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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.

While the (re-)establishment of Blue Carbon Ecosystems (BCE) is seen as an important tool to mitigate climate change, the credibility of such nature-based solutions has been marred by recent revelations ranging from weak accounting to malpractice. In light of this, there is a clear need to develop monitoring, reporting and verification (MRV) systems towards the reliable, practical, and accurate accounting of additional and durable carbon dioxide removal (CDR). We propose the development of a Blue Carbon Ecosystem Digital Twin (BCE-DT) as a practical solution, integrating real-time data and models into What-If Scenarios of CDR aimed at the quantification of CDR additionality and durability. Critically, such a solution would be amenable to projects across a broad range in spatial scale and ecosytem type. In parallel, we propose the creation of an independent and not-for-profit Standards Development Organization (SDO) for the management of this Digital Twin and oversight of the certification process based on MRV. Considering the interwoven nature of the scientific and policy/legal needs we raise, an improved dialogue and collaboration between the scientific and policy communities is clearly needed. We argue that this BCE-DT, along with its oversight and implementation by a SDO, would fit this niche and support the fair and accurate implementation of MRV critically needed for BCE-based CDR to proceed.

The secondary circulation in a predominantly well-mixed estuarine tidal inlet is examined with three-dimensional numerical simulations of the currents and density field in the German Bight. Simulations analyze two complete neap and spring tidal cycles, inspired by cross-section measurements in the tidal inlet, with a focus on subtidal time scales. The study scrutinizes the lateral momentum balance and quantifies the individual forces that drive the residual flow on the cross-section. Forces (per unit mass) from the covariance between eddy viscosity and tidal vertical shear (ESCO) play a role in the lateral momentum budget. During neap tide, the ESCO-driven flow is weak. Accelerations driven by advection dominate the subtidal secondary circulation, which shows an anti-clockwise rotation. During spring tide, the ESCO acceleration, together with the baroclinicity and centrifugal acceleration, drives a clockwise circulation (looking seaward). This structure counteracts the advection-induced flow, leading to the reversal of the secondary circulation. The decomposition of the lateral ESCO term contributors reveals that the difference in ESCO between neap and spring tides is attributed to the change in the vertical structure of lateral tidal currents, which are maximum near the bottom in spring tide. The findings highlight the role of the tidally varying vertical shears in the ESCO mechanism.

In this study, the effects of fully coupling the atmosphere, waves, and ocean compared with two-way-coupled simulations of either atmosphere and waves or atmosphere and ocean are analyzed. Two-year-long simulations (2017 and 2018) are conducted using the atmosphere–ocean–wave (AOW) coupled system consisting of the atmosphere model CCLM, the wave model WAM, and the ocean model NEMO. Furthermore, simulations with either CCLM and WAM or CCLM and NEMO are done in order to estimate the impacts of including waves or the ocean into the system. For the North Sea area, it is assessed whether the influence of the coupling of waves and ocean on the atmosphere varies throughout the year and whether the waves or the ocean have the dominant effect on the atmospheric model. It is found that the effects of adding the waves into the system already consisting of atmosphere and ocean model or adding the ocean to the system of atmosphere and wave model vary throughout the year. Which component has a dominant effect and whether the effects enhance or diminish each other depends on the season and variable considered. For the wind speed, during the storm season, adding the waves has the dominant effect on the atmosphere, whereas during summer, adding the ocean has a larger impact. In summer, the waves and the ocean have similar influences on mean sea level pressure (MSLP). However, during the winter months, they have the opposite effect. For the air temperature at 2 m height (T_2m), adding the ocean impacts the atmosphere all year around, whereas adding the waves mainly influences the atmosphere during summer. This influence, however, is not a straight feedback by the waves to the atmosphere, but the waves affect the ocean surface temperature, which then also feedbacks to the atmosphere. Therefore, in this study we identified a season where the atmosphere is affected by the interaction between the waves and the ocean. Hence, in the AOW-coupled simulation with all three components involved, processes can be represented that uncoupled models or model systems consisting of only two models cannot depict.

In this study, we apply probabilistic estimates of mean sea level (MSL) rise and a sub-set of regional climate model ensemble simulations to force a numerical model of the southern North Sea, downscaling projected sea level variability to the Elbe estuary that serves as a prototype for an industrialised meso-tidal estuary. The specific forcing combination enables a localised projection of future estuarine hydrodynamics accounting for the spread of projected global sea level rise and the spread of the regional climate projection due to internal variability. Under the applied high-emission scenario, the Elbe estuary shows high decadal rates of mean water level (MWL) rise beyond 19 mm y-1, increase in the tidal range of up to 14 mm y-1 and increase in extreme water levels of up to 18 mm y-1. The bandwidth of the estuarine response is also high. For example, the range of average monthly extreme water levels is up to 0.57 m due to the spread of projected global sea level rise, up to 0.58 m due to internal variability whereas seasonal range attains 1.99 m locally. In the lower estuary, the spread of projected global sea level rise dominates over internal variability. Internal variability, represented by ensemble spread, notably impacts the range of estuarine water levels and tidal current asymmetry in the shallow upper estuary. This area demonstrates large seasonal fluctuations of MWLs, the M2 tidal amplitude and monthly extreme water levels. On the monthly and inter-annual time scales, the MWL and M2 amplitude reveal opposite trends, indicative of a locally non-linear response to the decadal MSL rise enforced at the open boundary. Overall, imposed by the climate projections decadal change and MSL rise enhance the horizontal currents and turbulent diffusivities whereas internal variability locally mitigates sea level rise–driven changes in the water column. This work establishes a framework for providing consistent regionalised scenario-based climate change projections for the estuarine environment to support sustainable adaptation development.

Coastal restoration is often distrusted and, at best, implemented at small scales, which hampers its potential for coastal adaptation. Present technical, economic and management barriers stem from sectoral and poorly coordinated local interventions, which are insufficiently monitored and maintained, precluding the upscaling required to build up confidence in ecosystem restoration. The paper posits that there is enough knowledge, technology, financial and governance capabilities for increasing the pace and scale of restoration, before the onset of irreversible coastal degradation. We propose a systemic restoration, which integrates Nature based Solutions (NbS) building blocks, to provide climate-resilient ecosystem services and improved biodiversity to curb coastal degradation. The result should be a reduction of coastal risks from a decarbonised coastal protection, which at the same time increases coastal blue carbon. We discuss barriers and enablers for coastal adaptation-through-restoration plans, based on vulnerable coastal archetypes, such as deltas, estuaries, lagoons and coastal bays. These plans, based on connectivity and accommodation space, result in enhanced resilience and biodiversity under increasing climatic and human pressures. The paper concludes with a review of the interconnections between the technical, financial and governance dimensions of restoration, and discusses how to fill the present implementation gap.

Few studies have focused on the projected future changes in wave climate in the Chinese marginal seas. For the first time, we investigate the projected changes of the mean and extreme wave climate over the Bohai Sea, Yellow Sea, and East China Sea (BYE) during two future periods (2021–2050 and 2071–2100) under the RCP2.6 and RCP8.5 scenarios from the WAM wave model simulations with a resolution of 0.1°. This is currently the highest-resolution wave projection dataset available for the study domain. The wind forcings for WAM are from high-resolution (0.22°) regional climate model (RCM) CCLM-MPIESM simulations. The multivariate bias-adjustment method based on the N-dimensional probability density function transform is used to correct the raw simulated significant wave height (SWH), mean wave period (MWP), and mean wave direction (MWD). The annual and seasonal mean SWH are generally projected to decrease (-0.15 to -0.01 m) for 2021–2050 and 2071–2100 under the RCP2.6 and RCP8.5 scenarios, with statistical significance at a 0.1 level for most BYE in spring and for most of the Bohai Sea and Yellow Sea in annual and winter/autumn mean. There is a significant decrease in the spring MWP for two future periods under both the RCP2.6 and RCP8.5 scenarios. In contrast, the annual and summer/winter 99th percentile SWH are generally projected to increase for large parts of the study domain. Results imply that the projected changes in the mean and 99th percentile extreme waves are very likely related to projected changes in local mean and extreme surface wind speeds, respectively.

The mesoscale variability in the Mediterranean Sea is investigated through eddy detection techniques. The analysis is performed over 24 years (1993–2016) considering the three-dimensional (3D) fields from an ocean re-analysis of the Mediterranean Sea (MED-REA). The objective is to achieve a fit-for-purpose assessment of the 3D mesoscale eddy field. In particular, we focus on the contribution of eddy-driven anomalies to ocean dynamics and thermodynamics. The accuracy of the method used to disclose the 3D eddy contributions is assessed against pointwise in-situ measurements and observation-based data sets. Eddy lifetimes ≥ 2 weeks are representative of the 3D mesoscale field in the basin, showing a high probability (> 60%) of occurrence in the areas of the main quasi-stationary mesoscale features. The results show a dependence of the eddy size and thickness on polarity and lifetime: anticyclonic eddies (ACE) are significantly deeper than cyclonic eddies (CE), and their size tends to increase in long-lived structures which also show a seasonal variability. Mesoscale eddies result to be a significant contribution to the ocean dynamics in the Mediterranean Sea, as they account for a large portion of the sea-surface height variability at temporal scales longer than 1 month and for the kinetic energy (50–60%) both at the surface and at depth. Looking at the contributions to ocean thermodynamics, the results exhibit the existence of typical warm (cold) cores associated with ACEs (CEs) with exceptions in the Levantine basin (e.g., Shikmona gyre) where a structure close to a mode-water ACE eddy persists with a positive salinity anomaly. In this area, eddy-induced temperature anomalies can be affected by a strong summer stratification in the surface water, displaying an opposite sign of the anomaly whether looking at the surface or at depth. The results show also that temperature anomalies driven by long-lived eddies (≥ 4 weeks) can affect up to 15–25% of the monthly variability of the upper ocean heat content in the Mediterranean basin.

Uncertain parameters in a 3D barotropic circulation model of the German Bight are estimated with a variational optimisation approach. Surface current measurements from a high frequency (HF) radar are used in combination with acoustic Doppler current profiler (ADCP) and tide gauge observations as input for a 4DVAR assimilation scheme. The required cost function gradients are estimated using an adjoint model code. The focus of the study is on systematic errors of the model with the control vector including parameters of the bathymetry, bottom roughness, open boundary forcing, meteorological forcing as well as the turbulence model. The model uses the same bathymetry, open boundary forcing, and metereological forcing as the operational model run at the Federal Maritime and Hydrographic Agency (BSH). The baroclinic BSH model is used as a reference to put the performance of the optimised model into perspective. It is shown that the optimised model has better agreement with HF radar data and tide gauge observations both within the fortnight training period and the test period 1 month later. Current profile measurements taken at two platforms indicate that both models have comparable error magnitudes at those locations. The optimised model was also compared with independent drifter data. In this case, drifter simulations based on the BSH model and the respective operational drift model including some surface wave effects were used as a reference. Again, these comparison showed very similar results overall, with some larger errors of the tuned model in very shallow areas, where no observations were used for the tuning and surface wave effects, which are only explicitly considered in the BSH model, play a more important role. The tuned model seems to be slightly more dissipative than the BSH model with more energy entering through the western boundary and less energy leaving toward the north. It also became evident that the 4DVAR cost function minimisation process is complicated by momentum advection, which leads to non-differentiable dependencies of the model with respect to the control vector. It turned out that the omission of momentum advection in the adjoint code still leads to robust estimates of descent directions.

The Elbe estuary is a substantially engineered tidal water body that receives high loads of organic matter from the eutrophied Elbe river. The organic matter entering the estuary at the tidal weir is dominated by diatom populations that collapse in the deepened freshwater reach. Although the estuary’s freshwater reach is considered to manifest vertically homogenous density distribution (i.e., to be well-mixed), several indicators like trapping of particulate organic matter, near-bottom oxygen depletion and ammonium accumulation suggest that the vertical exchange of organic particles and dissolved oxygen is weakened at least temporarily. To better understand the causal links between the hydrodynamics and the oxygen and nutrient cycling in the deepened freshwater reach of the Elbe estuary, we establish a three-dimensional coupled hydrodynamical-biogeochemical model. The model demonstrates good skill in simulating the variability of the physical and biogeochemical parameters in the focal area. Coupled simulations reveal that this region is a hotspot of the degradation of diatoms and organic matter transported from the shallow productive upper estuary and the tidal weir. In summer, the water column weakly stratifies when at the bathymetric jump warmer water from the shallow upper estuary spreads over the colder water of the deepened mid reaches. Enhanced thermal stratification also occurs also in the narrow port basins and channels. Model results show intensification of the particle trapping due to the thermal gradients. The stratification also reduces the oxygenation of the near-bottom region and sedimentary layer inducing oxygen depletion and accumulation of ammonium. The study highlights that the vertical resolution is important for the understanding and simulation of estuarine ecological processes, because even weak stratification impacts the cycling of nutrients via modulation of the vertical mixing of oxygen, particularly in deepened navigation channels and port areas.

Recent advances in numerical modeling, satellite data, and coastal processes, together with the rapid evolution of CMEMS products and the increasing pressures on coastal zones, suggest the timeliness of extending such products toward the coast. The CEASELESS EU H2020 project combines Sentinel and in-situ data with high-resolution models to predict coastal hydrodynamics at a variety of scales, according to stakeholder requirements. These predictions explicitly introduce land discharges into coastal oceanography, addressing local conditioning, assimilation memory and anisotropic error metrics taking into account the limited size of coastal domains. This article presents and discusses the advances achieved by CEASELESS in exploring the performance of coastal models, considering model resolution and domain scales, and assessing error generation and propagation. The project has also evaluated how underlying model uncertainties can be treated to comply with stakeholder requirements for a variety of applications, from storm-induced risks to aquaculture, from renewable energy to water quality. This has led to the refinement of a set of demonstrative applications, supported by a software environment able to provide met-ocean data on demand. The article ends with some remarks on the scientific, technical and application limits for CMEMS-based coastal products and how these products may be used to drive the extension of CMEMS toward the coast, promoting a wider uptake of CMEMS-based predictions.

The ability of forecasting systems to simulate tropical cyclones is still insufficient, and currently, there is an increased interest in improving model performance for intense tropical cyclones. In this study, the impact of reducing surface drag at high wind speeds on modeling wind and wave conditions during the super Typhoon Lingling event over the northwest Pacific Ocean in 2019 is investigated. The model response with respect to the parameterization for momentum exchange at the ocean surface is demonstrated using a fully coupled regional atmosphere model (the Consortium for Small-Scale Modeling-Climate Limited-area Modeling, CCLM) and a wind wave model (WAM). The active two-way coupling between the atmosphere and ocean waves model is enabled through the introduction of sea state-dependent surface drag into the CCLM and updated winds into the WAM. The momentum exchange with the sea surface is modeled via the dependency of the roughness length (Z0) on the surface stress itself and, when applicable, on the wind speed. Several high-resolution runs are performed using one-way or two-way fully coupled regional atmosphere-wave (CCLM-WAM) models. The model simulations are assessed against the best track data as well as against buoy and satellite observations. The results show that the spectral nudging technique can improve the model’s ability to capture the large-scale circulation, track and intensity of Typhoon Lingling at regional scales. Under the precondition of large-scale constraining, the two-way coupling simulation with the proposed new roughness parameterization performs much better than the simulations used in older studies in capturing the maximum wind speed of Typhoon Lingling due to the reduced drag at extreme wind conditions for the new Z0.

Ensemble simulations are performed to quantify the internal variability of both regional atmospheric models and wave-atmosphere coupled model systems. Studies have shown that the internal variability in atmospheric models (e.g., wind or pressure fields) is increased during extreme events, such as storms. Comparing the magnitude of the internal variability of the atmospheric model with the internal variability of the coupled model system reveals that the internal variability can be reduced by coupling a wave model to the atmospheric model. While this effect is most evident during extreme events, it is still present in a general assessment of the mean internal variability during the whole study period. Furthermore, the role of this wave-atmosphere coupling can be distinguished from that of the internal variability of the atmospheric model since the impact of the wave-atmosphere interaction is larger than the internal variability. This is shown to be robust to different boundary conditions. One method to reduce the internal variability of the atmospheric model is to apply spectral nudging, the role of which in both the stand-alone atmospheric model and the coupled wave-atmosphere system is evaluated. Our analyses show that spectral nudging in both coupled and stand-alone ensemble simulations keeps the internal variability low, while the impact of the wave-atmosphere interaction remains approximately the same as in simulations without spectral nudging, especially for the wind speed and significant wave height. This study shows that in operational and climate research systems, the internal variability of the atmospheric model is reduced when the ocean waves and atmosphere are coupled. Clear influences of the wave-atmosphere interaction on both of these earth system components can be detected and differentiated from the internal model variability. Furthermore, the wave-atmosphere coupling has a positive effect on the agreement of the model results with both satellite and in situ observations.

An overview of the current European capacity in terms of operational modeling of marine and coastal systems is presented. This overview is compiled from a survey conducted in 2018–2019 among members of EuroGOOS and its related network of Regional Operational Oceanographic Systems, addressing the purposes, context and technical specificities of operational modeling systems. Contributions to the survey were received from 49 organizations around Europe, which represent 104 operational model systems simulating mostly hydrodynamics, biogeochemistry and sea waves. The analysis of contributions highlights the strengths and weaknesses of the current capacity from an operational point of view, and leads to the formulation of recommendations toward the improvement of marine operational modeling services in Europe. In particular, this study highlights the heterogeneity of the European operational modeling capacity in terms of atmospheric and land boundary conditions, its limited deployment for biogeochemical phenomena, and a restricted use of data assimilation methods. In order to improve the accuracy of their simulations, model operators aim toward a further refinement of spatial resolution, and identify the quality and accessibility of forcing data and the suitability of observations for data assimilation as restricting factors. The described issues call for institutional integration efforts and promotion of good practices to homogenize operational marine model implementations, and to ensure that external forcing datasets, observation networks and process formulations and parameterizations are adequately developed to enable the deployment of high-level operational marine and coastal modeling services across Europe.

The Black Sea Monitoring and Forecasting Center (BS-MFC) is the European reference service for the provision of ocean analyses, forecasts, and reanalyses in the Black Sea basin. It is part of the Copernicus Marine Environment and Monitoring Service (CMEMS) and ensures a high level of efficiency in terms of operations, science, and technology for predictions and the monitoring of physical and biogeochemical processes in the Black Sea. The operational BS-MFC framework is based on state-of-the-art numerical models for hydrodynamics, biogeochemistry, and waves; analysis, forecast, and reanalysis are provided on a spatial grid with about 3 km of horizontal resolution that covers the whole Black Sea basin (the Azov Sea is not included). The scientific assessment of BS-MFC products is performed by implementing a product quality dashboard that provides pre-qualification and operational model skills according to GODAE/OceanPredict standards. Novel interfaces based on high-resolution models are part of the scientific development plan to ensure a strong connection with the nearest seas from a modelling point of view, in particular with the Mediterranean Sea. To improve forecasting skills, dedicated online coupled systems are being developed, which involve physics, biogeochemistry, and waves together with the atmosphere and, in the future, with ensemble forecasting methodologies and river-ocean interfaces.

Operational oceanography can be described as the provision of routine oceanographic information needed for decision-making purposes. It is dependent upon sustained research and development through the end-to-end framework of an operational service, from observation collection to delivery mechanisms. The core components of operational oceanographic systems are a multi-platform observation network, a data management system, a data assimilative prediction system, and a dissemination/accessibility system. These are interdependent, necessitating communication and exchange between them, and together provide the mechanism through which a clear picture of ocean conditions, in the past, present, and future, can be seen. Ocean observations play a critical role in all aspects of operational oceanography, not only for assimilation but as part of the research cycle, and for verification and validation of products. Data assimilative prediction systems are advancing at a fast pace, in tandem with improved science and the growth in computing power. To make best use of the system capability these advances would be matched by equivalent advances in operational observation coverage. This synergy between the prediction and observation systems underpins the quality of products available to stakeholders, and justifies the need for sustained ocean observations. In this white paper, the components of an operational oceanographic system are described, highlighting the critical role of ocean observations, and how the operational systems will evolve over the next decade to improve the characterization of ocean conditions, including at finer spatial and temporal scales.

A major challenge for managing impacts and implementing effective mitigation measures and adaptation strategies for coastal zones affected by future sea level (SL) rise is our limited capacity to predict SL change at the coast on relevant spatial and temporal scales. Predicting coastal SL requires the ability to monitor and simulate a multitude of physical processes affecting SL, from local effects of wind waves and river runoff to remote influences of the large-scale ocean circulation on the coast. Here we assess our current understanding of the causes of coastal SL variability on monthly to multi-decadal timescales, including geodetic, oceanographic and atmospheric aspects of the problem, and review available observing systems informing on coastal SL. We also review the ability of existing models and data assimilation systems to estimate coastal SL variations and of atmosphere-ocean global coupled models and related regional downscaling efforts to project future SL changes. We discuss (1) observational gaps and uncertainties, and priorities for the development of an optimal and integrated coastal SL observing system, (2) strategies for advancing model capabilities in forecasting short-term processes and projecting long-term changes affecting coastal SL, and (3) possible future developments of sea level services enabling better connection of scientists and user communities and facilitating assessment and decision making for adaptation to future coastal SL change.

Integration of observations of the coastal ocean continuum, from regional oceans to shelf seas and estuaries/deltas with models, can substantially increase the value of observations and enable a wealth of applications. In particular, models can play a critical role at connecting sparse observations, synthesizing them, and assisting the design of observational networks; in turn, whenever available, observations can guide coastal model development. Coastal observations should sample the two-way interactions between nearshore, estuarine and shelf processes and open ocean processes, while accounting for the different pace of circulation drivers, such as the fast atmospheric, hydrological and tidal processes and the slower general ocean circulation and climate scales. Because of these challenges, high-resolution models can serve as connectors and integrators of coastal continuum observations. Data assimilation approaches can provide quantitative, validated estimates of Essential Ocean Variables in the coastal continuum, adding scientific and socioeconomic value to observations through applications (e.g., sea-level rise monitoring, coastal management under a sustainable ecosystem approach, aquaculture, dredging, transport and fate of pollutants, maritime safety, hazards under natural variability or climate change). We strongly recommend an internationally coordinated approach in support of the proper integration of global and coastal continuum scales, as well as for critical tasks such as community-agreed bathymetry and coastline products.

The ultimate goal of modern operational oceanography are end user oriented products with high scientific quality. Beneficiaries are the governmental services, coast and offshore based enterprises and research institutions that make use of the products generated by operational oceanography. Direct users are coastal managers, shipping, search and rescue, oil spill combat, offshore industry, ports, fishing, tourism, and recreation industry. Indirect beneficiaries, through climate forecasting based on ocean observations, are food, energy, water and medical suppliers. Availability of updated information on the actual state as well as forecast of marine environment is essential for the success and safety of maritime operations in the offshore industry. Various systems for the collection and presentation of marine data for the needs of different users have been developed and put in operation in the Black Sea. The systems are located both along the coast and in the open sea and the information they provide is used by both the maritime industry and the widest range of users. The Black Sea Monitoring and Forecasting Center in the frame of the Copernicus Marine Service is providing regular and systematic information about the physical state of the ocean, marine ecosystem and wave conditions in the Black Sea area, assimilating observations, keeping efficient operations, advanced technology and high quality modeling products. Combining and optimizing in situ, remote sensing, modeling and forecasting into a Black Sea observing system is a task that has to be solved, and that will allow to get a more complete and comprehensive picture of the state of the marine environment as well as to forecast future changes of physical and biogeochemical state of the Black Sea and the Black Sea ecosystem.

The Copernicus Marine Environment Monitoring Service (CMEMS) provides regular and systematic reference information on the physical and biogeochemical ocean and sea-ice state for the global ocean and the European regional seas. CMEMS serves a wide range of users (more than 15,000 users are now registered to the service) and applications. Observations are a fundamental pillar of the CMEMS value-added chain that goes from observation to information and users. Observations are used by CMEMS Thematic Assembly Centres (TACs) to derive high-level data products and by CMEMS Monitoring and Forecasting Centres (MFCs) to validate and constrain their global and regional ocean analysis and forecasting systems. This paper presents an overview of CMEMS, its evolution, and how the value of in situ and satellite observations is increased through the generation of high-level products ready to be used by downstream applications and services. The complementary nature of satellite and in situ observations is highlighted. Long-term perspectives for the development of CMEMS are described and implications for the evolution of the in situ and satellite observing systems are outlined. Results from Observing System Evaluations (OSEs) and Observing System Simulation Experiments (OSSEs) illustrate the high dependencies of CMEMS systems on observations. Finally future CMEMS requirements for both satellite and in situ observations are detailed.

This study performed several sensitivity experiments to investigate the impact of atmosphere−wave coupling on the simulated wind and waves over the East China Sea (ECS) with a focus on typhoon events. These experiments include stand-alone regional atmosphere model (CCLM) simulations, stand-alone spectral wave model (WAM) simulations driven by the regional atmospheric model CCLM or ERA5 reanalysis, and two-way (CCLM-WAM) coupled simulations. We assessed the simulated wind speed and significant wave height against in situ observations and remote sensing data and focused on typhoon events in 2010. We analyzed the differences between the experiments in capturing the surface pressure, wind speed, and roughness length. Both ERA5 reanalysis data and our regional model simulations demonstrate high quality in capturing wind and wave conditions over the ECS. The results show that downscaled simulations tend to be closer to in situ observations than ERA5 reanalysis data in capturing wind variability and probability distribution, dominant wind and wave directions, strong typhoon intensity and related extreme significant wave height. In comparison with satellite observations, the CCLM-WAM simulation outperforms the CCLM in reducing wind bias. The coupled and uncoupled simulations are very similar in terms of other wind and wave statistics. Though there is much improvement in capturing typhoon intensity to ERA5, regional downscaled simulations still underestimate the wind intensity of tropical cyclones.

Simulations of a Regional Climate Model (RCM) driven by identical lateral boundary conditions but initialized at different times exhibit the phenomenon of so-called internal model variability (or in short, Internal Variability—IV), which is defined as the inter-member spread between members in an ensemble of simulations. Our study investigates the effects of air-sea coupling on IV of the regional atmospheric model COSMO-CLM (CCLM) of the new regional coupled system model GCOAST-AHOI (Geesthacht Coupled cOAstal model SysTem: Atmosphere, Hydrology, Ocean and Sea Ice). We specifically address physical processes parameterized in CCLM, which may cause a large IV during an extreme event, and where this IV is affected by the air-sea coupling. Two six-member ensemble simulations were conducted with GCOAST-AHOI and the stand-alone CCLM (CCLM_ctr) for a period of 1 September−31 December 2013 over Europe. IV is expressed by spreads within the two sets of ensembles. Analyses focus on specific events during this period, especially on the storm Christian occurring from 27 to 29 October 2013 in northern Europe. Results show that simulations of CCLM_ctr vary largely amongst ensemble members during the storm. By analyzing two members of CCLM_ctr with opposite behaviors, we found that the large uncertainty in CCLM_ctr is caused by a combination of two factors (1) uncertainty in parameterization of cloud-radiation interaction in the atmospheric model. and (2) lack of an active two-way air-sea interaction. When CCLM is two-way coupled with the ocean model, the ensemble means of GCOAST-AHOI and CCLM_ctr are relatively similar, but the spread is reduced remarkably in GCOAST-AHOI, not only over the ocean where the coupling is done but also over land due to the land-sea interactions.

A new parameterization for calculating the nonlinear near-bed wave orbital velocity in the shallow water was presented. The equations proposed by Isobe and Horikawa (1982) were modified in order to achieve more accurate predictions of the peak orbital velocities. Based on field data from Egmond Beach in the Netherlands, the correction coefficient and maximum skewness were determined as functions of the Ursell number. The obtained equations were validated against measurements from Egmond Beach, and with laboratory data from small-scale wave flume experiments at Delft University of Technology and from large-scale wave flume experiments at Delft Hydraulics. Inter-comparisons with other previously developed parameterizations were also carried out. The model simulations by the present study were in good agreement with the measurements and have been improved compared to the previous ones. For Egmond Beach, the root-mean-square errors for the peak onshore (uc) and offshore (ut) orbital velocities were approximately 21%. The relative biases were small, approximately 0.013 for uc and −0.068 for ut. The coefficient of determination was in the range between 0.64 and 0.68. For laboratory experiments, the root-mean-square errors in a range of 7.2%−24% for uc, and 7.9%−15% for ut.

The effects of coupling between the atmospheric model of the Consortium for Small-Scale Modelling-Climate Limited-area Modelling (CCLM) and the wind wave model (WAM) on the lower atmosphere within the North Sea area are studied. Due to the two-way coupling between the models, the influences of wind waves and the atmosphere on each other can be determined. This two-way coupling between these models is enabled through the introduction of wave-induced drag into CCLM and updated winds into WAM. As a result of wave-induced drag, different atmospheric parameters are either directly or indirectly influenced by the wave conditions. The largest differences between the coupled and reference model simulation are found during storm events as well as in areas of steep gradients in the mean sea level pressure, wind speed or temperature. In the two-way coupled simulation, the position and strength of these gradients vary, compared to the reference simulation, leading to differences that spread throughout the entire planetary boundary layer and outside the coupled model area, thereby influencing the atmosphere over land and ocean, although not coupled to the wave model. Ultimately, the results of both model simulations are assessed against in situ and satellite measurements, with a better general performance of the two-way coupled simulation with respect to the observations.

Wave climate change by the end of the 21st century (2075−2100) was investigated using a regional wave climate projection under the RCP 8.5 scenario. The performance of the historical run (1980−2005) in representing the present wave climate was assessed when compared with in situ (e.g., GTS) and remote sensing (i.e., Jason-1) observations and wave hindcasts (e.g., ERA5-hindcast). Compared with significant wave height observations in different subdomains, errors on the order of 20−30% were observed. A Principal Component (PC) analysis showed that the temporal leading modes obtained from in situ data were well correlated (0.9) with those from the historical run. Despite systematic differences (10%), the general features of the present wave climate were captured by the historical run. In the future climate projection, with respect to the historical run, similar wave climate change patterns were observed when considering both the mean and severe wave conditions, which were generally larger during summer. The range of variation in the projected extremes (±10%) was consistent with those observed in previous studies both at the global and regional spatial scales. The most interesting feature was the projected increase in extreme wind speed, surface Stokes drift speed and significant wave height in the Northeast Atlantic. On the other hand, a decrease was observed in the North Sea and the southern part of the Baltic Sea basin, while increased extreme values occurred in the Gulf of Bothnia during winter.

A Coupled Model Intercomparison Project Phase 5 (CMIP5)-derived single-forcing, single-model, and single-scenario dynamic wind-wave climate ensemble is presented, and its historic period (1979–2005) performance in representing the present wave climate is evaluated. A single global climate model (GCM)-forcing wave climate ensemble was produced with the goal of reducing the inter GCM variability inherent in using a multi-forcing approach for the same wave model. Seven CMIP5 EC-Earth ensemble runs were used to force seven WAM wave model realizations, while future wave climate simulations, not analyzed here, were produced using a high-emission representative concentration pathway 8.5 (RCP8.5) set-up. The wave climate ensemble’s historic period was extensively compared against a set of 72 in situ wave-height observations, as well as to ERA-Interim reanalysis and Climate Forecast System Reanalysis (CFSR) hindcast. The agreement between the wave climate ensemble and the in situ measurements and reanalysis of mean and extreme wave heights, mean wave periods, and mean wave directions was good, in line with previous studies or even better in some areas of the global ocean, namely in the extratropical latitudes. These results give a good degree of confidence in the ability of the ensemble to simulate a realistic climate change signal.

This study describes the coupling between physical and biogeochemical models and analyses the response of the ecosystem in the north-western Black Sea to nutrient loads and climate changes. The basic physical and biological dynamics of the upper north-western Black Sea is illustrated as well. The physical model is based on the Princeton Ocean Model (POM); additionally, a parameterisation of mixed layer is included. The biogeochemical model is based on the European Regional Sea Ecosystem Model (ERSEM) and consists of five modules: (1) primary producers, (2) microbial loop, (3) mesozooplankton, (4) benthic nutrients, and (5) benthic biology. The ecosystem in ERSEM is subdivided into three functional types, producers (phytoplankton), decomposers (pelagic and benthic bacteria) and consumers (zooplankton and zoobenthos). Model-data comparisons have been performed for both calibrating and verifying coupled model simulations. We address here the impact of nutrient discharge from the Danube River on the functioning of the biological system. The evolution of the mixed layer, as well as the response of the biological system to variability of the nutrient discharge from the Danube River is described in detail. Several scenarios have been developed to study the impact which nutrient reduction has on the coastal marine system. The model predictions indicate that the biological system is very sensitive to the changes in nutrient concentrations, as well as to their ratios.