Operational Oceanography Research Articles

Assessment of high-resolution regional ocean reanalysis K-ORA22 for the Northwest Pacific

The Korea Institute of Ocean Science and Technology developed the Korea Operational Oceanographic System-Ocean Predictability Experiment for Marine Environment (KOOS-OPEM), a high-resolution (1/24°, 51 vertical levels) ocean prediction model for the Northwest Pacific Ocean that incorporates ensemble optimal interpolation. In this study, we present KOOS-OPEM ReAnalysis version 2022 (K-ORA22), which covers the period from 2011 to 2022. We conducted a comparative analysis between K-ORA22 and other high-resolution (1/10°–1/12°) global reanalyses, including the Hybrid Coordinate Ocean Model, Global Ocean Reanalysis and Simulation (GLORYS), and Bluelink ReAnalysis (BRAN), to demonstrate the reproducibility and reliability of regional characteristics. Statistical comparisons revealed that while K-ORA22 exhibited some warm biases, its sea surface temperature (SST) anomaly correlation after removing the seasonal cycle was approximately 0.87, comparable to other reanalyses. Additionally, K-ORA22 effectively reproduced coastal upwelling, which is characterized by a sharp decrease in SST, as observed by marine meteorological buoys in the Southwest of the East/Japan Sea. K-ORA22 exhibits a warm bias of approximately 0.50 °C around 200 m, slightly higher than those of GLORYS and BRAN, while maintaining a low salinity bias in the subsurface. Notably, K-ORA22 outperformed the other reanalyses in accurately reproducing the unique characteristics of North Pacific and East Sea intermediate waters, characterized by a salinity minimum layer. In addition, K-ORA22 stands out in its ability to accurately reproduce the Yellow Sea Cold Water Mass with a low-temperature root-mean-square error (RMSE) of 0.76 °C in the Yellow Sea (YS) region. However, it exhibited the highest RMSE for salinity in the YS region and Korea/Tsushima Strait, indicating a potential overestimation of river discharge from Korea and China. While the sea surface height (SSH) anomaly correlation of K-ORA22 did not surpass 0.80 in the entire region because of limitations in the background error covariance used, its ability to reproduce the Kuroshio path was comparable to those of other reanalysis datasets. In conclusion, K-ORA22 excels in reproducing the unique characteristics of Korean marginal seas. Still, it exhibits weaknesses, such as the overestimation of river discharge and a somewhat limited ability to simulate SSH variability, compared with other global reanalyses. We plan to enhance K-ORA22 by updating background error covariance, addressing biases related to river discharge and assimilating the best available in situ observations and satellite data.

New Measuring and Data Transmission Equipment for Operational Oceanography at the Gelendgik Black Sea Test Site of Institute of Oceanology of the RAS

The design and principles of operation of the bottom multi-modem station MDS-II, located in the coastal zone (depth of location — 25 m) of the northeastern part of the Black Sea at the Gelendzhik Test Site of IO RAS are described. The station is connected to the coastal center by means of a bottom fiber-optic cable, through which power is supplied to the station, and online transmission of measurement data takes place. The station is an underwater server to which one can connect a measuring device and get a real-time access to it, as well as remotely control on its operation. The design of an automatic stationary station for vertical sounding (SSVS) of water column, which is also used at the Gelendzhik Test Site, is also described. This station is installed close to the MDS-II multi-modem station and is connected to one of its modems. The station consists of a bottom electric winch installed on the seabed and a floating module (probe) on a cable line wound around the winch drum. When the command ʺsoundingʺ is given, the cable unwinds and the floating module, equipped with temperature and pressure sensors, floats and measures the water temperature profile from the bottom layer to the sea surface. Then the cable is winding on a drum, and the floating module returns to the bottom layer. A prototype of a new SSVS is being developed, which will allow sounding of the water layer with a thickness of up to 100 m. It will be equipped with a multi-parameter probe that makes joint measurements of hydrophysical and bio-optical parameters.

Combining neural networks and data assimilation to enhance the spatial impact of Argo floats in the Copernicus Mediterranean biogeochemical model

Abstract. Biogeochemical-Argo (BGC-Argo) float profiles provide substantial information on key vertical biogeochemical dynamics and have been successfully integrated in biogeochemical models via data assimilation approaches. Although BGC-Argo assimilation results have been encouraging, data scarcity remains a limitation with respect to their effective use in operational oceanography. To address availability gaps in the BGC-Argo profiles, an observing system experiment (OSE) that combines a neural network (NN) and data assimilation (DA) was performed here. A NN was used to reconstruct nitrate profiles, starting from oxygen profiles and associated Argo variables (pressure, temperature, and salinity), while a variational data assimilation scheme (3DVarBio) was upgraded to integrate BGC-Argo and reconstructed observations in the Copernicus Mediterranean operational forecast system (MedBFM). To ensure the high quality of oxygen data, a post-deployment quality control method was developed with the aim of detecting and eventually correcting potential sensors drift. The Mediterranean OSE features three different set-ups: a control run without assimilation; a multivariate run with assimilation of BGC-Argo chlorophyll, nitrate, and oxygen; and a multivariate run that also assimilates reconstructed observations. The general improvement in the skill performance metrics demonstrated the feasibility of integrating new variables (oxygen and reconstructed nitrate). Major benefits have been observed with respect to reproducing specific biogeochemical-process-based dynamics such as the nitracline dynamics, primary production, and oxygen vertical dynamics. The assimilation of BGC-Argo nitrate corrects a generally positive bias of the model in most of the Mediterranean areas, and the addition of reconstructed profiles makes the corrections even stronger. The impact of enlarged nitrate assimilation propagates to ecosystem processes (e.g. primary production) at a basin-wide scale, demonstrating the importance of the assimilation of BGC-Argo profiles in forecasting the biogeochemical ocean state.

Prediction of the sea surface temperature in Perhentian Islands by EMD-LSTM model

The increase in the sea surface temperature (SST) is currently an important factor in the decline of coral reef ecosystems worldwide, and SST prediction has always been an important research direction in operational oceanography. This paper collects and analyses the buoy data deployed at Malaysian Perhentian islands and combines CRW data to develop coral bleaching warning products for Malaysian Perhentian islands. The Long Short-Term Memory Network(LSTM) and Empirical Mode Decomposition(EMD)-LSTM methods are used to research the SST prediction, and the differences between the two prediction methods were compared. The research results show that both the LSTM prediction model and the EMD-LSTM prediction model can accurately predict SST, with almost all prediction errors at 0.11°C and 0.01°C, respectively.

Removing the systematic errors of the model in operational oceanography forecasting system using data assimilation method

For the operational oceanography forecast, the synoptic forecast error is partly from the long-term systematic bias of the model, which can be partly counteracted by adjusting the values of the physical parameters. To this end, a four-dimensional optimization system is implemented into the South China Sea operational oceanography forecasting system, to adjust the values of multi-parameters using data assimilation method. By assimilating Argo temperature profiles of 51 days in the model domain, five physical parameters (coefficients of horizontal/vertical diffusion/viscosity and linear bottom drag) of the model have been adjusted simultaneously, and then the optimal values are obtained. The RMSE of temperature simulations in the assimilation window decreases from 1.17 to 0.97 K, when using the optimal values. The validation of the freerun experiments shows that the temperature RMSE decreases from 0.97 to 0.88 K, which indicates that the optimal values are still valid in a longer and independent period. Finally, the validation of the hindcast experiments shows that at the synoptic scale the temperature RMSE decreases from 0.90 to 0.80 K and other variables also present improvements. It hints that it is feasible to reduce the synoptic forecast errors by adjusting the parameter values at the climatological scale to partly counteract the systematic bias of the model. Therefore, it also provides a potential pathway to improve the synoptic forecast skill for the operational oceanography forecasting system.

Operational Oceanography in Ports and Coastal Areas, Applications for the Management of Pollution Events

Maritime safety and the protection of the marine environment were the primary objectives of two European projects that the National Research Council of Italy had participated in, with numerical applications in two areas located in the northern part of Sardinia, Italy. Specifically, two operational Numerical Prediction Systems (NPS) for pollution risk management were developed; the first was applied to the area of the Bonifacio Strait and the Gulf of Asinara and the second to the port of Olbia. These systems are composed of many oceans and particle tracking numerical models. They are forced with meteorological and ocean data provided by the European Centre for Medium-Range Weather Forecasts and Copernicus Marine Service and their outputs have been compared with in situ measurements for preliminary calibration. A web graphical interface was ad hoc designed, specifically responding to projects’ needs, providing online access to a 3-day oceanographic forecast and advanced diagnostic variables like Oil Stranding Time, Risk Score and Water Age. These products, along with the interactive web platform, prove invaluable for marine spatial planning, prevention and emergency management at sea, for the use of competent governmental and local bodies.

New Measuring and Data Transmission Equipment for Operational Oceanography at the Gelendgik Black Sea Test Site of the Shirshov Institute of Oceanology, Russian Academy of Sciences

New Measuring and Data Transmission Equipment for Operational Oceanography at the Gelendgik Black Sea Test Site of the Shirshov Institute of Oceanology, Russian Academy of Sciences

Evaluating the Detection of Oceanic Mesoscale Eddies in an Operational Eddy-Resolving Global Forecasting System

In this study, a global analysis and forecasting system at 1/12° is built for operational oceanography at the National Marine Environmental Forecasting Center (NMEFC) by using the NEMO ocean model (NMEFC-NEMO). First, statistical analysis methods are designed to evaluate the performance of sea level anomaly (SLA) forecasting. The results indicate that the NMEFC-NEMO performs well in SLA forecasting when compared with the Mercator-PSY4, Mercator-PSY3, UK-FOAM, CONCEPTS-GIOPS and Bluelink-OceanMAPS forecasting systems. The respective root-mean-squared errors (RMSEs) of NMEFC-NEMO (Mercator PSY4) are 0.0654 m (0.0663 m) and 0.0797 m (0.0767 m) for the lead times of 1 and 7 days. The anomaly correlation coefficients between forecasting and observations exceed 0.8 for the NMEFC-NEMO and Mercator-PSY4 systems, suggesting that the accuracy of SLA predicted using NMEFC-NEMO is comparable to Mercator PSY4 and superior to other forecasting systems. Moreover, the global spatial distribution of oceanic eddies are effectively represented in NMEFC-NEMO when compared to that in the HYCOM reanalysis, and the detection rate reaches more than 90% relative to HYCOM reanalysis. Regarding the strong eddies in the Kuroshio region, the NMEFC-NEMO reproduces the characteristic for anticyclonic and cyclonic eddies merging and splitting alternatively. As for the detective eddies in the Gulf Stream, NMEFC-NEMO effectively represents the spatial distribution of mesoscale eddies from different seasons. The amplitude of oceanic eddies, including both cyclones and anticyclones, were much stronger on 1 July 2019 than 1 January 2019. Overall, NMEFC-NEMO has a superior performance in SLA forecasting and effectively represents the oceanic mesoscale eddies for operational oceanography.

Tar pollution event (2021) at the Southeastern Levantine oligotrophic basin, short-term impacts and operational oceanography perspectives

The Levantine basin (LB) in the Southeastern Mediterranean Sea is a high-risk oil pollution hot spot owing to its dense maritime traffic and intense oil and gas exploration and exploitation activities. In February 2021 the Israeli LB shorelines were impacted by an exceptional tar pollution event (~550 tons; average distribution: ~3 kg tar m−1 front beach) of an unknown oil spill source. Here we report on the immediate numerical modelling assessment of the oil spill propagation and tar distribution; operational use of underwater gliders for tracking water column anomalies of dissolved polycyclic aromatic hydrocarbons (PAHs) and turbidity signals; the beached tar composition and amounts and the short-term response of the microbial population along the ~180 km shoreline. This pollution event emphasizes the need for improving the early warning systems for oil spills and implementing continuous operational monitoring at high-risk, ecologically sensitive and valuable resource areas like the Israeli LB waters.

Delayed-mode reprocessing of in situ sea level data for the Copernicus Marine Service

Abstract. The number of tide gauges providing coastal sea level data has significantly increased in recent decades. They help in the issue of coastal hazard warnings, in the forecasting (indirectly through models) of storm surges and tsunamis, and in operational oceanography applications. These data are automatically quality controlled in near-real time in the Copernicus Marine Service. A new initiative seeks to provide delayed-mode reprocessed data for the Copernicus Marine Service by developing a new product and upgrading the software used in its automated quality control. Several new modules, such as buddy checking or the detection of attenuated data, are implemented. The new product was launched in November of 2022. The entire reprocessing is discussed in detail. An example of the information that can be extracted from the delayed-mode reprocessed product is also given.

A Global-Ocean-Data Assimilation for Operational Oceanography

In this study, a global-ocean-data-assimilation system based on the three-dimensional variational (3DVAR) scheme is built for operational oceanography. The available observations include satellite altimetry; the satellite-measured sea-surface temperature (SST); and T/S profiles from Argo floats, which are assimilated to provide the initial condition of the global-ocean forecasting. The statistical analysis methods are designed to assess the performance of the data-assimilation scheme, and the results show that the analysis SST fields agree well with OSTIA and MGDSST, and the corresponding root-mean-square errors are, respectively, 0.523 and 0.548 °C. Moreover, the analysis sea-surface-height fields are well represented at the middle and low latitudes and have a slightly greater difference in the regions with strong mesoscale eddies. The variations in the vertical distribution of the forecasting temperature profiles resemble those of the GTS buoy observation. The forecasting salinity profiles correspond well to GTS observations, except with a weaker cold bias between the depths 100 and 200 m (about 0.2 PSU) at buoy station 2901494. Overall, our 3DVAR assimilation system plays a significant role in improving the accuracy of analysis and forecasting fields for operational oceanography.

Uncertainty Quantification When Learning Dynamical Models and Solvers With Variational Methods

AbstractIn geosciences, data assimilation (DA) addresses the reconstruction of a hidden dynamical process given some observation data. DA is at the core of operational systems such as weather forecasting, operational oceanography and climate studies. Beyond the reconstruction of the mean or most likely state, the inference of the state posterior distribution remains a key challenge, that is, quantify uncertainties as well as to inform intrinsical stochastic variabilities. Indeed, DA schemes, such as variational DA and Kalman methods, can have difficulty in dealing with complex non‐linear processes. A growing literature investigates the cross‐fertilization of DA and machine learning. This study proposes an end‐to‐end neural scheme based on a variational Bayes inference formulation to jointly address DA and uncertainty quantification. It combines an Evidence Lower BOund variational cost to a trainable gradient‐based solver to infer the state posterior probability distribution function given observation data. The inference of the posterior and the trainable solver are learnt jointly. We demonstrate the relevance of the proposed scheme for a Gaussian parameterization of the posterior and different case‐study experiments, including Lorenz 63 dynamics and river flow measurements. A benchmark with respect to state‐of‐the‐art schemes is provided.

The Influence of the A Priori Uncertainty of the Shallow Sea Sound Channel Model on the Vertical Array Gain

The purpose of this paper is to numerically demonstrate and comparatively analyze the critically strong and ambiguous impact of the a priori uncertainty of a shallow sea waveguide model in its main physical parameters on the output performance of model-based methods for spatial processing of multimode signals received by a vertical antenna array. The scenario is specified when a relatively weak signal of a remote underwater source is received against the background of intensive interference excited by a subsurface source (like a ship, for example) and ambient sea noise excited by wind waves. The considered array processing methods include matched-signal processing, optimal processing of the signal on the background of interference and noise, and suboptimal processing based on matched-mode array filtering of one of the signal-carrying modes with adaptive selection of its number. Quantitative estimates are obtained from above for the environment uncertainties, or model errors, with respect to the sound velocity in the water column and geoacoustic parameters of the underlying bottom, at which the array gain loss does not exceed a given level. It is shown that such estimates are very different both for different environmental parameters and for processing methods, with the determining role played by the conditions of useful signal reception, namely, the modal composition and intensity levels of the interference and sea noise at the array input. The problem statement and results are considered to be useful to detail the requirements for operational oceanography tools designed to support the effective operation of sonar antenna systems in real sea environments.

The Influence of the A Priori Uncertainty of the Shallow Sea Sound Channel Model on the Vertical Array Gain

The purpose of this paper is to numerically demonstrate and comparatively analyze the critically strong and ambiguous impact of the a priori uncertainty of a shallow sea waveguide model in its main physical parameters on the output performance of model-based methods for spatial processing of multimode signals received by a vertical antenna array. The scenario is specified when a relatively weak signal of a remote underwater source is received against the background of intensive interference excited by a subsurface source (like a ship, for example) and ambient sea noise excited by wind waves. The considered array processing methods include matched-signal processing, optimal processing of the signal on the background of interference and noise, and suboptimal processing based on matched-mode array filtering of one of the signal-carrying modes with adaptive selection of its number. Quantitative estimates are obtained from above for the environment uncertainties, or model errors, with respect to the sound velocity in the water column and geoacoustic parameters of the underlying bottom, at which the array gain loss does not exceed a given level. It is shown that such estimates are very different both for different environmental parameters and for processing methods, with the determining role played by the conditions of useful signal reception, namely, the modal composition and intensity levels of the interference and sea noise at the array input. The problem statement and results are considered to be useful to detail the requirements for operational oceanography tools designed to support the effective operation of sonar antenna systems in real sea environments.

How useful are mispointing phase SARAL/AltiKa geophysical products for ocean applications?

SARAL/AltiKa, the first microwave altimeter operating at Ka-band frequency, recently completed nine years of operations in orbit. During these years, it has catered to many applications related to operational oceanography, climate sciences, hydrology and cryosphere. More specifically, in oceanography, SARAL has contributed immensely to operational wave and circulation modelling, eddy detection/tracking, ocean current generation and many more. However, since Feb 2019, SARAL has moved from the drifting phase (DP) to the mispointing phase (MP) due to the malfunctioning of the star sensor of the spacecraft. In this study, we analyse the instrument’s performance and its waveforms during its ongoing MP. We find out that during the MP, significant wave height (SWH) measurements are anomalously high between 18 and 24 m, and wind speed measurements are between 16 and 19 m/s. In sea surface height anomaly (SSHA), there is a steady rise in negative values during the MP. In the return waveform, ∼15% degradation in Brown-type waveforms in the open ocean region is noticed. These changes significantly impact the SARAL applications. Two important applications of wave forecast and eddy detection are discussed here as examples. Following this, we also recommend using provided quality flags so that the data can be further explored for various ocean applications.

Modelling CO2 budget of mussel farms across the Mediterranean Sea.

The role of bivalve aquaculture as a carbon sink is highly debated, without a general consensus on the components to include in the budget. This study proposes to estimate the terms of the budget using a scope-for-growth-based model. The model was applied at 12 Mediterranean sites, with environmental forcings provided by operational oceanography data spanning over 12 years. Mussels were found to be slight sinks, with a limited variability across sites, if all components of the budget, i.e. accumulation in soft tissue, emissions associated with calcification and respiration, are included. The differences found among stations concerning the calcification and soft tissue contributions to the budget were found to be related to site-specific productivity and water chemistry parameters. This led to the identification of a set of meta-models, which could be used for relating the budget to local conditions, at a screening level, rendering them useful for optimal site selection.

EuroGOOS roadmap for operational coastal downstream services

The EuroGOOS Coastal working group examines the entire coastal value chain from coastal observations to services for coastal users. The main objective of the working group is to review the status quo, identify gaps and future steps needed to secure and improve the sustainability of the European coastal service provision. Within this framework, our white paper defines a EuroGOOS roadmap for sustained “community coastal downstream service” provision, provided by a broad EuroGOOS community with focus on the national and local scale services. After defining the coastal services in this context, we describe the main components of coastal service provision and explore community benefits and requirements through sectoral examples (aquaculture, coastal tourism, renewable energy, port, cross-sectoral) together with the main challenges and barriers to user uptake. Technology integration challenges are outlined with respect to multiparameter observations, multi-platform observations, the land-coast-ocean continuum, and multidisciplinary data integration. Finally, the technological, financial, and institutional sustainability of coastal observing and coastal service provision are discussed. The paper gives special attention to the delineation of upstream and downstream services, public-private partnerships and the important role of Copernicus in better covering the coastal zone. Therefore, our white paper is a policy and practice review providing a comprehensive overview, in-depth discussion and actionable recommendations (according to key short-term or medium-term priorities) on the envisaged elements of a roadmap for sustained coastal service provision. EuroGOOS, as an entity that unites European national operational oceanography centres, research institutes and scientists across various domains within the broader field of operational oceanography, offers to be the engine and intermediary for the knowledge transfer and communication of experiences, best practices and information, not only amongst its members, but also amongst the different (research) infrastructures, institutes and agencies that have interests in coastal oceanography in Europe.

Verifying Measurements of Surface Current Velocities by X-Band Coherent Radar Using Drifter Data

Introduction. Conventional contact measurements of hydrographic parameters frequently fail to provide the necessary accuracy of data in the field of water area monitoring. This problem can be solved using coherent radars enabling direct measurements of surface current velocities.Aim. To establish the accuracy of surface current velocities measured by a Doppler radar using drifter data.Materials and methods. In June 2022, coastal operational oceanography studies were conducted at the hydrophysical test site of the Institute of Oceanology of the Russian Academy of Sciences in the Black Sea near Gelendzhik. Measurements were carried out using a coherent X-band radar installed on the Ashamba research vessel simultaneously with drifter experiments using Lagrangian drifters of the near-surface layer with an underwater 0.5 m sail. Coordinates were transmitted via mobile communication. The drifter data on the current velocity and direction were used to verify radar measurements. Measurements were taken onboard of the research vessel at a low speed and different distances from the shore, near the drifters. The tracks of the vessel and drifters were recorded simultaneously. Processing of the radar data involved obtaining Doppler spectra of signals to estimate the dynamic processes on the sea surface, including the current velocity.Results. Radial components of the near-surface current velocity were calculated. Then, the current velocity values obtained based on the drifter and radar data were compared.Conclusion. The present work makes a contribution to the advancement of methods for measuring surface currents from the board of a moving ship by Doppler radars. The obtained results confirm the suitability of the radar hardware and software and signal processing algorithms for measuring currents. The radar measurement data were found agree well with drifter data in the velocity range from 15 cm/s.

Oceanic and ecological response to native Typhoons Cempaka and Lupit (2021) along the northern South China Sea continental shelf: comparison and evaluation of global and regional Operational Oceanography Forecasting Systems

The Global Operational Oceanography Forecasting System from the Mercator Ocean (MO) and the regional South China Sea Operational Oceanography Forecasting System (SCSOFSv2) were compared and evaluated using in situ and satellite observations, with a focus on the oceanic and ecological response to two consecutive native typhoons, Cempaka and Lupit, that occurred in July–August 2021. Results revealed a better simulation of the chlorophyll a (Chla) structure by SCSOFSv2 and a better simulation of the temperature profile by MO in the Pearl River Estuary. In addition, SCSOFSv2 sea surface temperature (SST) and MO Chla variations corresponded well with observations along the northern SCS shelf. Simulated maximum SST cooling was larger and 2–3 days earlier than those observations. Maximum Chla was stronger and led the climatological average by 2 days after the typhoon passage. Typhoon-induced vertical variations of Chla and NO3 indicated that different Chla bloom processes from coastal waters to the continental shelf. Discharge brought extra nutrients to stimulate Chla bloom in coastal waters, and model results revealed that its impact could extend to the continental shelf 50–150 km from the coastline. However, bottom nutrients were uplifted to contribute to Chla enhancement in the upper and middle layers of the shelf. Nutrients transported from the open sea along the continental slope with the bottom cold water could trigger Chla enhancement in the Taiwan Bank. This study suggests considering strong tides and waves as well as regional dynamics to improve model skills in the future.

Regional dynamic co-management for sustainable fisheries and ecosystem conservation: a pilot analysis in the Catalan Sea

The complexity of coastal fisheries, which often involve many gears with cross-impacts on various species and life stages, requires a management system that is able to integrate these multiple interactions in order to gradually achieve sustainability. In this paper, we argue that regional co-management can appropriately address the complex interactions between fisheries, including those with other potentially conflicting human activities. Our results, notably obtained through a questionnaire to local fishers’ representatives mainly on bottom trawl fisheries in the Catalan Sea region, show, however, that improved mutual understanding through effective communication and long-term collaboration between stakeholders, and in particular between fishers and scientists, is essential to ensure the successful implementation of fisheries co-management. In addition to balancing the voices of the many stakeholders, co-management needs to be further improved by developing multi-species, multi-gear and multi-use approaches to the oceans. This improvement could in turn support the effectiveness of co-decisions, as they would be based on the recognised administrative structure of co-management committees and sound scientific guidance that addresses both ecosystem protection and sustainable fisheries profitability. Dynamic management over time and space, using real-time essential fish habitat from operational oceanography, can help to make the co-management process more robust by improving collaboration between stakeholders and the effectiveness of measures in a changing environment. The decision-making, social and ecological components are described as integral and dependent parts of the co-management system, with priority given to mutual understanding between stakeholders. This integrated co-management framework is flexible enough to take into account regional complexity, but also national legislation and the EU Common Fisheries Policy, which all promote sustainable use of the oceans and protection of the ecosystem.