Sources, pathways, and abatement strategies of macroplastic pollution: an interdisciplinary approach for the southern North Sea

The issue of marine plastic pollution has been extensively studied by various scientific disciplines in recent decades due to its global threat. However, owing to its complexity, it requires an interdisciplinary approach to develop effective management strategies. The multidisciplinary scientific approach presented here focuses on understanding the sources and pathways of macroplastic litter and developing abatement strategies in the southern North Sea region. Over 2.5 years, more than 63,400 biodegradable wooden drifters were deployed with the help of citizen science to study the sources, pathways, and accumulation areas of floating marine litter. Rivers act as sinks of most of the floating marine litter released within their waterways. Short-term field experiments were also conducted to analyse the hydrodynamic and atmospheric processes that govern the transport of floating litter particles at the sea surface. Numerical models were used to examine the transport of virtual litter particles in the entire North Sea and in coastal regions. It was found that there are no permanent accumulation areas in the North Sea, and the Skagerrak and fronts can increase the residence times of floating marine litter and favour sinking. Field surveys revealed that the majority of litter objects originate from fisheries and consumer waste. To develop effective abatement strategies, the key stakeholder landscape was analysed on a regional level. The interdisciplinary approach developed in this study highlights the importance of synergizing scientific resources from multiple disciplines for a better understanding of marine plastic pollution and the development of effective management strategies

Model-observations synergy in the coastal ocean

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

Interannual Change in Mode Waters: Case of the Black Sea

More than 6,000 profiles from profiling floats in the Black Sea over the 2005–2020 period were used to study the ventilation of this basin and the mixing pathways along isopycnals. The layer of the minimum potential vorticity (PV), the Black Sea pycnostad, approximately follows the core of the cold intermediate layer, similar to the case of oceanic mode waters. However, unlike in the ocean, the horizontal patterns of PV are shaped by cyclonic gyre circulation. There is a principle difference in the probability distribution of the thermohaline properties presented in geopotential coordinates from those presented in density coordinates. In the latter case, several mixing pathways, which are not known from previous studies, dominate the ocean states. These formed after three intermittent events of cold water formation. The density ratio decreased three times during the last 15 years, revealing the decreasing role of temperature in the vertical layering of the Black Sea halocline. The basin‐wide distribution of PV above σθ = 16, which is where the maximum vertical density gradient appears, is opposite to the distribution below this depth. This finding suggests a complex change in the mesoscale dynamics in different layers. Comparisons of observations with data from the Copernicus Black Sea operational model demonstrate that the mixing parameterizations of models need further improvements

Reconstruction of the Basin‐Wide Sea‐Level Variability in the North Sea Using Coastal Data and Generative Adversarial Networks

We present an application of generative adversarial networks (GANs) to reconstruct the sea level of the North Sea using a limited amount of data from tidal gauges (TGs). The application of this technique, which learns how to generate datasets with the same statistics as the training set, is explained in detail to ensure that interested scientists can implement it in similar or different oceanographic cases. Training is performed for all of 2016, and the model is validated on data from 3 months in 2017 and compared against reconstructions using the Kalman filter approach. Tests with datasets generated by an operational model (“true data”) demonstrated that using data from only 19 locations where TGs permanently operate is sufficient to generate an adequate reconstruction of the sea surface height (SSH) in the entire North Sea. The machine learning approach appeared successful when learning from different sources, which enabled us to feed the network with real observations from TGs and produce high‐quality reconstructions of the basin‐wide SSH. Individual reconstruction experiments using different combinations of training and target data during the training and validation process demonstrated similarities with data assimilation when errors in the data and model were not handled appropriately. The proposed method demonstrated good skill when analyzing both the full signal and the low‐frequency variability only. It was demonstrated that GANs are also skillful at learning and replicating processes with multiple time scales. The different skills in different areas of the North Sea are explained by the different signal‐to‐noise ratios associated with differences in regional dynamics.Plain Language Summary: The variability of sea level is one of the most important elements of the ocean dynamics. Basin‐wide observations are due to satellite altimeters, observations in coastal stations are provided by tidal gauges. The first are not very accurate in the coastal areas, the second do not provide basin‐wide coverage. The task in the present work is to use machine learning to reconstruct the sea‐level variability in the North Sea, which is an almost enclosed ocean region, using observations only. Using data from 19 coastal stations and data from numerical models as a representation of the true ocean (synthetic observations), we demonstrated that the generative adversarial networks reconstruct almost perfectly the sea level of the North Sea. The application of this technique, which learns how to generate datasets with the same statistics as the training set, is explained in detail to ensure that interested scientists can implement it in similar or different oceanographic cases.Key Points: Generative Adversarial Networks successfully reconstruct basin‐wide sea level in the North Sea using data from tidal gauges. Machine learning appeared successful when learning from different data sources. The proposed method is skillful at learning and replicating processes with multiple time scales

Ensemble perturbation smoother for optimizing tidal boundary conditions by assimilation of High-Frequency radar surface currents - application to the German Bight

High-Frequency (HF) radars measure the ocean surface currents at various spatial and temporal scales. These include tidal currents, wind-driven circulation, density-driven circulation and Stokes drift. Sequential assimilation methods updating the model state have been proven successful to correct the density-driven currents by assimilation of observations such as sea surface height, sea surface temperature and in-situ profiles. However, the situation is different for tides in coastal models since these are not generated within the domain, but are rather propagated inside the domain through the boundary conditions. For improving the modeled tidal variability it is therefore not sufficient to update the model state via data assimilation without updating the boundary conditions. The optimization of boundary conditions to match observations inside the domain is traditionally achieved through variational assimilation methods. In this work we present an ensemble smoother to improve the tidal boundary values so that the model represents more closely the observed currents. To create an ensemble of dynamically realistic boundary conditions, a cost function is formulated which is directly related to the probability of each boundary condition perturbation. This cost function ensures that the boundary condition perturbations are spatially smooth and that the structure of the perturbations satisfies approximately the harmonic linearized shallow water equations. Based on those perturbations an ensemble simulation is carried out using the full three-dimensional General Estuarine Ocean Model (GETM). Optimized boundary values are obtained by assimilating all observations using the covariances of the ensemble simulation.ECOO

Turbulent mixing due to surface waves indicated by remote sensing of suspended particulate matter and its implementation into coupled modeling of waves, turbulence and circulation

This paper studies the impact of the surface waves on the turbulent mixing. The satellite observations of Suspended Particulate Matter (SPM) at ocean surface as an indicator of turbulent quantities of the flow are used. In a water column, SPM builds a vertical profile depending on settling velocities of the particles and on vertical mixing processes, thus SPM is a perfect marker to study the turbulent quantities of the flow. Satellite observations in the North Sea show that surface SPM concentrations, in locations of its deposition, grow rapidly and build plume-shaped, long (many km) uninterrupted and consistent structures during a storm. Also, satellites reveal that SPM rapidly sinks to the seabed after the storm peak has passed and wave height decreases, i.e. with absence of strong turbulence. The non-breaking wave-induced turbulence has been discussed, parameterized and implemented into an equation of evolution of turbulent kinetic energy (TKE) in the frame of mean-flow concept, which can be used in existing circulation models. The ratio between dissipated and total wave energy is used to describe the influence of wave dumping on the mean flow. Our numerical tests reproduce experiments in a wave tank very well and are supported by observations of SPM in the North Sea. Our results show that the motion of an individual non-breaking wave includes turbulent fluctuations if the critical Reynolds number for wave motion is exceeded, independent from presence of currents due to wind or tides. These fluctuations can produce high diffusivity and strongly influences mixing in the upper water layer of the ocean

Dynamics of the Baltic Sea straits via numerical simulation of exchange flows

The Semi-implicit Cross-scale Hydroscience Integrated System Model (SCHISM), which uses unstructured grids, is set up for the North and Baltic Seas. With a resolution of ∼100 m in the narrow straits connecting the two basins, this model accurately resolves the inter-basin exchange. Validation against observations in the straits shows the model has good skill in simulating the transport and vertical profiles of temperature, salinity and currents. The timing and magnitude of the major inflow event in 2014–2015 is also realistically simulated. The analysis is focused on the two-layer exchange, its dependence on the atmospheric forcing, and dominant physical balances. The two-layer flows in the three connecting straits show different dependencies upon the net transport. The spatial variability of this dependence is also quite pronounced. The three-strait system developed specific dynamics, with time lags and differences between currents in the individual straits during inflow and outflow conditions. Analysis on the impact of resolution indicates that the performance of the model changes depending on whether the narrow parts of the straits are resolved with a resolution of 500 m or 100 m. With this ultra-fine resolution, gravity flows and variability of salinity in deep layers is generally more adequately simulated. This paper identifies the needs for more profound analysis of the coupled dynamics of Baltic and North Seas with a focus on the Danish straits

Relative Dispersion of Surface Drifters in the North Sea: The Effect of Tides on Mesoscale Diffusivity

We examine the relative dispersion and the contribution of tides on the relative diffusivities of surface drifters in the North Sea. The drifters are released in two clusters, yielding 43 pairs, in the vicinity of a tidal mixing front in the German Bight, which is located in the southeastern area of the North Sea. Both clusters indicate decreasing dispersion when crossing the tidal mixing front, followed by exponentially increasing dispersion with e-folding times of 0.5 days for Cluster 1 and 0.3 days for Cluster 2. A transition of the dispersion regimes is observed at scales of the order of the Rossby radius of deformation (10 km). After that, the relative dispersion grows with a power-law dependency with a short period of ballistic dispersion (quadratic growth), followed by a Richardson regime (cubic growth) in the final phase. Scale-dependent metrics such as the relative diffusivities are consistent with these findings, while the analysis of the finite-scale Lyapunov exponents (FSLEs) shows contradictory results for the submesoscales. In summary, the analysis of various statistical Lagrangian metrics suggests that tracer stirring at the submesoscales is nonlocal and becomes local at separation scales larger than 10 km. The analysis of meridional and zonal dispersion components indicates anisotropic dispersion at the submesoscales, which changes into isotropic dispersion on the mesoscales. Spectral analysis of the relative diffusivity gives evidence that semidiurnal and shallow-water tides influence relative diffusivity at the mesoscales, especially for drifter separations above 50 km