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Two types of variability are discernible in the ocean: a response to the atmospheric forcing and the so-called internal/intrinsic ocean variability, which is associated with internal instabilities, nonlinearities, and the interactions between processes at different scales. Producing an ensemble of 20 multiyear ocean simulations of the Mediterranean Sea, initialized with different realistic initial conditions but using the same atmospheric forcing, the study examines the intrinsic variability in terms of its spatial distribution and seasonality. In general, the importance of the external forcing decreases with depth but dominates in extended shelves such as the Adriatic Sea and the Gulf of Gabes. In the case of temperature, the atmospheric forcing plays a major role in the uppermost 50 m of the water column during summer and the uppermost 100 m during winter. Additionally, intrinsic variability displays a distinct seasonal cycle in the surface layers, with a prominent maximum at around 30 m depth during the summer connected to the summer thermocline formation processes. Concerning current velocity, the internal variability has a significant influence at all depths.

The effects of tides on the Mediterranean Sea's general circulation, with a particular focus on the horizontal and vertical currents, are investigated using twin simulations with and without tides. Amplitudes of tides in the region are typically low, but an analysis of the potential and kinetic energy demonstrates that tides have effects across many spatial and temporal scales in the basin, including non-linear effects in short periods (less than 1 d) with high kinetic energy peaks at near-inertial basin modes and tidal frequencies. Internal tidal waves are also revealed below 100 m. Tides are found to amplify several basin modes of the Mediterranean Sea, broaden several tidal frequency energy spectra bands, and interact energetically with near-inertial waves. Tides increase the mixed layer depth in the Mediterranean Sea, particularly in the deep and intermediate water formation areas of the western Mediterranean Basin and eastern Mediterranean Basin. The addition of tides in the cases considered does also enhance Western Mediterranean Deep Water formation.

Biogeochemical (BGC) models are widely used in ocean simulations for a range of applications but typically include parameters that are determined based on a combination of empiricism and convention. Here, we describe and demonstrate an optimization-based parameter estimation method for high-dimensional (in parameter space) BGC ocean models. Our computationally efficient method combines the respective benefits of global and local optimization techniques and enables simultaneous parameter estimation at multiple ocean locations using multiple state variables. We demonstrate the method for a 17-state-variable BGC model with 51 uncertain parameters, where a one-dimensional (in space) physical model is used to represent vertical mixing. We perform a twin-simulation experiment to test the accuracy of the method in recovering known parameters. We then use the method to simultaneously match multi-variable observational data collected at sites in the subtropical North Atlantic and Pacific. We examine the effects of different objective functions, sometimes referred to as cost functions, which quantify the disagreement between model and observational data. We further examine increasing levels of data sparsity and the choice of state variables used during the optimization. We end with a discussion of how the method can be applied to other BGC models, ocean locations, and mixing representations.

The Mediterranean Forecasting System produces operational analyses and reanalyses and 10 d forecasts for many essential ocean variables (EOVs), from currents, temperature, salinity, and sea level to wind waves and pelagic biogeochemistry. The products are available at a horizontal resolution of 1/24∘ (approximately 4 km) and with 141 unevenly spaced vertical levels. The core of the Mediterranean Forecasting System is constituted by the physical (PHY), the biogeochemical (BIO), and the wave (WAV) components, consisting of both numerical models and data assimilation modules. The three components together constitute the so-called Mediterranean Monitoring and Forecasting Center (Med-MFC) of the Copernicus Marine Service. Daily 10 d forecasts and analyses are produced by the PHY, BIO, and WAV operational systems, while reanalyses are produced every ∼ 3 years for the past 30 years and are extended (yearly). The modelling systems, their coupling strategy, and their evolutions are illustrated in detail. For the first time, the quality of the products is documented in terms of skill metrics evaluated over a common 3-year period (2018–2020), giving the first complete assessment of uncertainties for all the Mediterranean environmental variable analyses.

This study examines the wind-wave characteristics along the Emilia-Romagna coasts (northern Adriatic Sea, Italy) with a 10-year wave simulation for the period 2010–2019 performed with the high-resolution unstructured-grid WAVEWATCH III (WW3) coastal wave model. The wave parameters (significant wave height, mean and peak wave period, and wave direction) were validated with the in situ measurements at a coastal station, Cesenatico. In the coastal belt, the annual mean wave heights varied from 0.2–0.4 m, and the seasonal mean was highest for the winter period (>0.4 m). The Emilia-Romagna coastal belt was characterized by wave and spectra seasonal signals with two dominant frequencies of the order of 10 and 5–6 s for autumn and winter and 7–9 and 4 s for spring and summer. The wavelet power spectra of significant wave height for 10 years show considerable variability, having monthly and seasonal periods. This validated and calibrated data set enabled us to study the probability distributions of the significant wave height along the coasts and define a hazard index based on a fitted Weibull probability distribution function.

Abstract The origin of the Mediterranean Outflow is investigated by deploying six millions virtual Lagrangian parcels at the Strait of Gibraltar, and tracing them backward in time using velocity estimates from an eddy‐permitting reanalysis. The Lagrangian parcels are followed until they intercept one of three sections. The hypothesis is that each section is associated with distinct water masses: the Gulf of Lions, related to Western Mediterranean Deep Water and Western Intermediate Water, carries 86% of the Outflow's transport; the Northern Tyrrhenian, related to Tyrrhenian Deep and Intermediate Waters, carries 1% of the transport; the Strait of Sicily, related to Levantine Intermediate Waters, carries 13% of the transport. The median transit times from the sections to the Strait of Gibraltar range from 5 years (Gulf of Lions) to 8 years (Strait of Sicily).

This paper presents the message passing interface (MPI)-based parallelization of the three-dimensional hydrodynamic model SHYFEM (System of HydrodYnamic Finite Element Modules). The original sequential version of the code was parallelized in order to reduce the execution time of high-resolution configurations using state-of-the-art high-performance computing (HPC) systems. A distributed memory approach was used, based on the MPI. Optimized numerical libraries were used to partition the unstructured grid (with a focus on load balancing) and to solve the sparse linear system of equations in parallel in the case of semi-to-fully implicit time stepping. The parallel implementation of the model was validated by comparing the outputs with those obtained from the sequential version. The performance assessment demonstrates a good level of scalability with a realistic configuration used as benchmark.

We present a newly developed upper-thermocline, open-ocean biogeochemical flux model that is complex and flexible enough to capture open-ocean ecosystem dynamics but reduced enough to incorporate into highly resolved numerical simulations and parameter optimization studies with limited additional computational cost. The model, which is derived from the full 56-state-variable Biogeochemical Flux Model (BFM56; Vichi et al., 2007), follows a biological and chemical functional group approach and allows for the development of critical non-Redfield nutrient ratios. Matter is expressed in units of carbon, nitrogen, and phosphate, following techniques used in more complex models. To reduce the overall computational cost and to focus on upper-thermocline, open-ocean, and non-iron-limited or non-silicate-limited conditions, the reduced model eliminates certain processes, such as benthic, silicate, and iron influences, and parameterizes others, such as the bacterial loop. The model explicitly tracks 17 state variables, divided into phytoplankton, zooplankton, dissolved organic matter, particulate organic matter, and nutrient groups. It is correspondingly called the Biogeochemical Flux Model 17 (BFM17). After describing BFM17, we couple it with the one-dimensional Princeton Ocean Model for validation using observational data from the Sargasso Sea. The results agree closely with observational data, giving correlations above 0.85, except for chlorophyll (0.63) and oxygen (0.37), as well as with corresponding results from BFM56, with correlations above 0.85, except for oxygen (0.56), including the ability to capture the subsurface chlorophyll maximum and bloom intensity. In comparison to previous models of similar size, BFM17 provides improved correlations between several model output fields and observational data, indicating that reproduction of in situ data can be achieved with a low number of variables, while maintaining the functional group approach. Notable additions to BFM17 over similar complexity models are the explicit tracking of dissolved oxygen, allowance for non-Redfield nutrient ratios, and both dissolved and particulate organic matter, all within the functional group framework.

A simulation of the Turkish Straits System (TSS) using a high-resolution, three-dimensional, unstructured mesh ocean circulation model with realistic atmospheric forcing for the 2008–2013 period is presented. The depth of the pycnocline between the upper and lower layers remains stationary after 6 years of integration, indicating that despite the limitations of the modelling system, the simulation maintains its realism. The solutions capture important responses to high-frequency atmospheric events such as the reversal of the upper layer flow in the Bosphorus due to southerly severe storms, i.e. blocking events, to the extent that such storms are present in the forcing dataset. The annual average circulations show two distinct patterns in the Sea of Marmara. When the wind stress maximum is localised in the central basin, the Bosphorus jet flows to the south and turns west after reaching the Bozburun Peninsula. In contrast, when the wind stress maximum increases and expands in the north–south direction, the jet deviates to the west before reaching the southern coast and forms a cyclonic gyre in the central basin. In certain years, the mean kinetic energy in the northern Sea of Marmara is found to be comparable to that of the Bosphorus inflow.

An observing system simulation experiment (OSSE) is presented in the Sea of Marmara. A high-resolution ocean circulation model (FESOM) and an ensemble data assimilation tool (DART) are coupled. The OSSE methodology is used to assess the possible impact of a FerryBox network in the eastern Sea of Marmara. A reference experiment without assimilation is performed. Then, synthetic temperature and salinity observations are assimilated along the track of the ferries in the second experiment. The results suggest that a FerryBox network in the Sea of Marmara has potential to improve the forecasts significantly. The salinity and temperature errors get smaller in the upper layer of the water column. The impact of the assimilation is negligible in the lower layer due to the strong stratification. The circulation in the Sea of Marmara, particularly the Bosphorus outflow, helps to propagate the error reduction towards the western basin where no assimilation is performed. Overall, the proposed FerryBox network can be a good start to designing an optimal sustained marine observing network in the Sea of Marmara for assimilation purposes.

A meteo-hydrological modelling system has been designed for the reconstruction of long time series of rainfall and river runoff events. The modelling chain consists of the mesoscale meteorological model of the Weather Research and Forecasting (WRF), the land surface model NOAH-MP and the hydrology–hydraulics model WRF-Hydro. Two 3-month periods are reconstructed for winter 2011 and autumn 2013, containing heavy rainfall and river flooding events. Several sensitivity tests were performed along with an assessment of which tunable parameters, numerical choices and forcing data most impacted on the modelling performance.The calibration of the experiments highlighted that the infiltration and aquifer coefficients should be considered as seasonally dependent.The WRF precipitation was validated by a comparison with rain gauges in the Ofanto basin. The WRF model was demonstrated to be sensitive to the initialization time and a spin-up of about 1.5 days was needed before the start of the major rainfall events in order to improve the accuracy of the reconstruction. However, this was not sufficient and an optimal interpolation method was developed to correct the precipitation simulation. It is based on an objective analysis (OA) and a least square (LS) melding scheme, collectively named OA+LS. We demonstrated that the OA+LS method is a powerful tool to reduce the precipitation uncertainties and produce a lower error precipitation reconstruction that itself generates a better river discharge time series. The validation of the river streamflow showed promising statistical indices.The final set-up of our meteo-hydrological modelling system was able to realistically reconstruct the local rainfall and the Ofanto hydrograph.

Reliable and timely information on the environmental conditions at sea is key to the safety of professional and recreational users as well as to the optimal execution of their activities. The possibility of users obtaining environmental information in due time and with adequate accuracy in the marine and coastal environment is defined as sea situational awareness (SSA). Without adequate information on the environmental meteorological and oceanographic conditions, users have a limited capacity to respond, which has led to loss of lives and to large environmental disasters with enormous consequent damage to the economy, society and ecosystems. Within the framework of the TESSA project, new SSA services for the Mediterranean Sea have been developed. In this paper we present SeaConditions, which is a web and mobile application for the provision of meteorological and oceanographic observation and forecasting products. Model forecasts and satellite products from operational services, such as ECMWF and CMEMS, can be visualized in SeaConditions. In addition, layers of information related to bathymetry, sea level and ocean-colour data (chl a and water transparency) are displayed. Ocean forecasts at high spatial resolutions are included in the version of SeaConditions presented here. SeaConditions provides a user-friendly experience with a fluid zoom capability, facilitating the appropriate display of data with different levels of detail. SeaConditions is a single point of access to interactive maps from different geophysical fields, providing high-quality information based on advanced oceanographic models. The SeaConditions services are available through both web and mobile applications. The web application is available at www.sea-conditions.com and is accessible and compatible with present-day browsers. Interoperability with GIS software is implemented. User feedback has been collected and taken into account in order to improve the service. The SeaConditions iOS and Android apps have been downloaded by more than 105 000 users to date (May 2016), and more than 100 000 users have visited the web version.

SANIFS (Southern Adriatic Northern Ionian coastal Forecasting System) is a coastal-ocean operational system based on the unstructured grid finite-element three-dimensional hydrodynamic SHYFEM model, providing short-term forecasts. The operational chain is based on a downscaling approach starting from the large-scale system for the entire Mediterranean Basin (MFS, Mediterranean Forecasting System), which provides initial and boundary condition fields to the nested system. The model is configured to provide hydrodynamics and active tracer forecasts both in open ocean and coastal waters of southeastern Italy using a variable horizontal resolution from the open sea (3–4 km) to coastal areas (50–500 m). Given that the coastal fields are driven by a combination of both local (also known as coastal) and deep-ocean forcings propagating along the shelf, the performance of SANIFS was verified both in forecast and simulation mode, first (i) on the large and shelf-coastal scales by comparing with a large-scale survey CTD (conductivity–temperature–depth) in the Gulf of Taranto and then (ii) on the coastal-harbour scale (Mar Grande of Taranto) by comparison with CTD, ADCP (acoustic doppler current profiler) and tide gauge data. Sensitivity tests were performed on initialization conditions (mainly focused on spin-up procedures) and on surface boundary conditions by assessing the reliability of two alternative datasets at different horizontal resolution (12.5 and 6.5 km). The SANIFS forecasts at a lead time of 1 day were compared with the MFS forecasts, highlighting that SANIFS is able to retain the large-scale dynamics of MFS. The large-scale dynamics of MFS are correctly propagated to the shelf-coastal scale, improving the forecast accuracy (+17 % for temperature and +6 % for salinity compared to MFS). Moreover, the added value of SANIFS was assessed on the coastal-harbour scale, which is not covered by the coarse resolution of MFS, where the fields forecasted by SANIFS reproduced the observations well (temperature RMSE equal to 0.11 °C). Furthermore, SANIFS simulations were compared with hourly time series of temperature, sea level and velocity measured on the coastal-harbour scale, showing a good agreement. Simulations in the Gulf of Taranto described a circulation mainly characterized by an anticyclonic gyre with the presence of cyclonic vortexes in shelf-coastal areas. A surface water inflow from the open sea to Mar Grande characterizes the coastal-harbour scale.

Based on a novel estimation of background-error covariances for assimilating Argo profiles, an oceanographic three-dimensional variational (3DVAR) data assimilation scheme was developed for the northwestern Pacific Ocean model (NwPM) for potential use in operational predictions and maritime safety applications. Temperature and salinity data extracted from Argo profiles from January to December 2010 were assimilated into the NwPM. The results show that the average daily temperature (salinity) root mean square error (RMSE) decreased from 0.99 °C (0.10 psu) to 0.62 °C (0.07 psu) in assimilation experiments throughout the northwestern Pacific, which represents a 37.2 % (27.6 %) reduction in the error. The temperature (salinity) RMSE decreased by ∼ 0.60 °C ( ∼ 0.05 psu) for the upper 900 m (1000 m). Sea level, temperature and salinity were in better agreement with in situ and satellite datasets after data assimilation than before. In addition, a 1-month experiment with daily analysis cycles and 5-day forecasts explored the performance of the system in an operational configuration. The results highlighted the positive impact of the 3DVAR initialization at all forecast ranges compared to the non-assimilative experiment. Therefore, the 3DVAR scheme proposed here, coupled to ROMS, shows a good predictive performance and can be used as an assimilation scheme for operational forecasting.

A new web-based and mobile decision support system (DSS) for search-and-rescue (SAR) at sea is presented, and its performance is evaluated using real case scenarios. The system, named OCEAN-SAR, is accessible via the website http://www.ocean-sar.com. In addition to the website, dedicated applications for iOS and Android have been created to optimise the user experience on mobile devices. OCEAN-SAR simulates drifting objects at sea, using as input ocean currents and wind data provided, respectively, by the CMEMS and ECMWF. The modelling of the drifting objects is based on the leeway model, which parameterises the wind drag of an object using a series of coefficients. These coefficients have been measured in field experiments for different types of objects, ranging from a person in the water to a coastal freighter adrift. OCEAN-SAR provides the user with an intuitive interface to run simulations and to visualise their results using Google Maps. The performance of the service is evaluated by comparing simulations to data from the Italian Coast Guard pertaining to actual incidents in the Mediterranean Sea.

A multiscale sampling experiment was carried out in the Gulf of Taranto (eastern Mediterranean) providing the first synoptic evidence of the large-scale circulation structure and associated mesoscale variability. The mapping of the mesoscale and large-scale geostrophic circulation showed the presence of an anticyclonic large-scale gyre occupying the central open ocean area of the Gulf of Taranto. On the periphery of the gyre upwelling is evident where surface waters are colder and saltier than at the center of the gyre. Over a 1-week period, the rim current of the gyre undergoes large changes which are interpreted as baroclinic–barotropic instabilities, generating small-scale cyclonic eddies in the periphery of the anticyclone. The eddies are generally small, one of which can be classified as a submesoscale eddy due to its size. This eddy field modulates the upwelling regime in the gyre periphery.

The main scope of the Marine Strategy Framework Directive is to achieve good environmental status (GES) of the EU's marine waters by 2020, in order to protect the marine environment more effectively. The trophic index (TRIX) was developed by Vollenweider in 1998 for the coastal area of Emilia-Romagna (northern Adriatic Sea) and was used by the Italian legislation to characterize the trophic state of coastal waters. We compared the TRIX index calculated from in situ data (“in situ TRIX”) with the corresponding index simulated with a coupled physics and biogeochemical numerical model (“model TRIX”) implemented in the overall Adriatic Sea. The comparison between in situ and simulated data was carried out for a data time series on the Emilia-Romagna coastal strip. This study shows the compatibility of the model with the in situ TRIX and the importance of the length of the time series in order to get robust index estimates. The model TRIX is finally calculated for the whole Adriatic Sea, showing trophic index differences across the Adriatic coastal areas.

VISIR (discoVerIng Safe and effIcient Routes) is an operational decision support system (DSS) for optimal ship routing designed and implemented in the frame of the TESSA (TEchnology for Situational Sea Awareness) project. The system is aimed to increase safety and efficiency of navigation through the use of forecast environmental fields and route optimization. VISIR can be accessed through a web interface (www.visir-nav.com) and mobile applications for both iOS and Android devices. This paper focuses on the technological infrastructure developed for operating VISIR as a DSS. Its main components are described, the performance of the operational system is assessed through experimental measurements, and a few case studies are presented.

This paper presents an innovative web-based decision support system to facilitate emergency management in the case of oil spill accidents, called WITOIL (Where Is The Oil). The system can be applied to create a forecast of oil spill events, evaluate uncertainty of the predictions, and calculate hazards based on historical meteo-oceanographic datasets. To compute the oil transport and transformation, WITOIL uses the MEDSLIK-II oil spill model forced by operational meteo-oceanographic services. Results of the modeling are visualized through Google Maps. A special application for Android is designed to provide mobile access for competent authorities, technical and scientific institutions, and citizens.

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 of a multiple linear regression technique applied to a multi-physics multi-model super-ensemble (MMSE) data set. 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 data set 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 training period length, 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 data set (a subset with the higher-quality ensemble members) and the least-squares algorithm being filtered a posteriori.

On 7 March 2014 (UTC), Malaysia Airlines flight 370 vanished without a trace. The aircraft is believed to have crashed in the southern Indian Ocean, but despite extensive search operations the location of the wreckage is still unknown. The first tangible evidence of the accident was discovered almost 17 months after the disappearance. On 29 July 2015, a small piece of the right wing of the aircraft was found washed up on the island of Réunion, approximately 4000 km from the assumed crash site. Since then a number of other parts have been found in Mozambique, South Africa and on Rodrigues Island. This paper presents a numerical simulation using high-resolution oceanographic and meteorological data to predict the movement of floating debris from the accident. Multiple model realisations are used with different starting locations and wind drag parameters. The model realisations are combined into a superensemble, adjusting the model weights to best represent the discovered debris. The superensemble is then used to predict the distribution of marine debris at various moments in time. This approach can be easily generalised to other drift simulations where observations are available to constrain unknown input parameters. The distribution at the time of the accident shows that the discovered debris most likely originated from the wide search area between 28 and 35° S. This partially overlaps with the current underwater search area, but extends further towards the north. Results at later times show that the most probable locations to discover washed-up debris are along the African east coast, especially in the area around Madagascar. The debris remaining at sea in 2016 is spread out over a wide area and its distribution changes only slowly.

Operational approaches have been more and more widely developed and used for providing marine data and information services for different socio-economic sectors of the Blue Growth and to advance knowledge about the marine environment. The objective of operational oceanographic research is to develop and improve the efficiency, timeliness, robustness and product quality of this approach. This white paper aims to address key scientific challenges and research priorities for the development of operational oceanography in Europe for the next 5–10 years. Knowledge gaps and deficiencies are identified in relation to common scientific challenges in four EuroGOOS knowledge areas: European Ocean Observations, Modelling and Forecasting Technology, Coastal Operational Oceanography and Operational Ecology. The areas “European Ocean Observations” and “Modelling and Forecasting Technology” focus on the further advancement of the basic instruments and capacities for European operational oceanography, while “Coastal Operational Oceanography” and “Operational Ecology” aim at developing new operational approaches for the corresponding knowledge areas.

A new numerical model for the on-demand computation of optimal ship routes based on sea-state forecasts has been developed. The model, named VISIR (discoVerIng Safe and effIcient Routes) is designed to support decision-makers when planning a marine voyage. The first version of the system, VISIR-I, considers medium and small motor vessels with lengths of up to a few tens of metres and a displacement hull. The model is comprised of three components: a route optimization algorithm, a mechanical model of the ship, and a processor of the environmental fields. The optimization algorithm is based on a graph-search method with time-dependent edge weights. The algorithm is also able to compute a voluntary ship speed reduction. The ship model accounts for calm water and added wave resistance by making use of just the principal particulars of the vessel as input parameters. It also checks the optimal route for parametric roll, pure loss of stability, and surfriding/broaching-to hazard conditions. The processor of the environmental fields employs significant wave height, wave spectrum peak period, and wave direction forecast fields as input. The topological issues of coastal navigation (islands, peninsulas, narrow passages) are addressed. Examples of VISIR-I routes in the Mediterranean Sea are provided. The optimal route may be longer in terms of miles sailed and yet it is faster and safer than the geodetic route between the same departure and arrival locations. Time savings up to 2.7 % and route lengthening up to 3.2 % are found for the case studies analysed. However, there is no upper bound for the magnitude of the changes of such route metrics, which especially in case of extreme sea states can be much greater. Route diversions result from the safety constraints and the fact that the algorithm takes into account the full temporal evolution and spatial variability of the environmental fields.

The sensitivity of the dynamics of the Mediterranean Sea to atmospheric pressure and free surface elevation formulation using NEMO (Nucleus for European Modelling of the Ocean) was evaluated. Four different experiments were carried out in the Mediterranean Sea using filtered or explicit free surface numerical schemes and accounting for the effect of atmospheric pressure in addition to wind and buoyancy fluxes. Model results were evaluated by coherency and power spectrum analysis with tide gauge data. We found that atmospheric pressure plays an important role for periods shorter than 100 days. The free surface formulation is important to obtain the correct ocean response for periods shorter than 30 days. At frequencies higher than 15 days−1 the Mediterranean basin's response to atmospheric pressure was not coherent and the performance of the model strongly depended on the specific area considered. A large-amplitude seasonal oscillation observed in the experiments using a filtered free surface was not evident in the corresponding explicit free surface formulation case, which was due to a phase shift between mass fluxes in the Gibraltar Strait and at the surface. The configuration with time splitting and atmospheric pressure always performed best; the differences were enhanced at very high frequencies.

The processes of transport, diffusion and transformation of surface oil in seawater can be simulated using a Lagrangian model formalism coupled with Eulerian circulation models. This paper describes the formalism and the conceptual assumptions of a Lagrangian marine surface oil slick numerical model and rewrites the constitutive equations in a modern mathematical framework. The Lagrangian numerical representation of the oil slick requires three different state variables: the slick, the particle and the structural state variables. Transformation processes (evaporation, spreading, dispersion and coastal adhesion) act on the slick state variables, while particle variables are used to model the transport and diffusion processes. The slick and particle variables are recombined together to compute the oil concentration in water, a structural state variable. The mathematical and numerical formulation of oil transport, diffusion and transformation processes described in this paper, together with the many simplifying hypothesis and parameterizations, form the basis of a new, open source Lagrangian surface oil spill model, the so-called MEDSLIK-II, based on its precursor MEDSLIK (Lardner et al., 1998, 2006; Zodiatis et al., 2008a). Part 2 of this paper describes the applications of the model to oil spill simulations that allow the validation of the model results and the study of the sensitivity of the simulated oil slick to different model numerical parameterizations.

In this paper we use MEDSLIK-II, a Lagrangian marine surface oil spill model described in Part 1 (De Dominicis et al., 2013), to simulate oil slick transport and transformation processes for realistic oceanic cases, where satellite or drifting buoys data are available for verification. The model is coupled with operational oceanographic currents, atmospheric analyses winds and remote sensing data for initialization. The sensitivity of the oil spill simulations to several model parameterizations is analyzed and the results are validated using surface drifters, SAR (synthetic aperture radar) and optical satellite images in different regions of the Mediterranean Sea. It is found that the forecast skill of Lagrangian trajectories largely depends on the accuracy of the Eulerian ocean currents: the operational models give useful estimates of currents, but high-frequency (hourly) and high-spatial resolution is required, and the Stokes drift velocity has to be added, especially in coastal areas. From a numerical point of view, it is found that a realistic oil concentration reconstruction is obtained using an oil tracer grid resolution of about 100 m, with at least 100 000 Lagrangian particles. Moreover, sensitivity experiments to uncertain model parameters show that the knowledge of oil type and slick thickness are, among all the others, key model parameters affecting the simulation results. Considering acceptable for the simulated trajectories a maximum spatial error of the order of three times the horizontal resolution of the Eulerian ocean currents, the predictability skill for particle trajectories is from 1 to 2.5 days depending on the specific current regime. This suggests that re-initialization of the simulations is required every day.

A large number of SLA observations at a high along track horizontal resolution are an important ingredient of the data assimilation in the Mediterranean Forecasting System (MFS). Recently, new higher-frequency SLA products have become available, and the atmospheric pressure forcing has been implemented in the numerical model used in the MFS data assimilation system. In a set of numerical experiments, we show that, in order to obtain the most accurate analyses, the ocean model should include the atmospheric pressure forcing and the observations should contain the atmospheric pressure signal. When the model is not forced by the atmospheric pressure, the high-frequency filtering of SLA observations, however, improves the quality of the SLA analyses. It is further shown by comparing the power density spectra of the model fields and observations that the model is able to extract the correct information from noisy observations even without their filtering during the pre-processing.

A novel method for three-dimensional variational assimilation of Lagrangian data with a primitive-equation ocean model is proposed. The assimilation scheme was implemented in the Mediterranean ocean Forecasting System and evaluated for a 4-month period. Four experiments were designed to assess the impact of trajectory assimilation on the model output, i.e. the sea-surface height, velocity, temperature and salinity fields. It was found from the drifter and Argo trajectory assimilation experiment that the forecast skill of surface-drifter trajectories improved by 15 %, that of intermediate-depth float trajectories by 20 %, and moreover, that the forecasted sea-surface height fields improved locally by 5 % compared to satellite data, while the quality of the temperature and salinity fields remained at previous levels. In conclusion, the addition of Lagrangian trajectory assimilation proved to reduce the uncertainties in the model fields, thus yielding a higher accuracy of the ocean forecasts.

No abstract available.

This paper describes the first evaluation of the quality of the forecast and analyses produced at the basin scale by the Mediterranean ocean Forecasting System (MFS) (http://gnoo.bo.ingv.it/mfs). The system produces short-term ocean forecasts for the following ten days. Analyses are produced weekly using a daily assimilation cycle. The analyses are compared with independent data from buoys, where available, and with the assimilated data before the data are inserted. In this work we have considered 53 ten days forecasts produced from 16 August 2005 to 15 August 2006. The forecast skill is evaluated by means of root mean square error (rmse) differences, bias and anomaly correlations at different depths for temperature and salinity, computing differences between forecast and analysis, analysis and persistence and forecast and persistence. The Skill Score (SS) is defined as the ratio of the rmse of the difference between analysis and forecast and the rmse of the difference between analysis and persistence. The SS shows that at 5 and 30 m the forecast is always better than the persistence, but at 300 m it can be worse than persistence for the first days of the forecast. This result may be related to flow adjustments introduced by the data assimilation scheme. The monthly variability of SS shows that when the system variability is high, the values of SS are higher, therefore the forecast has higher skill than persistence. We give evidence that the error growth in the surface layers is controlled by the atmospheric forcing inaccuracies, while at depth the forecast error can be interpreted as due to the data insertion procedure. The data, both in situ and satellite, are not homogeneously distributed in the basin; therefore, the quality of the analyses may be different in different areas of the basin.

A new numerical general circulation ocean model for the Mediterranean Sea has been implemented nested within an Atlantic general circulation model within the framework of the Marine Environment and Security for the European Area project (MERSEA, Desaubies, 2006). A 4-year twin experiment was carried out from January 2004 to December 2007 with two different models to evaluate the impact on the Mediterranean Sea circulation of open lateral boundary conditions in the Atlantic Ocean. One model considers a closed lateral boundary in a large Atlantic box and the other is nested in the same box in a global ocean circulation model. Impact was observed comparing the two simulations with independent observations: ARGO for temperature and salinity profiles and tide gauges and along-track satellite observations for the sea surface height. The improvement in the nested Atlantic-Mediterranean model with respect to the closed one is particularly evident in the salinity characteristics of the Modified Atlantic Water and in the Mediterranean sea level seasonal variability.

This paper analyzes the relationship between deep sedimentary fluxes and ocean current vertical velocities in an offshore area of the Ionian Sea, the deepest basin of the Eastern Mediterranean Sea. Sediment trap data are collected at 500 m and 2800 m depth in two successive moorings covering the period September 1999–May 2001. A tight coupling is observed between the upper and deep traps and the estimated particle sinking rates are more than 200 m day−1. The current vertical velocity field is computed from a 1/16°×1/16° Ocean General Circulation Model simulation and from the wind stress curl. Current vertical velocities are larger and more variable than Ekman vertical velocities, yet the general patterns are alike. Current vertical velocities are generally smaller than 1 m day−1: we therefore exclude a direct effect of downward velocities in determining high sedimentation rates. However we find that upward velocities in the subsurface layers of the water column are positively correlated with deep particle fluxes. We thus hypothesize that upwelling would produce an increase in upper ocean nutrient levels – thus stimulating primary production and grazing – a few weeks before an enhanced vertical flux is found in the sediment traps. High particle sedimentation rates may be attained by means of rapidly sinking fecal pellets produced by gelatinous macro-zooplankton. Other sedimentation mechanisms, such as dust deposition, are also considered in explaining large pulses of deep particle fluxes. The fast sinking rates estimated in this study might be an evidence of the efficiency of the biological pump in sequestering organic carbon from the surface layers of the deep Eastern Mediterranean basins.

This study describes a new model implementation for the Mediterranean Sea with what is currently the highest vertical resolution over the Mediterranean basin. The resolution is of 1/16°×1/16° in the horizontal and has 72 unevenly spaced vertical levels. This model has been developed in the frame of the EU-MFSTEP project and is the operational forecast model currently used at the basin scale. The model considers an implicit free surface and this characteristic enhances the model's capability to simulate the sea surface height variability and the net transport at the Strait of Gibraltar. In this study we show the calibration/validation experiments performed before and after the model was used for forecasting. The first experiment consists of a six-year simulation forced by a perpetual year forcing, and the other experiment is a simulation from January 1997 to December 2004, forcing the model with 6-h atmospheric forcing fields from ECMWF. The model Sea Level Anomaly has been compared for the first time with satellite SLA and with ARGO data to provide evidence of the quality of the simulation. The results show that this model is capable of reproducing most of the variability of the general circulation in the Mediterranean Sea. However, some basic model inadequacies stand out and should be corrected in the near future.

This study presents the upgrade of the Optimal Interpolation scheme used in the basin scale assimilation scheme of the Mediterranean Forecasting System. The modifications include a daily analysis cycle, the assimilation of ARGO float profiles, the implementation of the geostrophic balance in the background error covariance matrix and the initialisation of the analyses. A series of numerical experiments showed that each modification had a positive impact on the accuracy of the analyses: The daily cycle improved the representation of the processes with the temporal variability shorter than a week, the assimilation of ARGO floats profiles significantly improved the salinity analyses quality, the geostrophically balanced background error covariances improved the accuracy of the surface elevation analyses, and the initialisation removed the barotropic adjustment in the forecast first time steps starting from the analysis.

A "ship of opportunity" program was launched as part of the Mediterranean Forecasting System Pilot Project. During the operational period (September 1999 to May 2000), six tracks covered the Mediterranean from the northern to southern boundaries approximately every 15 days, while a long eastwest track from Haifa to Gibraltar was covered approximately every month. XBT data were collected, sub-sampled at 15 inflection points and transmitted through a satellite communication system to a regional data centre. It was found that this data transmission system has limitations in terms of quality of the temperature profiles and quantity of data successfully transmitted. At the end of the MFSPP operational period, a new strategy for data transmission and management was developed. First of all, VOS-XBT data are transmitted with full resolution. Secondly, a new data management system, called Near Real Time Quality Control for XBT (NRT.QC.XBT), was defined to produce a parallel stream of high quality XBT data for further scientific analysis. The procedure includes: (1) Position control; (2) Elimination of spikes; (3) Re-sampling at a 1 metre vertical interval; (4) Filtering; (5) General malfunctioning check; (6) Comparison with climatology (and distance from this in terms of standard deviations); (7) Visual check; and (8) Data consistency check. The first six steps of the new procedure are completely automated; they are also performed using a new climatology developed as part of the project. The visual checks are finally done with a free-market software that allows NRT final data assessment. Key words. Oceanography: physical (instruments and techniques; general circulation; hydrography)

This paper describes the operational implementation of the data assimilation scheme for the Mediterranean Forecasting System Pilot Project (MFSPP). The assimilation scheme, System for Ocean Forecast and Analysis (SOFA), is a reduced order Optimal Interpolation (OI) scheme. The order reduction is achieved by projection of the state vector into vertical Empirical Orthogonal Functions (EOF). The data assimilated are Sea Level Anomaly (SLA) and temperature profiles from Expandable Bathy Termographs (XBT). The data collection, quality control, assimilation and forecast procedures are all done in Near Real Time (NRT). The OI is used intermittently with an assimilation cycle of one week so that an analysis is produced once a week. The forecast is then done for ten days following the analysis day. The root mean square (RMS) between the model forecast and the analysis (the forecast RMS) is below 0.7°C in the surface layers and below 0.2°C in the layers deeper than 200 m for all the ten forecast days. The RMS between forecast and initial condition (persistence RMS) is higher than forecast RMS after the first day. This means that the model improves forecast with respect to persistence. The calculation of the misfit between the forecast and the satellite data suggests that the model solution represents well the main space and time variability of the SLA except for a relatively short period of three – four weeks during the summer when the data show a fast transition between the cyclonic winter and anti-cyclonic summer regimes. This occurs in the surface layers that are not corrected by our assimilation scheme hypothesis. On the basis of the forecast skill scores analysis, conclusions are drawn about future improvements. Key words. Oceanography; general (marginal and semi-enclosed seas; numerical modeling; ocean prediction)

The Mediterranean Forecasting system Pilot Project has concluded its activities in 2001, achieving the following goals: 1. Realization of the first high-frequency (twice a month) Voluntary Observing Ship (VOS) system for the Mediterranean Sea with XBT profiles for the upper thermocline (0–700 m) and 12 n.m. along track nominal resolution; 2. Realization of the first Mediterranean Multidisciplinary Moored Array (M3A) system for the Near-Real-Time (NRT) acquisition of physical and biochemical observations. The actual observations consists of: air-sea interaction parameters, upper thermocline (0–500 m) temperature, salinity, oxygen and currents, euphotic zone (0–100 m) chlorophyll, nutrients, Photosinthetically Available Radiation (PAR) and turbidity; 3. Analysis and NRT dissemination of high quality along track Sea Level Anomaly (SLA), Sea Surface Temperature (SST) data from satellite sensors to be assimilated into the forecasting model; 4. Assembly and implementation of a multivariate Reduced Order Optimal Interpolation scheme (ROOI) for assimilation in NRT of all available data, in particular, SLA and VOS-XBT profiles; 5. Demonstration of the practical feasibility of NRT ten day forecasts at the Mediterranean basin scale with resolution of 0.125° in latitude and longitude. The analysis or nowcast is done once a week; 6. Development and implementation of nested regional (5 km) and shelf (2–3 km) models to simulate the seasonal variability. Four regional and nine shelf models were implemented successfully, nested within the forecasting model. The implementation exercise was carried out in different region/shelf dynamical regimes and it was demonstrated that one-way nesting is practical and accurate; 7. Validation and calibration of a complex ecosystem model in data reach shelf areas, to prepare for forecasting in a future phase. The same ecosystem model is capable of reproducing the major features of the primary producers’ carbon cycle in different regions and shelf areas. The model simulations were compared with the multidisciplinary M3A buoy observations and assimilation techniques were developed for the biochemical data. This paper overviews the methodological aspects of the research done, from the NRT observing system to the forecasting/modelling components and to the extensive validation/calibration experiments carried out with regional/shelf and ecosystem models. Key words. Oceanography: general (ocean prediction; instruments and techniques) Oceanography: physical (currents)

Multivariate vertical Empirical Orthogonal Functions (EOF) are calculated for the entire Mediterranean Sea both from observations and model simulations, in order to find the optimal number of vertical modes to represent the upper thermocline vertical structure. For the first time, we show that the large-scale Mediterranean thermohaline vertical structure can be represented by a limited number of vertical multivariate EOFs, and that the "optimal set" can be selected on the basis of general principles. In particular, the EOFs are calculated for the combined temperature and salinity statistics, dividing the Mediterranean Sea into 9 regions and grouping the data seasonally. The criterion used to establish whether a reduced set of EOFs is optimal is based on the analysis of the root mean square residual error between the original data and the profiles reconstructed by the reduced set of EOFs. It was found that the number of EOFs needed to capture the variability contained in the original data changes with geographical region and seasons. In particular, winter data require a smaller number of modes (4–8, depending on the region) than the other seasons (8–9 in summer). Moreover, western Mediterranean regions require more modes than the eastern Mediterranean ones, but this result may depend on the data scarcity in the latter regions. The EOFs computed from the in situ data set are compared to those calculated using data obtained from a model simulation. The main results of this exercise are that the two groups of modes are not strictly comparable but their ability to reproduce observations is the same. Thus, they may be thought of as equivalent sets of basis functions, upon which to project the thermohaline variability of the basin. Key words. Oceanography: general (water masses) – Oceanography: physical (hydrography; instruments and techniques)

A modelling system for the Adriatic Sea has been built within the framework of the Mediterranean Forecasting System Pilot Project. The modelling system consists of a hierarchy of three numerical models (whole Mediterranean Sea, whole Adriatic Sea, Northern Adriatic Basin) coupled among each other by simple one-way, off-line nesting techniques, to downscale the larger scale flow field to highly resolved coastal scale fields. Numerical simulations have been carried out under climatological surface forcing. Simulations were aimed to assess the effectiveness of the nesting techniques and the skill of the system to reproduce known features of the Adriatic Sea circulation phenomenology (main circulation features, dense water formation,flow at the Otranto Strait and coastal circulation characteristics over the northern Adriatic shelf), in view of the pre-operational use of the modelling system. This paper describes the modelling system setup, and discusses the simulation results for the whole Adriatic Sea and its northern basin, comparing the simulations with the observed climatological circulation characteristics. Results obtained with the northern Adriatic model are also compared with the corresponding simulations obtained with the coarser resolution Adriatic model. Key words. Oceanography: general (continental shelf processes; numerical modelling) – Oceanography: physical (general circulation)

In this paper we show results from numerical simulations carried out with a complex biogeochemical fluxes model coupled with a one-dimensional high-resolution hydrodynamical model and implemented at three different locations of the northern Adriatic shelf. One location is directly affected by the Po River influence, one has more open-sea characteristics and one is located in the Gulf of Trieste with an intermediate behavior; emphasis is put on the comparison with observations and on the functioning of the northern Adriatic ecosystem in the three areas. The work has been performed in a climatological context and has to be considered as preliminary to the development of three-dimensional numerical simulations. Biogeochemical model parameterizations have been ameliorated with a detailed description of bacterial substrate utilization associated with the quality of the dissolved organic matter (DOM), in order to improve the models capability in capturing the observed DOM dynamics in the basin. The coupled model has been calibrated and validated at the three locations by means of climatological data sets. Results show satisfactory model behavior in simulating local seasonal dynamics in the limit of the available boundary conditions and the one-dimensional implementation. Comparisons with available measurements of primary and bacterial production and bacterial abundances have been performed in all locations. Model simulated rates and bacterial dynamics are in the same order of magnitude of observations and show a qualitatively correct time evolution. The importance of temperature as a factor controlling bacteria efficiency is investigated with sensitivity experiments on the model parameterizations. The different model behavior and pelagic ecosystem structure developed by the model at the three locations can be attributed to the local hydrodynamical features and interactions with external inputs of nutrients. The onset of the winter/spring bloom in the climatological simulations is primarily driven by local stratification conditions. During summer the major carbon-transfer pathway developed by the model is the microbial web at all the sites, indicating that a large fraction of organic matter is processed through bacteria during productive periods, as suggested by field observations. The site directly influenced by riverine inputs differs from the others, showing a more alternate shifting among trophic pathways. Applying the conceptual scheme proposed by Legendre and Rassoulzadegan (Ophelia, 41, 153-172, 1995), it can be recognized as a herbivorous spring phase tightly followed by a microbial loop development, a summer microbial web phase and a multivorous trophic web pattern during autumn with a subsequent recovery of microbial processes. Results are discussed in terms of regime shifting from transient to stable water column conditions.Key words. Oceanography: general (continental shelf processes; numerical modelling) – Oceanography: biological and chemical (biochemistry and food chains)