error. Altimeter data, satellite sea surface temperature (SST) and temperature and salinity vertical profiles are jointly assimilated. This paper describes the configuration we used to perform MEDRYS. We then validate the skills of the data assimilation system. It is shown that the data assimilation restores a good average temperature and salinity at intermediate layers compared to the hindcast. No particular biases are identified in the bottom layers. However, the reanalysis shows slight positive biases of 0.02 psu and 0.15 °C above 150m depth. In the validation stage, it is also shown that the assimilation allows one to better reproduce water, heat and salt transports through the Strait of Gibraltar. Finally, the ability of the reanalysis to represent the sea surface high-frequency variability is shown., This research has received funding from the French National Research Agency (ANR) project REMEMBER (contract ANR-12-SENV-001).

Le projet MERCATOR vise, a l'echeance 2003, a fournir un systeme de prevision pre-operationnel des courants oceaniques. Celui-ci doit simuler l'ocean mondial avec un modele aux equations primitives a moyenne resolution dans lequel sont assimilees des donnees altimetriques et in situ. Dans le meme temps un prototype a haute resolution couvrant l'Atlantique Nord et la Mediterranee (PAM) est developpe. C'est dans la phase de mise au point de ce prototype que cette etude a ete realisee. Des tests de sensibilite ont ete effectues dans le but d'ameliorer la calibration du modele avant le branchement de l'algorithme d'assimilation de donnees qui sera utilise dans le nouveau systeme analyse prevision (PSY2). Les tests realises concernent le contexte de l'experience et non les parametrisations elles memes. Il s'agit de la bathymetrie qui represente la condition limite au fond, du forcage atmospherique qui represente la principale source d'energie responsable des circulations, et le rappel dans la masse a la temperature et a la salinite dans la region cle du Golfe de Cadix. Ils ameliorent respectivement la penetration de la derive nord Atlantique, l'intensite de la cellule meridienne de retournement et la plongee de la veine d'eau mediterraneenne dans l'Atlantique.

This work is dedicated to the study of the propagation of the Western Mediterranean Deep Water (WMDW) formed in the Gulf of Lions during the exceptional winter 2005. A simulation of the 1998-2008 period has been carried out with an eddy-resolving Ocean General Circulation Model of the Mediterranean Sea, driven by interannual high-resolution air-sea fluxes. This study first presents a validation of the recently improved model configuration against satellite observations. Then, we assess the ability of the model to reproduce the particularly intense deep convection event of winter 2005 in the Gulf of Lions. A huge volume of very dense water is formed in the simulations at that time (annual formation rate of about 3 Sv). The thermohaline characteristics of the new WMDW allow a monitoring of its deep propagation. We identify several deep cyclones as mainly responsible of the fast spreading of the WMDW southwards in the Western Mediterranean. By comparing Eulerian and Lagrangian approaches, we estimate different transport times of the WMDW by these cyclonic eddies and compare them to those deduced from several observations. Finally, we argue that these cyclones favour the propagation of the WMDW thermohaline characteristics towards the Channel of Sardinia and decrease the volume of WMDW which can reach the Strait of Gibraltar.

Since December 2010, the global analysis and forecast of the MyOcean system consists in the Mercator Océan NEMO global 1/4° configuration with a 1/12° "zoom" over the Atlantic and Mediterranean Sea. The zoom open boundaries come from the global 1/4° at 20° S and 80° N. The data assimilation uses a reduced order Kalman filter with a 3-D multivariate modal decomposition of the forecast error. It includes an adaptative error and a localization algorithm. A 3D-Var scheme corrects for the slowly evolving large-scale biases in temperature and salinity. Altimeter data, satellite temperature and in situ temperature and salinity vertical profiles are jointly assimilated to estimate the initial conditions for the numerical ocean forecasting. This paper gives a description of the recent systems. The validation procedure is introduced and applied to the current and future systems. This paper shows how the validation impacts on the quality of the systems. It is shown how quality check (in situ, drifters) and data source (satellite temperature) impacts as much as the systems design (model physics and assimilation parameters). The validation demonstrates the accuracy of the MyOcean global products. Their quality is stable in time. The future systems under development still suffer from a drift. This could only be detected with a 5 yr hindcast of the systems. This emphasizes the need for continuous research efforts in the process of building future versions of MyOcean2 forecasting capacities.

Within the MyOcean R&D project MESCLA (MEsoSCale dynamical Analysis through combined model, satellite and in situ data), different estimates of the vertical velocities derived from observations have been compared. Two main approaches have been considered, one based on the retrieval of 3-D fields from the observations alone and one based on the analyses provided by MyOcean MERCATOR models. The motivation for this double approach is that, while data assimilation in numerical models is crucial to obtain more accurate analyses and forecasts, its results might be significantly influenced by specific model configurations (e.g. forcing, parameterization of smaller scale processes and spatial resolution). On the other hand, the purely observation-based approach is limited by the underlying assumptions of simplified dynamical models and by the relatively low resolution of present products. MESCLA tested innovative methods for the high resolution mapping of 3-D mesoscale dynamics from observations, developing new products that might be used to gradually build the next generations of operational observation-based products.

International audience; European eel (Anguilla anguilla) larvae achieve one of the longest larval migrations of the marine realm, i.e., more than 6000 km from their spawning grounds in the Sargasso Sea to European continental shelves. The duration of this migration remains debated, between 7 months and 3 years. This information is, however, crucial since it determines the period over which larvae are affected by environmental conditions and hence the subsequent recruitment success. We investigate the pathways and duration of trans-Atlantic connections using 3 years of high-resolution (daily, 1/12°) velocity fields available from a Mercator-Océan model configuration without data assimilation. We study specifically the effect of spatial and temporal resolutions on our estimates by applying various filters in time (from daily to 12-day averages) and space (from 1/12° to 1° gridcell aggregation) to the nominal model outputs. Numerical particles are released in the presumed European eel spawning area and considered as passive tracers at three specific depths (around 0, 50, and 200 m). We diagnose particularly the intensity of the water transfer between suitable control sections that encompass the eel larva distribution. Transit ages are also investigated, with a particular focus on the pathways that minimize the connection times between the western and eastern North Atlantic. We show that small-scale structures (eddies and filaments) contribute to faster connections though they also correspond to additional complexity in trajectories. The shortest pathways mostly follow the Gulf Stream and the North Atlantic Drift, whereas interior connections require longer transfers that prove less compatible with biological observations.

The Gulf Stream is the focus of an effort aimed at dynamical understanding and evaluation of current systems simulated by eddy-resolving Ocean General Circulation Models (OGCMs), including examples with and without data assimilation and results from four OGCMs (HYCOM, MICOM, NEMO, and POP), the first two including Lagrangian isopycnal coordinates in the vertical and the last two using fixed depths. The Gulf Stream has been challenging to simulate and understand. While different non-assimilative models have at times simulated a realistic Gulf Stream pathway, the simulations are very sensitive to small changes, such as subgrid-scale parameterizations and parameter values. Thus it is difficult to obtain consistent results and serious flaws are often simulated upstream and downstream of Gulf Stream separation from the coast at Cape Hatteras. In realistic simulations, steering by a key abyssal current and a Gulf Stream feedback mechanism constrain the latitude of the Gulf Stream near 68.5°W. Additionally, the Gulf Stream follows a constant absolute vorticity (CAV) trajectory from Cape Hatteras to ~70°W, but without the latitudinal constraint near 68.5°W, the pathway typically develops a northern or southern bias. A shallow bias in the southward abyssal flow of the Atlantic Meridional Overturning Circulation (AMOC) creates a serious problem in many simulations because it results in abyssal currents along isobaths too shallow to feed into the key abyssal current or other abyssal currents that provide a similar pathway constraint. Pathways with a southern bias are driven by a combination of abyssal currents crossing under the Gulf Stream near the separation point and the increased opportunity for strong flow instabilities along the more southern route. The associated eddy-driven mean abyssal currents constrain the mean pathway to the east. Due to sloping topography, flow instabilities are inhibited along the more northern routes west of ~69°W, especially for pathways with a northern bias. The northern bias occurs when the abyssal current steering constraint needed for a realistic pathway is missing or too weak and the simulation succumbs to the demands of linear dynamics for an overshoot pathway. Both the wind forcing and the upper ocean branch of the AMOC contribute to those demands. Simulations with a northern pathway bias were all forced by a wind product particularly conducive to that result and they have a strong or typical AMOC transport with a shallow bias in the southward flow. Simulations forced by the same wind product (or other wind products) that have a weak AMOC with a shallow bias in the southward limb exhibit Gulf Stream pathways with a southern bias. Data assimilation has a very positive impact on the model dynamics by increasing the strength of a previously weak AMOC and by increasing the depth range of the deep southward branch. The increased depth range of the southward branch generates more realistic abyssal currents along the continental slope. This result in combination with vortex stretching and compression generated by the data-assimilative approximation to meanders in the Gulf Stream and related eddies in the upper ocean yield a model response that simulates the Gulf Stream-relevant abyssal current features seen in historical in situ observations, including the key abyssal current near 68.5°W, a current not observed in the assimilated data set or corresponding simulations without data assimilation. In addition, the model maintains these abyssal currents in a mean of 48 14-day forecasts, but does not maintain the strength of the Gulf Stream east of the western boundary.

International audience; The impact of the atmospheric forcing on the winter ocean convection in the Mediterranean Sea was studied with a high-resolution ocean general circulation model. The major areas of focus are the Levantine basin, the Aegean-Cretan Sea, the Adriatic Sea, and the Gulf of Lion. Two companion simulations differing by the horizontal resolution of the atmospheric forcing were compared. The first simulation (MED16-ERA40) was forced by air-sea fields from ERA40, which is the ECMWF reanalysis. The second simulation (MED16-ECMWF) was forced by the ECMWF-analyzed surface fields that have a horizontal resolution twice as high as those of ERA40. The analysis of the standard deviations of the atmospheric fields shows that increasing the resolution of the atmospheric forcing leads in all regions to a better channeling of the winds by mountains and to the generation of atmospheric mesoscale patterns. Comparing the companion ocean simulation results with available observations in the Adriatic Sea and in the Gulf of Lion shows that MED16-ECMWF is more realistic than MED16-ERA40. In the eastern Mediterranean, although deep water formation occurs in the two experiments, the depth reached by the convection is deeper in MED16-ECMWF. In the Gulf of Lion, deep water formation occurs only in MED16-ECMWF. This larger sensitivity of the western Mediterranean convection to the forcing resolution is investigated by running a set of sensitivity experiments to analyze the impact of different time-space resolutions of the forcing on the intense winter convection event in winter 1998-1999. The sensitivity to the forcing appears to be mainly related to the effect of wind channeling by the land orography, which can only be reproduced in atmospheric models of sufficient resolution. Thus, well-positioned patterns of enhanced wind stress and ocean surface heat loss are able to maintain a vigorous gyre circulation favoring efficient preconditioning of the area at the beginning of winter and to drive realistic buoyancy loss and mixing responsible for strong convection at the end of winter.

The new generation of high-resolution ocean models offers a new way to investigate the characteristics and the evolution of the ocean mesoscale. An analysis of the simulated Mediterranean eddies, the so-called ''meddies,'' is presented. The model used in this study is the Mercator North Atlantic [9°N, 70°N] and Mediterranean Sea Prototype (PAM), a high-resolution configuration (3.5-8 km horizontal grid) based on the OPA ocean general circulation model. The meddies are coherent structures of warm and salt Mediterranean Water (MW) advected in the northeast Atlantic. A 5 year experiment performed with PAM reproduced the main observed characteristics of the meddies: thermohaline properties (11.8°C, 36 psu), sizes (radius between 25 and 110 km), thickness (between 500 and 1000 m), westward advection velocities (1.4 cm.s-1), angular velocities (a period of 20 days), a good estimate of the number of meddies in the northeast Atlantic (~22), and their realistic geographical distribution (80% south of 40°N). Moreover, and in agreement with a previous study based on an observation cruise, these modeled meddies represent half of the westward salinity transport of MW.

Nowadays, many authorities in charge of rescue-at-sea operations lean on operational oceanography products to outline research perimeters. Moreover, current fields estimated with sophisticated ocean forecasting systems can be used as input data for oil spill/ drifting object fate models. This emphases the necessity of an accurate sea state forecast, with a mastered level of reliability. This Ph.D. Thesis focuses on the issues inherent to drift modelling, dealing in the first place with several aspects in the estimation of the oceanic current field. For that purpose, benchmarked drift scenarios were set up from real surface drifters data collected in the Mediterranean sea and off the coasts of Angola. The idea is to generate series of current fields of different qualities (i.e. with different modelling options or physical processes) and then to assess them in term of drifting predictability. Oceanic configurations with regional improvements and nested into Mercator 1/12° operational system and based on the NEMO 2.3 code are designed to perform ocean predictions. The drift forecasts are computed offline with two particles fate models: MOTHY (Météo-France's oil spill crisis response system) and Ariane (B. Blanke, 1997). The use of these softwares gives two different approaches. In the first one, an extraction of the current in depth is used as background of the one computed by MOTHY, which describes precisely the mixed layer vertical profile in response to local wind and pressure. With regard to Ariane, surface currents are used directly to assess the modeling of surface processes in our oceanic configurations. Previous studies showed that meso-scale features and high frequency processes have a strong contribution in the oceanic Lagrangian predictability. We were therefore particularly interested in the impact of the horizontal resolution, the vertical mixing, the atmospheric forcing frequency and other physical processes relevant for the oceanic drift like tides. Time and space scales that we focus on are about 72h forecasts. This covers typical forecast periods in crisis situation, for final distance errors of a few dozen of km (acceptable for reconnaissance by aircrafts). Results suggest that the effect of the wind and the control of meso-scale through the resolution are of primary importance for drift applications in the Mediterranean sea. Physical processes related to winter winds like the Stokes drift and windage also impact the buoys path offshore. Concerning the Angola scenario, complex oceanic features like the influence of the Congo river's plume and the fast reversal of coastal currents, likely due to tropical waves, were studied. In this region, the vertical level of the current extraction is very sensitive because of undercurrents.; La plupart des opérations de secours en mer s'appuient aujourd'hui sur des prévisions numériques opérationnelles afin de coordonner les moyens d'action et de cibler les zones d'intervention prioritaires. Pour des cas de pollution marine ou pour la recherche d'objets dérivants, des modèles de trajectoire spécifiques existent et permettent d'élaborer des scenarii plus ou moins réalistes à partir de courants modélisés. La fiabilité de ces systèmes est en grande partie conditionnée par la qualité de ces courants prévus et utilisés. Ce travail de thèse s'intéresse à la modélisation des processus océaniques qui modifient les propriétés adjectives du courant, en particulier à proximité de la surface, où les vitesses sont les plus fortes, et où des structures de fine échelle liées aux interactions avec l'atmosphère et à des processus turbulents en complexifient l'estimation. La méthodologie adoptée est la classique confrontation modèle-observation pour deux cas d'étude distincts, l'un en Méditerranée occidentale (hiver 2007) et l'autre en Atlantique Est-Équatorial près de l'embouchure du Congo (printemps 2008). À partir d'outils numériques dérivés de l'opérationnel, il est tenté de reproduire des trajectoires réelles de flotteurs de surface en réalisant diverses études de sensibilité. Les prévisions de courant sont générées à partir de configurations régionales à haute résolution basées sur le code d'océan NEMO. Le logiciel Ariane (B. Blanke, 1997) utilise les propriétés de surface du courant, alors que le modèle d'hydrocarbure Mothy (Météo France) utilise une extraction en profondeur afin de compléter sa modélisation interne de l'océan en réponse aux changements rapides du forçage atmosphérique. Cette étude cible des échelles de prévisions de quelques heures à trois jours au maximum (échéance typique demandée en cas de crise). Les tests ciblent la résolution horizontale, l'impact des paramétrisations sur les forçages et la représentation des processus physiques, en particulier ceux rencontrés par les bouées, comme par exemple le panache du fleuve Congo en Angola.

Nowadays, many authorities in charge of rescue-at-sea operations lean on operational oceanography products to outline research perimeters. Moreover, current fields estimated with sophisticated ocean forecasting systems can be used as input data for oil spill/ drifting object fate models. This emphases the necessity of an accurate sea state forecast, with a mastered level of reliability. This Ph.D. Thesis focuses on the issues inherent to drift modelling, dealing in the first place with several aspects in the estimation of the oceanic current field. For that purpose, benchmarked drift scenarios were set up from real surface drifters data collected in the Mediterranean sea and off the coasts of Angola. The idea is to generate series of current fields of different qualities (i.e. with different modelling options or physical processes) and then to assess them in term of drifting predictability. Oceanic configurations with regional improvements and nested into Mercator 1/12° operational system and based on the NEMO 2.3 code are designed to perform ocean predictions. The drift forecasts are computed offline with two particles fate models: MOTHY (Météo-France's oil spill crisis response system) and Ariane (B. Blanke, 1997). The use of these softwares gives two different approaches. In the first one, an extraction of the current in depth is used as background of the one computed by MOTHY, which describes precisely the mixed layer vertical profile in response to local wind and pressure. With regard to Ariane, surface currents are used directly to assess the modeling of surface processes in our oceanic configurations. Previous studies showed that meso-scale features and high frequency processes have a strong contribution in the oceanic Lagrangian predictability. We were therefore particularly interested in the impact of the horizontal resolution, the vertical mixing, the atmospheric forcing frequency and other physical processes relevant for the oceanic drift like tides. Time and space scales that we focus on are about 72h forecasts. This covers typical forecast periods in crisis situation, for final distance errors of a few dozen of km (acceptable for reconnaissance by aircrafts). Results suggest that the effect of the wind and the control of meso-scale through the resolution are of primary importance for drift applications in the Mediterranean sea. Physical processes related to winter winds like the Stokes drift and windage also impact the buoys path offshore. Concerning the Angola scenario, complex oceanic features like the influence of the Congo river's plume and the fast reversal of coastal currents, likely due to tropical waves, were studied. In this region, the vertical level of the current extraction is very sensitive because of undercurrents.; La plupart des opérations de secours en mer s'appuient aujourd'hui sur des prévisions numériques opérationnelles afin de coordonner les moyens d'action et de cibler les zones d'intervention prioritaires. Pour des cas de pollution marine ou pour la recherche d'objets dérivants, des modèles de trajectoire spécifiques existent et permettent d'élaborer des scenarii plus ou moins réalistes à partir de courants modélisés. La fiabilité de ces systèmes est en grande partie conditionnée par la qualité de ces courants prévus et utilisés. Ce travail de thèse s'intéresse à la modélisation des processus océaniques qui modifient les propriétés adjectives du courant, en particulier à proximité de la surface, où les vitesses sont les plus fortes, et où des structures de fine échelle liées aux interactions avec l'atmosphère et à des processus turbulents en complexifient l'estimation. La méthodologie adoptée est la classique confrontation modèle-observation pour deux cas d'étude distincts, l'un en Méditerranée occidentale (hiver 2007) et l'autre en Atlantique Est-Équatorial près de l'embouchure du Congo (printemps 2008). À partir d'outils numériques dérivés de l'opérationnel, il est tenté de reproduire des trajectoires réelles de flotteurs de surface en réalisant diverses études de sensibilité. Les prévisions de courant sont générées à partir de configurations régionales à haute résolution basées sur le code d'océan NEMO. Le logiciel Ariane (B. Blanke, 1997) utilise les propriétés de surface du courant, alors que le modèle d'hydrocarbure Mothy (Météo France) utilise une extraction en profondeur afin de compléter sa modélisation interne de l'océan en réponse aux changements rapides du forçage atmosphérique. Cette étude cible des échelles de prévisions de quelques heures à trois jours au maximum (échéance typique demandée en cas de crise). Les tests ciblent la résolution horizontale, l'impact des paramétrisations sur les forçages et la représentation des processus physiques, en particulier ceux rencontrés par les bouées, comme par exemple le panache du fleuve Congo en Angola.