The Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report highlights the accelerating rise of global mean sea level (GMSL), with trends surpassing historical rates observed over the past two millennia. The China-Europe Sea Route (CESR), a region of strategic importance for international trade, is particularly vulnerable to sea level changes and extreme events. This study integrates data from satellite altimetry, tide gauge records, and a global hydrodynamic model to assess absolute and relative sea level variations, as well as extreme sea level events, across eight CESR sub-regions over the period 1993-2023.Statistically significant mean sea level trends confirm systematic decadal variability across regions. Notably, the East China Sea, Yellow Sea and Bohai Sea show a decadal trend slowdown in the second (2003-2013) and third decade (2013-2023) with respect to the first one (1993-2003).Signals of enhanced regional mean SLA trends are observed in the North Indian Ocean, while Pacific sub-regions exhibit pronounced decadal variability. Discrepancies between tide gauge and satellite altimetry in specific areas were attributed to land subsidence and inherent limitations of coastal altimetry.A global hydrodynamic model provided estimates of return periods for extreme sea levels, identifying high-risk zones such as the Bay of Bengal and the South China Sea. However, challenges remain in capturing cyclone impacts, emphasizing the need for continued improvements in modeling frameworks for extreme sea level assessment.By highlighting the importance of localized, data-driven approaches and continuous monitoring, the findings contribute to advancing climate resilience and informing risk mitigation strategies in this globally significant region.

Eutrophication status assessments of the Baltic Sea rely on regionally agreed monitoring and assessment methodologies based on indicators with thresholds of achieving or not achieving a good environmental status. Model outputs can be used to increase the data availability and assessment confidence. We evaluated the applicability of Copernicus Marine Service (CMEMS) reanalysis products for four eutrophication indicators - dissolved inorganic nitrogen (DIN) and phosphorus (DIP), chlorophyll-a and oxygen debt. The most significant discrepancies between the model-based and monitoring-based indicator results were found for DIN. Compared to observations, significantly lower winter DIN concentrations were also reflected in modelled low summer chlorophyll-a levels. A general agreement between the modelled and observed DIP values was not the case in the northern and eastern basins with large freshwater discharges and either very low or high DIP concentrations. A poor agreement between the model and observations in these basins could be related to low data availability for the assessment and assimilation into the model. Significantly lower oxygen debt values in the deep basins derived using the reanalysis product than the observations point to model deficiencies in reproducing mixing and biogeochemical processes. More observations and biogeochemical data assimilation, which was skipped in the latest CMEMS reanalysis product, are obvious ways to improve the model outputs. However, biogeochemical models must be further developed to better match model outputs and observations before introducing more sophisticated eutrophication indicators.

The development and tuning of oceanographic models for coastal regions can be a time-consuming process. However, there are many situations in which an easily producible, user-friendly and still reliable tool is desirable for unresolved coastal regions, or planning modifications of coastal infrastructure, wind farms, assist in search and rescue operations, etc. This paper develops a prototype of an on-demand, relocatable modelling tool enabling to create the coastal setup easily by simply attaching higher resolution domain(s) to the base setup of open seas. The prototype runs on internal system at Danish Meteorological Institute (DMI), that is designed for further public use in a later stage in EU Digital Twin Ocean. To accomplish this, we apply the oceanographic circulation model HIROMB BOOS Model (HBM) which implements a two-way nesting technique to ensure a seamless transition from open seas to coastal waters. This tool is based on publicly available resources: bathymetry, oceanographic software, weather forcing, boundary forcing, etc., so that, it can be accessible by public community. The base bathymetry of the model at resolution of 2 arc seconds is derived from EMODnet bathymetry with coastal correction by using OpenStreetMap coastline. Lower resolution bathymetries in discrete resolutions are derived from the base bathymetry and processed beforehand, ensuring that users can apply them directly. To ensure close connections (strait, fjord, large river, channel, etc.) between water bodies, a vector layer of waterways is used for each low-resolution bathymetry. In the same way, narrow land forms (dam, narrow-long island or peninsula, road, etc.) are ensured by vector layer of dams. The on-demand tool is specifically designed for the North Sea-Baltic Sea region and is based on a tuned setup for open seas with properly-resolved Danish straits. As the on-demand tool will not use data assimilation, salinity inflow in the Baltic Sea is enhanced by slight smoothing of the bathymetry from Danish straits to Baltic proper. When comparing the results of base setup with existing reanalysis products in the North Sea - Baltic Sea, sea level of the HBM base setup shows favourable results. On-demand high resolution downscaling simulations have been tested for some major storm surge cases, showing benefits of using high resolution in storm surge modelling. The stability and quality of the resulting two-way nested coastal setups can be enhanced by implementing a cascade of two-way nestings. In summary, the paper demonstrates that creation of on-demand coastal oceanographic applications by attaching highly resolved coastal domains to existing base setups for open seas is achievable task.

The EDITO-Model Lab project is aiming to develop the next generation of ocean and coastal models, combining artificial intelligence and high-performance computing, to be integrated into the EDITO public infrastructure, providing access to Focus applications. The improved core model suite together with automated model builders and downscaling tools, as well as high-resolution data sources from both numerical simulations and machine learning approaches will be published in an interactive manner on the EDITO platform. In this work we demonstrate the capabilities of the European Digital Twin Ocean in so called Focus Applications, designed for intermediate users that are interested in ocean and coastal management. The Focus Applications cover three areas in line with the EU Mission "Restore our Ocean and Waters". Biodiversity: Optimizing Marine Protected Areas by simulating biodiversity indicators and habitat suitability; Zero Carbon: Reducing carbon emissions of the marine transportation industry by including waves and currents in optimizing ship routing; and Zero Pollution: Reducing marine pollution by simulating the transport of oil spills and marine plastics, assessing hazards and backtracking to the source. By developing these Focus Applications and deploying them in the EDITO public infrastructure, the EDITO Model Lab consortium hopes to showcase the value of the next generation of ocean models (DTO engine), moreover contribute to a fruitful discussion with intermediate users around observing, simulating, forecasting and projecting coastal and ocean processes. This work includes interactive demonstrations.

The Pan-Eurasian Experiment Modelling Platform (PEEX-MP) is one of the key blocks of the PEEX Research Programme. The PEEX MP has more than 30 models and is directed towards seamless environmental prediction. The main focus area is the Arctic-boreal regions and China. The models used in PEEX-MP cover several main components of the Earth's system, such as the atmosphere, hydrosphere, pedosphere and biosphere, and resolve the physical-chemical-biological processes at different spatial and temporal scales and resolutions. This paper introduces and discusses PEEX MP multi-scale modelling concept for the Earth system, online integrated, forward/inverse, and socioeconomical modelling, and other approaches with a particular focus on applications in the PEEX geographical domain. The employed high-performance computing facilities, capabilities, and PEEX dataflow for modelling results are described. Several virtual research platforms (PEEX-View, Virtual Research Environment, Web-based Atlas) for handling PEEX modelling and observational results are introduced. The overall approach allows us to understand better physical-chemical-biological processes, Earth's system interactions and feedbacks and to provide valuable information for assessment studies on evaluating risks, impact, consequences, etc. for population, environment and climate in the PEEX domain. This work was also one of the last projects of Prof. Sergej Zilitinkevich, who passed away on 15 February 2021. Since the finalization took time, the paper was actually submitted in 2023 and we could not argue that the final paper text was agreed with him.

The slow water renewal endows the Baltic Sea a strong retention of pollutants/nutrients. Constraining water age is a practical way to depict the transport pathways/timescales for water masses and accompanying soluble substances. Although the water ages in the Baltic Sea have been resolved by 3D ocean models 20 years ago, the simulated results have not been verified. In this work, we exploited two anthropogenic radionuclides (129I and 236U) as an age marker to constrain the ages of inflowing North Sea saline waters into the Baltic Sea. Our results indicate that the Baltic Sea has a highly stratified structure with distinctly different timescales for surface-water and deep-water circulations (3 ± 2 and 20 ± 3 years, respectively), providing the first observation-based proof for the multi-decadal retention of (radioactive) pollutants within the Baltic Sea. This work demonstrates the power of anthropogenic radiotracers in investigating hydrodynamic processes in the Northwestern European coastal areas.

Abstract. A Baltic dataset covering 1990–2020 is reconstructed using a circulation model and data assimilation. Satellite observations of sea surface temperature and temperature and salinity (T/S) profiles are used to reduce model biases by a local Singular Evolutive Interpolated Kalman (SEIK) filter. The dataset is evaluated with assimilated T/S profiles and reprocessed grid observations, and the results demonstrate that the sea surface temperature, sea surface height, mixed layer depth, and vertical distribution of T/S are all reasonably reproduced. T/S trends at various depths in the Baltic sub-basins are analyzed from a reanalysis perspective, revealing a clear warming trend in recent decades, with a slight desalination trend in the northern Baltic Sea and a salination trend in the southern Baltic Sea. In particular, T/S trends of the Baltic Sea are larger in the south than in the north. In the Baltic Sea over the past 30 years, the temperature rises at a rate of 0.036 to 0.041 °C/year, with a larger warming trend below the thermocline than above it, while the salinity increases with a trend of -0.0036 to 0.049 PSU/year. In addition, seasonal variations are evident in the temperature at the surface, 60 m, and bottom, as well as in the surface salinity, whereas no clear seasonal variations are detected in the salinity below the surface and temperature at 100 m.

The rapid expansion of offshore wind farms (OWFs) in European seas is accompanied by many challenges, including efficient and safe operation and maintenance, environmental protection, and biodiversity conservation. Effective decision-making for industry and environmental agencies relies on timely, multi-disciplinary marine data to assess the current state and predict the future state of the marine system. Due to high connectivity in space (land–estuarial–coastal sea), socioeconomic (multi-sectoral and cross-board), and environmental and ecological processes in sea areas containing OWFs, marine observations should be fit for purpose in relation to multiple OWF applications. This study represents an effort to map the major observation requirements (Part-I), identify observation gaps, and recommend solutions to fill those gaps (Part-II) in order to address multi-dimension challenges for the OWF industry. In Part-I, six targeted areas are selected, including OWF operation and maintenance, protection of submarine cables, wake and lee effects, transport and security, contamination, and ecological impact assessments. For each application area, key information products are identified, and integrated modeling–monitoring solutions for generating the information products are proposed based on current state-of-the-art methods. The observation requirements for these solutions, in terms of variables and spatial and temporal sampling needs, are therefore identified.

Ocean reanalyses provide a valuable source of data for understanding the dynamics of the ocean, climate studies and practical applications. We introduce a new CMEMS high-resolution ocean reanalysis for the Baltic Sea for the period from 1993 to 2021. The reanalysis is an upgrade of the existing CMEMS products BALTICSEA_REANALYSIS_PHY_003_011 and BALTICSEA_REANALYSIS_BIO_003_012 and introduces numerous changes including higher horizontal resolution, approximately 1.9 km, a new versions of ocean, ice and biogeochemical models, and a new data assimilation scheme.We have analyzed the reanalysis data to assess the performance of the new reanalyses focusing on the ocean dynamics. We found that the high resolution of the reanalysis allowed us to detect finer-scale features in the data, such as mesoscale eddies, that were not apparent in lower resolution dataset as well as improve the ocean currents.We also used the reanalysis to study the occurrence and evolution of salt water inflows from the North Sea. Our results suggest that the high resolution of the reanalysis enables more accurate predictions of these events.Overall, our study demonstrates the utility of the new high-resolution ocean reanalysis for understanding the dynamics of the Baltic Sea and improving our ability produce a physically consistent combination of model and observations.

We simulated the spatial distribution and dynamics of macro plastic in the Baltic Sea, using a new Lagrangian approach called the dynamical renormalization resampling scheme (DRRS). This approach extends the super-individual simulation technique, so the weight-per-individual is dynamic rather than fixed. The simulations were based on a mapping of the macro plastic sources along the Baltic coast line, and a five year time series of realistic wind, wave and current data to resolve time-variability in the transport and spatial distribution of macro plastics in the Baltic Sea. The model setup has been validated against beach litter observations and was able to reproduce some major spatial trends in macroplastic distributions. We also simulated plastic dispersal using Green's functions (pollution plumes) for individual sources. e.g. rivers, and found a significant variation in the spatial range of Green's functions corresponding to different pollution sources. We determined a significant temporal variability (up to 7 times the average) in the plastic concentration locally, which needs to be taken into account when assessing the ecological impact of marine litter. Accumulation patterns and litter wave formation were observed to be driven by an interplay between positive buoyancy, coastal boundaries and varying directions of physical forcing. Finally we determined the range of wind drag coefficients for floating plastic, where the dynamics is mostly directly wind driven, as opposed to indirectly by surface currents and waves. This study suggests that patterns of litter sorting by transport processes should be observable in many coastal and off-shore environments.

Maritime information services supporting European agencies such as the FRONTEX require European-wide forecast solutions. Following a consistent approach, regional and global forecasts of the sea surface conditions from Copernicus Marine Service and national met-ocean services are aggregated in space and time to provide a European-wide forecast service on a common grid for the assistance of Search and Rescue operations. The best regional oceanographic model solutions are selected in regional seas with seamless transition to the global products covering the Atlantic Ocean. The regional forecast models cover the Black Sea, Mediterranean Sea, Baltic Sea, North Sea and combine the North Sea - Baltic Sea at the Danish straits. Two global models have been added to cover the entire model domain, including the regional models. The aggregated product is required to have an update frequency of 4 times a day and a forecasting range of 7 days, which most of the regional models do not provide. Therefore, smooth transition in time, from the shorter time range, regional forecast models to the global model with longer forecast range are applied. The set of parameter required for Search and Rescue operations include sea surface temperature and currents, waves and winds. The current version of the aggregation method was developed for surface temperature and surface currents but it will be extended to waves in latter stages. The method relies on the calculation of aggregation weights for individual models. For sea surface temperature (SST), near real-time satellite data at clear-sky locations for the past days is used to determine the aggregation weights of individual forecast models. A more complicated method is to use a weighted multi-model ensemble (MME) approach based on best forecast features of individual models and possibly including near real time observations. The developed method explores how satellite observations can be used to assess spatially varying, near real time weights of different forecasts. The results showed that, although a MME based on multiple forecasts only may improve the forecast, if the forecasts are unbiased, it is essential to use observations in the MME approach so that proper weights from different models can be calculated and forecast bias can be corrected. It is also noted that, in some months, e.g., June in Baltic Sea, even SST was assimilated, the forecast still show quite high error. There are also visible difference between different Copernicus Marine Environment Monitoring Service (CMEMS) satellite products, e.g. OSTIA and regional SST products, which can lead different forecast quality if different SST observation products are assimilated.

This report summarises demonstrated benefit from integrating BOOS and HELCOM observations with CMEMS observations, including i) improved observation data accessibility by BOOS, CMEMS INSTAC and EMODnet, ii) improved quality of frequently updated CMEMS reanalysis, and iii) improved quality and update frequency of eutrophication assessment in the Baltic Sea based on the reanalysis. Also, feasibility for extending this approach to other regional seas, other indicators, and fishery advice applications is analysed and recommendations from the workshop on “Full value chain integration for monitoring and assessment” are provided. (EuroSea Deliverable, D6.6)

Having steadily increased with global production in the past 50 years, the presence and accumulation of plastic debris is now recognized as a major environmental problem, with consequences directly affecting not only marine ecosystems, but also society and human well-being. After human activities release plastic litter, it is either directly discharged into the ocean or it is transported to the sea via inland pathways (e.g., rivers, lakes, wastewater treatment plants). Once in the ocean, plastics are further transported and transformed by processes such as ocean currents, winds and waves, water dispersion, fragmentation, biofouling, sinking, sedimentation, and beaching (Figure 1).

Offshore wind energy installations in coastal areas have grown massively over the last decade. This development comes with a large number of technological, environmental, economic, and scientific challenges, which need to be addressed to make the use of offshore wind energy sustainable. One important component in these optimization activities is suitable information from observations and numerical models. The purpose of this study is to analyze the gaps that exist in the present monitoring systems and their respective integration with models. This paper is the second part of two manuscripts and uses results from the first part about the requirements for different application fields. The present solutions to provide measurements for the required information products are described for several European countries with growing offshore wind operations. The gaps are then identified and discussed in different contexts, like technology evolution, trans-European monitoring and modeling initiatives, legal aspects, and cooperation between industry and science. The monitoring gaps are further quantified in terms of missing observed quantities, spatial coverage, accuracy, and continuity. Strategies to fill the gaps are discussed, and respective recommendations are provided. The study shows that there are significant information deficiencies that need to be addressed to ensure the economical and environmentally friendly growth of the offshore wind farm sector. It was also found that many of these gaps are related to insufficient information about connectivities, e.g., concerning the interactions of wind farms from different countries or the coupling between physical and biological processes.

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.

EDITORIAL article Front. Mar. Sci., 28 June 2023Sec. Marine Pollution Volume 10 - 2023 | https://doi.org/10.3389/fmars.2023.1232888

The assessment of microplastic pollution in the marine environment is a requirement for the evaluation of the present situation and development of efficient combatting strategies. In combination with model based transport assessments, the monitoring of microplastics provides a tool for the assessment of the overall budget for the entire Baltic Sea and sub-basins. Furthermore, monitoring data sets can be used to evaluate the model performance in capturing spatial and seasonal pattern of marine pollution. Currently, the scope of microplastic monitoring is quite limited, which is why it is an important issue to control the quality of the available datasets and to derive useful indicators from the available data. Our study of single source data sets, with improved error statistics compared to multi source data sets, shows that the mean sampling error is still relatively high, about 40%–56%, which has been estimated using replicate samples. The lack of surface flow correction when using mantra net or trawl methods introduces and additional 12% uncertainty. When compared to model data, additional uncertainties come into play, related to the model characterization of microplastics as a set of spherical particles with a given density and diameter, which differs fundamentally from the broad range of values occurring in nature. It is therefore important to derive useful indicators from the measured and monitored data sets before attempting to validate the model. In our presentation, we will detail the assessment of sampling errors and provide an overview over the extent of microplastic monitoring assessed in the CLAIM project for the Baltic Sea. The collected data set was used to evaluate the quality of DMI’s microplastic transport model in reproducing spatial and seasonal patterns. The database of the model-observation assessment covers the 6 years period 2014-2019, with regular monitoring data sets in the eastern Baltic Sea being available since 2016. Finally, we discuss recommendations that could help to reduce sampling errors and derive indicators that are useful for a quality assessment of microplastic models. Aim is the development of operational modelling and monitoring capabilities for marine microplastic pollution.

Although previous research indicated that the Baltic Sea has a strong "memory effect" for trapping pollutants/nutrients, the associated environmental risks are not well understood due to the knowledge gaps in the long-term hydrodynamics-driven exchange of pollutants/nutrients between the North Sea and the Baltic Sea. In this work, we exploited 99Tc and 129I released from the two European nuclear reprocessing plants as oceanic tracers and pollutant proxies, and performed a five-decade hindcast simulation to quantitatively estimate the fluxes and timescales of marine transport of pollutants/nutrients in the North-Baltic Sea. Modeling results underline two potential environmental risks of the Baltic Sea's "memory effect": (1) ∼26 years of environmental half-life for any existing water-soluble pollutants/nutrients in the Baltic Sea driven by its hydrodynamics; (2) the Baltic Sea as a pollutant reservoir continuously exporting 3 % of contaminations per year to the downstream areas after any pollution event. Our findings provide fundamental knowledge for understanding the long-term hydrodynamics-driven pollutant/nutrient transport in the North-Baltic Sea, facilitating the future regional management of the marine environment.

This paper aims to quantify data uncertainties in marine microplastic measurements, including spatiotemporal sampling error and sample volume estimation error, identify impacts of varying mesh sizes, sampling and analysis methods, and evaluate consistency in multiple microplastic observation datasets. Twenty-seven datasets on surface marine microplastics with particle size >100 µm in the Baltic Sea are compiled. Results show that the trawl datasets have a spatiotemporal sampling error of 25% for microlitter concentration, 36% for microplastic fiber concentrations and 40-56% for microplastic particle concentration. By taking surface currents and wave-induced Stokes drift into account, the sample volume of the trawl measurements is corrected, leading to a mean microplastic concentration correction of 12%. The differences of microplastic concentration between datasets with varying mesh sizes from 100 – 500 µm are not statistically significant. Analysis methods, however, can lead to significant differences in microplastic datasets. The dataset consistency is further examined among the three dataset categories using trawl, pump and bulk sampling techniques. It is found that an individual dataset is often self-consistent. Most of the datasets within one monitoring category are more consistent than those from different categories. More than 70% of the datasets within individual categories are consistent, which have mean microplastic concentration significantly smaller than the rest of the datasets. Significant inconsistencies are identified between different data categories. Six out of eight highest relative standard deviations are found in the pump and bulk datasets. The median value of the mean microplastic concentration from the 10 pump datasets is about 4.5 times as much as that of the 14 trawl datasets, both for fiber and non-fiber particles. Significant differences are also identified on microplastic fiber fraction in different dataset categories. Two thirds of the 13 bulk and pump datasets have a microplastic fiber fraction >85% while the 14 trawl datasets show much lower microplastic fiber fractions between 45-70%. In addition, the particle collection efficiency, potential leakage of particles with irregular shapes, clogging, the false zero samples and related lower limit of the detectable microplastic concentration for given sampling methods and water environment, are also discussed.

This task set out to increase communication between the ocean monitoring and modelling communities in the Baltic Sea area. Through these improved communications, the goal was to advance and improve the HELCOM marine environmental assessments. To gain confidence in the numerical model outputs, an effort was undertaken to ensure ocean observing in-situ data, collected by multiple nations in the Baltic Sea, was assimilated into a numerical model. Here, we report on the development of indicators, as requested by our stakeholders, and we discuss if the Baltic Sea numerical modelling efforts are ready to augment regional environmental status reports, and can our results help guide environmental management in the region.