The EU Copernicus Marine Service, implemented by Mercator Ocean International with a large network of observation and modelling production centers, is a world-leading, reference digital information service on the world ocean and EU regional seas. The Copernicus Marine Service monitors in real time and over the past decades the world ocean across the entire water column using in situ and satellite observations and monitoring and forecasting systems. It provides free and fully open, regular and systematic reference information on the physical, biogeochemical ocean and sea-ice state for the global ocean and the European regional seas. The Copernicus Marine Service supports applications dealing with maritime safety, sustainable use of marine resources, healthy waters, informing coastal and marine hazard services, ocean climate services, protecting marine biodiversity.
For the last 10 years, the Copernicus Marine has been implementing unique capabilities to inform and support action for the Ocean. Through a regular dialogue with the user community and taking into account observation, science and technology advances, the service is continuously evolving to better answer user and societal needs. The first phase of Copernicus Marine 2 (July 2021 – December 2024) has ensured the continuity of service with respect to Copernicus Marine 1 (April 2014-July 2021) and implemented a series of evolutions for the Thematic Assembly Centers (TACs) and Monitoring and Forecasting Centers (MFCs). User uptake has steadily increased with almost 80,000 registered users in 2025. International cooperation and impact have been strengthened in the framework of the UN Decade of Ocean Science. In the second and last phase of Copernicus Marine 2 (January 2025 – June 2028), the objective is to build on these achievements to continue evolving Copernicus Marine product and service offer and maintain a world leading and state-of-the art marine service responsive to user and policy needs. Continuous evolutions of observation (TACs) and modelling (MFC) products will allow the integration of new satellite missions and in-situ observations, the improvement of processing techniques, the improvement of models, coupling and data assimilation, and an increasing use of Artificial Technique (AI) techniques. Synergies with the development of the EU Digital Twin Ocean will be strengthened.
An overview of recent achievements of Copernicus Marine will be given and the main objectives and scientific challenges of the new phase of Copernicus Marine 2 will be outlined. Long-term perspectives (post 2028) will also be discussed.
How to cite: Le Traon, P.-Y.: Copernicus Marine 2 (2021-2028): achievements and future plans , EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-5158, https://doi.org/10.5194/egusphere-egu25-5158, 2025.
The Sea-Level Thematic Assembly Centers (SL-TAC), a component of the Copernicus Marine Services, provides near-real-time and delayed-time gridded sea level and surface current products at global and regional scales. These datasets, processed using the Data Unification and Altimeter Combination System (DUACS), are important for the ocean science community, enabling the study and monitoring of oceanic system evolution.
Recently, DUACS has reprocessed 30 years of altimeter data, releasing the DT2024 products through the Copernicus Marine Service (CMEMS) and Copernicus Climate Change Service (C3S). These new products integrate updated geophysical correction standards, advanced mapping methods, and refined processing techniques, delivering significant accuracy improvements compared to the previous DT2021 release.
This study provides a comprehensive overview of the CMEMS and C3S DT2024 products and assesses their quality against independent datasets. The analysis demonstrates that updated altimetry standards enhance accuracy, especially in coastal regions, reducing errors by approximately 10% due to improved ocean tide model corrections. Furthermore, the application of the Multi-Scale Inversion of Ocean Surface Topography mapping method has reduced mapping errors by 5%–7% in areas of high ocean variability. These enhancements position the DT2024 products as valuable resources for advancing our understanding of ocean dynamics and improving the accuracy of climate and oceanographic research.
How to cite: Ballarotta, M., Dagneaux, Q., Delepoulle, A., Dibarboure, G., Dupuy, S., Faugère, Y., Jenn-Alet, M., Kocha, C., Pujol, I., and Taburet, G.: DUACS DT-2024: 30 years of reprocessed sea level altimetry products , EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-3715, https://doi.org/10.5194/egusphere-egu25-3715, 2025.
Mesoscale activity plays a central role in ocean variability, substantially influencing the mixing of biogeophysical tracers, such as heat and carbon, and driving changes in ecosystems. Eddy Kinetic Energy (EKE), a metric used for studying the intensity of mesoscale processes, has recently been shown to increase in regions of intense EKE worldwide. Strong EKE positive trends are, for example, observed in the principal western boundary current regions, such as the Gulf Stream, Kuroshio Extension, and the Brazil/Malvinas Confluence. In this study, we assess whether the Mediterranean Sea, known to be a hotspot for climate change impacts, also exhibits such intensification. Despite the high number of observational data (in-situ, satellite) and modeling experiments, there is a gap in understanding the long-term evolution of mesoscale dynamics and EKE trends in the Mediterranean Sea. This study investigates EKE trends in the Mediterranean Sea using altimetric data from the Copernicus Marine Service. Gridded altimetric products (L4) provide daily geostrophic velocities at the ocean surface from 1993 to 2023. The EKE is calculated from anomalies of these geostrophic velocities. We analyzed EKE trends computed from three different altimetric products: a global product derived from a stable two-satellite constellation (two-sat) and two others (global and European) incorporating all available satellites (all-sat). While all products reveal a general increase of EKE in the Mediterranean Sea over the period analyzed, trends calculated from the two-sat product are significantly smaller than those computed from the all-sat products. We surmise that this discrepancy is due to the increasing number of satellites over time used to construct the all-sat datasets, which enhances both spatial and temporal coverage, and, hence, their capacity to detect higher energy levels, and/or an underestimate of the EKE detected by the two-sat product. To further investigate these trends, along-track altimetric data (L3) were also used with a specific focus on the Alboran region. This area, dominated by intense mesoscale activity, holds strong statistically significant positive EKE trends. These findings highlight the importance of using altimetric products with a stable number of satellites and constructed for climate applications when addressing long-term ocean variability analysis.
How to cite: Hargous, P., Combes, V., Barceló-Llull, B., and Pascual, A.: Satellite Altimetry Reveals Intensification of Eddy Kinetic Energy in the Mediterranean Sea, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-2001, https://doi.org/10.5194/egusphere-egu25-2001, 2025.
Ocean reanalyses utilize state-of-the-art models that are constrained by atmospheric forcing and incorporate the best available observations through data assimilation techniques to reconstruct historical conditions. The Black Sea Physics Reanalysis (BLK-REA) product delivered within the Copernicus Marine Service provides a comprehensive dataset of oceanographic fields for the Black Sea basin, starting from January 1993. This high-resolution reanalysis is built using the NEMOv4.0 general circulation ocean model, implemented at a horizontal resolution of 1/40° and 121 vertical levels, delivering a detailed and accurate representation of ocean dynamics in the region. The BLK-REA is driven by atmospheric fluxes derived from ECMWF ERA5 fields with spatial and temporal resolutions of 1/4° and 1 hour, respectively. Sea surface temperature (SST) relaxation, based on the ESA-CCI SST-L4 product, is applied for heat flux corrections. A key advancement in this version is the incorporation of lateral open boundary conditions (LOBCs), enabling more accurate inflow and outflow dynamics at the Bosphorus Strait. The data assimilation system, OceanVar, utilizes a three-dimensional variational (3D-Var) assimilation algorithm. It integrates model outputs with along-track sea level anomaly (SLA) observations from Copernicus Marine, as well as in-situ temperature and salinity profiles sourced from SeaDataNet and Copernicus Marine datasets. Enhancements in the data assimilation include the adoption of an improved background error covariance matrix and an observation-based mean dynamic topography for SLA assimilation. The results of the reanalysis demonstrate a significant improvement in accuracy compared to previous versions, with better alignment to observed data. BLK-REA has proven to be an invaluable tool for generating Ocean Monitoring Indicators, essential for assessing climate change impacts in the Black Sea. For example, the analysis reveals ongoing warming within the 25–150 m depth range, corresponding to the Cold Intermediate Layer.
Looking ahead, future iterations of BLK-REA aim to expand the domain to include the Azov Sea and introduce enhanced Bosphorus LOBCs. Planned upgrades to the data assimilation system include the integration of a barotropic model for SLA assimilation and the first-guess-at-the-appropriate-time approach. Starting from 1980, the next reanalysis will provide a more comprehensive temporal scope, further enhancing the monitoring and assessment of climate-related changes in the Black Sea region.
How to cite: Lima, L., Azevedo, D., Ilicak, M., Costa, F., Sözer, A., Cretì, S., Causio, S., Miraglio, P., Jansen, E., and Clementi, E.: A New High-Resolution Black Sea Physics Reanalysis, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-7131, https://doi.org/10.5194/egusphere-egu25-7131, 2025.
How to cite: Mamnun, N., Perruche, C., and Lamouroux, J.: BIORYS4: A New Global Ocean Biogeochemical Reanalysis within Copernicus Marine Service, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-6514, https://doi.org/10.5194/egusphere-egu25-6514, 2025.
Since mid-2019, meso-zooplankton and micronekton density hindcast (large past time series that are processed with time-consistent forcings) are available and regularly extended for the Copernicus Marine Service catalogue. The product (also known as MICRORYS) is computed using SEAPODYM-LMTL, the Lower and Mid Trophic levels model of the Spatial Ecosystem And POpulation DYnamic Modeling framework. Meso-zooplankton organisms (200µm-2mm) constitute the low-trophic level. These organisms are transported along with the water masses. Micronekton organisms, constituting the mid-trophic level, are bigger organisms (2-20cm) able to swim over short distances. SEAPODYM models the spatial and population dynamics of the LMTL population with a system of advection-diffusion-reaction equations. The vertical dimension is simplified into three layers (namely epipelagic, upper, and lower mesopelagic). Layers matches the vertical distribution of organisms that is observed. The six micronekton groups are defined according to their diel vertical migration from the surface at night to the deep ocean during the day. MICRORYS product uses a global configuration of SEAPODYM at 1/12° daily resolution. We will present the latest release (dec. 2024) computed with a new computational grid with better geometrical properties. We will also visit new applications of micronekton biomass densities as prey fields for marine predators to better understand their behaviour. We will end with new contribution related to mid trophic levels to the Ocean State Report and the description of potential Ocean Monitoring Indicators.
How to cite: Titaud, O., Albernhe, S., Conchon, A., and Mérillet, L.: Low and mid-trophic levels hindcasts of the Copernicus Marine Service catalogue: new release and contribution to the Ocean State Report., EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-1392, https://doi.org/10.5194/egusphere-egu25-1392, 2025.
This study demonstrates a proof of concept for two-way coupling between generic higher-trophic-level (HTL) biomass models —fish and macrobenthos— and three lower-trophic-level (LTL) models used by Copernicus Marine Services. The ECOSMO E2E model is a functional group type ecosystem model with fish and macrobenthos within a standard NPZD (nutrient–phytoplankton–zooplankton–detritus) framework. By reprogramming fish and macrobenthos into independent modules (ECOSMO-E2E v2.0), we can now couple them flexibly with multiple LTL models of similar class as ECOSMO. We utilise the Framework for Aquatic Biogeochemical Models (FABM) to couple ECOSMO-E2E v2.0 with three LTL models: ECOSMO, ERSEM, and ERGOM. Our test setup focuses on a 1D water column in the central North Sea, simulated with the General Ocean Turbulence Model (GOTM). For simplicity, we ignore horizontal fish movement in our experiments. The model simulated fish biomass compares well with the observed annual fish biomass from International Bottom Trawl Survey estimates. Additionally, we explore how two-way coupling affects the LTL biomass dynamics in different model configurations. Our results emphasize the necessity of including HTL components in marine ecosystem models. Two-way coupling not only simulates realistic fish and macrobenthos fields but also provides spatially and temporally explicit closure terms to LTL model fields.
How to cite: Vijayakumaran, V., Daewel, U., Millington, R., Bruggeman, J., Powley, H., Lessin, G., Lindenthal, A., and Schrum, C.: The effect of coupling higher trophic level modules on the dynamics of three models of lower trophic level , EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-7123, https://doi.org/10.5194/egusphere-egu25-7123, 2025.
Ocean and sea-ice reanalyses are reconstructions of historical ocean and sea-ice states generated by ingesting observations into simulated model states through data assimilation methods. The Ocean ReAnalysis System-6 (ORAS6) is the 6th generation of ECMWF ocean and sea-ice reanalysis system. ORAS6 is forced by hourly ERA5 atmospheric fields and uses an ensemble variational ocean data assimilation (EDA) together with the latest reprocessed input datasets to produce a state-of-the-art 11-member ensemble of ocean reanalyses. Ocean and sea-ice states from ORAS6 will be used as ocean initial conditions for both the upcoming coupled ERA6 atmospheric reanalysis and ECMWF forecasting activities and will also be crucial for the continuation of climate monitoring activities within the Copernicus Services.
This presentation will address the performance of ORAS6 with respect to its predecessor (ORAS5) in terms of: fit to both in-situ and remotely sensed observations; representation of physical processes such as ocean transport and SST diurnal cycle; and also in terms of quality and consistency of the climate signals. Impacts of the use of an upgraded ocean and sea-ice model, new data assimilation methods and state-of-the-art atmospheric forcings and ocean observing system will also be evaluated in ORAS6.
Finally, the positive impact of ORAS6 ocean states as initial conditions for ECMWF coupled atmosphere-ocean-sea-ice forecasts will be discussed.
How to cite: de Boisseson, E., Zuo, H., Balmaseda, M., Browne, P., Chrust, M., Johnson, S., Keeley, S., Mayer, M., Mogensen, K., Pelletier, C., Roberts, C., de Rosnay, P., and Takakura, T.: ECMWF 6th generation ocean and sea-ice reanalysis system (ORAS6), EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-8348, https://doi.org/10.5194/egusphere-egu25-8348, 2025.
Arctic sea ice has recently experienced rapid changes, indicating a transition toward a new sea ice regime dominated by the marginal ice zone (MIZ) during summer. Modifications in extent, distribution, and volume of the MIZ have significant implications for polar and global climate, as the physical processes in the marginal ice largely differ from those in the pack ice, including air/sea exchanges, dynamic interactions with waves and currents, fast thermodynamic changes, and impact on marine ecosystems.
Copernicus Marine Service (CMS) provides a wide range of products capable of detecting the evolution of Arctic sea ice. Interestingly, not only the Arctic-focused regional products (such as TOPAZ reanalysis and satellite observations) can be used for this purpose, but the Global ocean Reanalysis Ensemble Product (GREP) has also proven its effectiveness in capturing the recent-past state of the Arctic sea ice.
Here, we study the temporal and spatial variability of Northern Hemisphere sea ice area and thickness over the past three decades, assessing their representation across a range of CMS products. The reanalyses are examined against CMS remote sensing observations as well as other Arctic reanalysis products.
We propose metrics at the pan-Arctic scale while also emphasizing the different responses of MIZ and consolidated pack ice to climate change. The results show that GREP and TOPAZ provide reliable estimates of present-day and recent past Arctic sea ice states and accurately reproduce the space/time variability of the MIZ area. In recents summers, the MIZ across both products has accounted for up to 40% of the total Arctic sea ice area, with its position (computed as monthly averaged latitude) experiencing a northward shift due to the contraction of pack ice in the central Arctic. Notably, despite an increased ensemble spread for sea ice thickness compared to that of sea ice area, GREP displays coherent interannual variability and trend. The proportion of GREP sea ice thinner than 2m has increased from 40% to 80% over the last 30 years. Additionally, TOPAZ demonstrates a significant impact of data assimilation updates on its outputs.
Overall, this study confirms that CMS reanalysis products are adequate tools for understanding the mean state and variability of ice classes in the Arctic region. Furthermore, these products hold significant potential for training machine learning model emulators for new predictions and supporting climate-related applications.
How to cite: Cocetta, F., Iovino, D., and Zampieri, L.: Evolution of Arctic sea ice in CMS reanalyses, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-17548, https://doi.org/10.5194/egusphere-egu25-17548, 2025.
The increasing adoption of AI-based approaches in Earth system sciences has led to breakthroughs in modeling and forecasting, exemplified by state-of-the-art performance of neural weather forecasting systems [Bi et al., 2023, Lam et al., 2022]. In oceanography, Deep Learning techniques show significant promise for advancing ocean state modeling by combining both modeled and observational ocean datasets [Febvre et al., 2023, Martin et al., 2023, Wang et al., 2024]. However, in the context of ocean forecasting, the deployment of neural forecasting approaches faces challenges such as sparse observational data and uncertainties in existing datasets. Despite advances in ocean observation systems, the ocean remains under-sampled, complicating the training of robust forecasting models [Wang et al., 2024].
This study presents the application of the 4DVarNet framework [Fablet et al., 2021, Fablet et al., 2023] in forecast mode, specifically for 7-day sea surface height (SSH) prediction. 4DVarNet employs an end-to-end Deep Learning strategy to forecast future SSH state from sparse satellite observational data. Using a variational data assimilation formulation, the framework combines a UNet with a convolutional LSTM to iteratively reconstruct future ocean state. The model was trained on synthetic altimetry observations sampled from the GLORYS12 operational reanalysis (2010–2019) and evaluated on independent Nadir altimetry tracks from 2023.
The results demonstrate that 4DVarNet outperforms traditional state-of-the-art operational forecasting system GLO12 [Lellouche et al., 2013], achieving a normalized RMSE (nRMSE) score of 0.92 for lead time 0 compared to 0.86 for the baseline GLO12. The model shows superior accuracy across all forecast lead times, highlighting its potential advantage in operational oceanography. The framework improves the accuracy of the SSH forecast by effectively using gappy satellite altimetry data. This demonstrates a particular interest of applying the proposed method to other data sources, such as the SWOT altimetry mission, but also of implementing alternative learning strategies, including training on synthetic datasets and fine-tuning with real-world altimetry observations.
In addition to the improved predictive performance compared to the state-of-the-art operational forecast system, this study establishes a standardized workflow for data processing, training, and evaluation, inspired by OceanBench framework [Johnson et al., 2023].
This research highlights the potential of the 4DVarNet framework for short-term neural ocean forecasting. The proposed method efficiently handles sparse altimetry data and achieves significant performance in predicting 7-days gap-free SSH state at global scale, improving the accuracy by almost 65% in average compared to the baseline GLO12. Future studies should focus on improving the model by incorporating additional data sources, evaluating the impact of input and output resolutions and associated learning strategies (eg. patching), and exploring its applicability to additional variables describing ocean state other than the SSH.
How to cite: Botvynko, D., Haslée, P., de Boyer Montégut, C., Chapron, B., Gaultier, L., Le Sommer, J., el Aouni, A., and Fablet, R.: OceanBench - Short-Term Global Ocean Forecasting, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-9294, https://doi.org/10.5194/egusphere-egu25-9294, 2025.
Chlorophyll concentration presents important implications in marine ecosystems (e.g eutrophication and proxy for phytoplankton abundance). Chlorophyll can be indirectly (satellite) or directly (insitu) observed and estimated through deterministic models. However, all these estimations present some limits: deterministic models cover the whole 3D domain but they can be inaccurate, while observations, highly accurate, are too sparse. Their integration through model-data fusion approach represents a new frontier for biogeochemical modeling.
We present a deep-learning approach for modeling the 3D distribution of biogeochemical variables in the Mediterranean Sea. Specifically, this work focuses on generating new 3D maps of chlorophyll-a by (a) modeling its relationship with physical variables, whose 3D-distribution is provided by the CMEMS physical numerical model, and (b) merging in-situ observations (i.e. BGC-Argo). The resulting 3D map offers a more accurate prediction leveraging the inclusion of Argo-float measurements, which are characterized by more accurate predictions than numerical model outputs.
This provides a tool that, given a 3D distribution of physical variables and sparse measurements of a biogeochemical variable, yields a 3D reconstruction of such biogeochemical variables. The novelty of this method lies in its ability to improve the accuracy of biogeochemical variable predictions by incorporating 1D Argo-float data into a 3D context, thus extending localized measurements over larger spatial domains.
The neural network models the relationship between physical variables and chlorophyll using numerical data (from BFM model) as a baseline. Since numerical models introduce approximation errors, a second training corrects these inaccuracies by incorporating Argo-float data.
We adopt a convolutional neural network (CNN), a deep learning architecture specifically designed to capture spatial correlation patterns. CNNs, commonly used for image reconstruction tasks, treat the 3D field (with an horizontal resolution of ⅛ x ⅛ degree for 30 vertical levels) as an image, replacing canonical RGB values by physical and biogeochemical variables.
To incorporate data from different sources, the training is divided into two-step: firstly, the network learns how to reproduce chlorophyll-a distribution with BFM model data, while secondly it incorporates Argo-float chlorophyll measures. In this way, Argo-float data are integrated into an already trained framework, thus entirely absorbing and expanding their information.
Trained on weekly data in the years 2019-2021 and tested on 2022, CNN shows the capability of reproducing chlorophyll maps mimicking BFM data, which are improved in the second step through the use of Argo-float. Results show the effectiveness of the proposed two-step method, since the use of BGC-Argo data not only leads the reconstruction closer to data itself but allows corrections to spread in the 3D domain.
To summarize, this approach exploits CNNs for the resolution of a re-mapping problem including different data sources. The two-step training procedure provides a new simple and intuitive method to efficiently merge sparse and incomplete data into a 3D seamless domain.
How to cite: Tonelli, T., Pietropolli, G., Cossarini, G., and Manzoni, L.: Convolutional neural networks for chlorophyll prediction in the Mediterranean Sea, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-6062, https://doi.org/10.5194/egusphere-egu25-6062, 2025.
The Copernicus Program, part of the EU Space program, is a publicly funded initiative benefiting European citizens by providing comprehensive Earth observation data. It transforms information from satellites and in-situ measurement systems into value-added data, supporting regional, national, European, and international efforts to address global challenges like marine environment preservation, climate change, land management, and atmospheric pollution. By offering free and open access, the program fosters innovation and the development of diverse applications and services. The Copernicus Marine Service provides reliable, regular information on the global and regional status of the Blue (physical), White (sea ice), and Green (biogeochemical) ocean. It aligns with EU policies and international commitments, addressing societal needs for ocean knowledge, supporting the Blue Economy, and contributing to marine protection, pollution control, maritime safety, renewable marine energy, and climate monitoring. Its comprehensive coverage includes current situation (analysis), 10-day forecasts, and retrospective data records (reprocessing of in-situ and satellite observations and reanalysis of model simulations). The program's significance extends beyond data provision to facilitating value-added services through innovative applications, referred to as "use cases." These downstream applications illustrate Copernicus data usage in various Blue Economy sectors, inspiring new users and stakeholders. Each entrusted entity engages actively with users to develop these applications and assist stakeholders in leveraging the data effectively. To enhance user engagement, the Copernicus Marine Service launched six calls for tenders during its first phase (2015-2021), receiving 122 bids and signing 40 contracts. In its second phase (2021-2028), the National Collaboration Program (NCP) was introduced with €6M funding to support the development of downstream services at national and transnational levels. The program includes four calls for tenders focusing on coastal and Arctic hubs, environmental EU policies, and stakeholder mapping to serve the Blue Market. Co-designed with the Copernicus Marine Forum, comprising representatives from EU Member and contributing States, NCP aims to increase uptake of Copernicus Marine Services by national coastal services. Thus far, 40 use cases have been funded through 15 projects involving 29 organizations across 12 European countries, driving innovation and advancing ocean governance.
How to cite: Silovic, T., Giunta, V., Lux, M., Crosnier, L., and Derval, C.: The Copernicus Marine National Collaboration Program , EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-11675, https://doi.org/10.5194/egusphere-egu25-11675, 2025.
Latvia’s Baltic Sea coast, with its network of ports, requires precise and timely sea state information to ensure safe and efficient navigation. The HywasPort service, operational since 2020, addresses this need by providing high-resolution hydrodynamic and wave forecasts within port aquatories. However, challenges persisted in port approaches, where open sea models lack the spatial detail necessary, and inner port models fall short.
The recent upgrade of the HywasPort service bridges this critical gap. It ensures a seamless transition between inner port and coastal marine models. Covering eight Latvian harbors, the system provides forecasts for waves, currents, sea level, temperature, salinity, and wind, alongside user and third-party observations.
The system is driven by HBM oceanographic model in an operational setup by the University of Latvia. It uses Copernicus Marine products as boundary conditions. The advanced seven-level nesting structure offers resolutions as fine as 36 meters, supporting accurate modeling of harbor entrances and outer coastal regions.
End users, including port authorities, dredging businesses, fishermen, and leisure sailors, benefit from a unified visualization platform that integrates data of various origin. This tool enhances decision-making and safety in areas prone to dynamic physical changes like waves, cross-currents, and siltation.
The reliability of the system is being continuously validated against observations from buoys, current meters, and gauges. On the other hand system provides spatial and temporal context for these limited observations.
In addition to navigation support, the service provides model support for coastal management and conservation efforts. Namely, it includes (1) operational sediment flux field in open seas and (2) seasonal and annual longshore transport along the Latvia’s coast.
The development of HywasPort system was funded under the Copernicus Marine National Collaboration Program.
How to cite: Timuhins, A., Bethers, U., Seņņikovs, J., Frišfelds, V., and Cepīte-Frišfelde, D.: HywasPort: Bridging Latvia’s Ports and Open Seas with Seamless Forecasting, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-8643, https://doi.org/10.5194/egusphere-egu25-8643, 2025.
Ostrea edulis has been harvested in Galway Bay, Ireland, for centuries, but the oyster aquaculture in the bay is facing multiple threats, including E. coli contamination, B. ostreae outbreaks and an alteration to freshwater inflow due to the development of a flood relief scheme. Periods characterized by low salinities (S<20 g kg-1) are common in the bay, especially after heavy rainfall events. These episodes are often associated with increased oyster mortality rates and subsequent economic loss for the farming sector. It is therefore important for producers to have access to real-time data and marine forecasts, and this information has to be accessible in a user-friendly and interactive way. Access to static, climatological information on the distribution of different seawater properties affecting oyster farming is also interesting for long-term planning and management.
This contribution will present the developments funded under the Copernicus Marine Service COP INNO USER Programme and carried out by the Marine Institute, Ireland, and Nologin Oceanic Weather Systems, Spain, that facilitate the provision of these services to the local oyster farming sector and environmentalists involved in biodiversity restoration. A high resolution (70 m) hydrodynamic model of Galway Bay has been developed, covering inner Galway Bay east of Black Head. In parallel, a SWAN application has been developed to provide wave data for Galway Bay and adjacent shelf waters. A 2012-2022 hindcast was run to obtain static, climatological data on seawater temperature, salinity, bottom stress, and wave kinetic energy. Both models (hydrodynamic and wave models) run operationally, delivering a 3-day forecast every day. Marine conditions mapping and low salinity warning services have been implemented and current developments include the extension to biogeochemical variables, marine heatwaves and indicators of the rate of change of temperature and salinity during the extreme events.
Service to the end users in this project is facilitated through a user-friendly, interactive web application NAUI (biodiver.naui.io) where real-time observational data, forecasts and c. 10 years hindcast data is provided. This application constitutes an excellent example of the increasing efforts to extend the amount of marine observations and forecasts available to the general public and can become an important tool for management of the aquaculture activity and for biodiversity preservation in the region. We are in the process of integrating with the European Digital Twin of the Ocean since the service was selected as coastal demonstrator in the Digital Ocean Forum 2024. Integrating into EDITO would allow for a faster service and for an easy extension of the service to new geographical locations, enhancing its scalability and replicability.
How to cite: Pereiro, D., Dabrowski, T., García-Valdecasas, J. M., Sotillo, M., Lyons, K., and Nolan, G.: Operational oceanographic services in support of aquaculture and biodiversity in Galway Bay, Ireland, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-4517, https://doi.org/10.5194/egusphere-egu25-4517, 2025.
The Latvian coastline along the Baltic Sea, stretching from the Latvian-Lithuanian boundary northward and encompassing the cities of Liepāja and Ventspils (Kurzeme Coast), is undergoing persistent coastal erosion. Annually, significant bank and sand erosion can result in a coastal displacement of up to 2 to 3 meters. This coastline is crucial for Maritime Spatial Planning (MSP) and delineates the boundaries of private property abutting the sea.
This boundary between land and sea has always garnered considerable interest. Multiple measurements have been performed, encompassing conventional geodetic techniques and aerial laser scanning. Advances in remote sensing with the Copernicus Program and the use of references of the Copernicus Marine Service are some aspects that contributed to more accessible and faster data collection.
When merging remote sensing data with the terrestrial reference system and tidal gauge data from ports of Liepājas and Ventspils, this integration provides a significant source of research data that enhances our understanding of coastal erosion and also helps us to predict the long-term impacts on land-sea stability. This has considerable ramifications not only for the design and implementation of MSP but also for the wider framework of land-sea interactions and maritime and coastal planning along the Kurzeme coastline.
Acknowledgements/funding
Jānis Kaminskis, Ieva Demjanenko, Ļubova Šuļakova and Dāvis Sīka recognize the support supported by research and development grant No. RTU-PA-2024/1-0049 (”Maritime spatial planning according to international requirements on the Kurzeme coast”) under the EU Recovery and Resilience Facility funded project No. 5.2.1.1.i.0/2/24/I/CFLA/003 “Implementation of consolidation and management changes at Riga Technical University, Liepaja University, Rezekne Academy of Technology, Latvian Maritime Academy and Liepaja Maritime College for the progress towards excellence in higher education, science, and innovation”.
Leila Neimane acknowledges the support received within the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No. 101034309 in the framework of the SEAS (Shaping European Research Leaders for Marine Sustainability) programme.
How to cite: Kaminskis, J., Demjanenko, I., Neimane, L., Sulakova, L., and Sika, D.: The Ever-Dynamic Kurzeme Coast: Harnessing Remote Sensing for Erosion Monitoring in the Context of Maritime Spatial Planning (MSP), EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-16566, https://doi.org/10.5194/egusphere-egu25-16566, 2025.
The European Commission launched the European Digital Twin of the Ocean (EDITO) at the One Ocean Summit in Brest, France, in February 2022. The EU is building the infrastructure backbone of EDITO through two projects (EDITO-Model Lab and EDITO-Infra) finishing respectively beginning and end of 2025 and with a continuity until 2028 with EDITO2. This is aligned with Copernicus Marine Service where a strong connection with EDITO will be managed during the new starting phase (2025-2028). This presentation will focus on the main achievements and demonstration of global ocean model component development and applications that are already available on the EDITO platform such as the demonstration of global 3km resolution forecasting system (GLO36), the global forecasting system based on machine learning (GLONET) and validation and process-oriented diagnostics.
How to cite: Drillet, Y., Drevillon, M., Le Traon, P. Y., Tonani, M., Arnaud, A., El Aouni, A., Bricaud, C., Van Gennip, S., and Gaudel, Q.: New developments and complementarity between European Digital Twin Ocean and Copernicus Marine Service. , EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-12286, https://doi.org/10.5194/egusphere-egu25-12286, 2025.
The European Union’s Digital Twin of the Ocean (EU DTO) represents a novel initiative to integrate advanced digital technologies with ocean governance, aiming to model and predict marine ecosystems to support policy decisions and sustainable management. As a complex socio-technical infrastructure, the development of the EU DTO involves coordination across a vast geographic area, integrating diverse technologies, standards, and stakeholders with varying resources and interests. This paper therefore analyzes the EU DTO as a Socio-Technical Network (STN) comprising three core components: the physical oceanic entity, the digital technical artifact, and the intricate socio-technical relationships binding them. It pursues the following research questions: (1) What are the primary social actors and technical components comprising the EU DTO infrastructure? and (2) What Social-Social, Technical-Technical, and Socio-Technical relations define this infrastructure?. Using a mixed methods approach involving interview data, stakeholder surveys, and desk research, it empirically maps out the multi-layered socio-technical relationships within the DTO’s infrastructure. By modelling and analyzing the dynamic interplay between social actors and technical components, it identifies socio-technical barriers: firstly, technical barriers (e.g., lack of standardized data), secondly, social barriers (e.g., unequal resources), and thirdly, socio-technical barriers (e.g., unclear data transfer responsibilities). Combining this approach with a political ecology (PE) lens reveals the power dynamics and socio-environmental challenges of the EU DTO, including data accessibility disparities, and highlights how broader power relations, institutional interests, and political agendas shape its development and implementation.
How to cite: Hirt, C. and Vadrot, A.: Investigating and Modeling the Making of the EU Digital Twin of the Ocean, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-19807, https://doi.org/10.5194/egusphere-egu25-19807, 2025.
To address these challenges, we introduce Poseidon, an HPC-oriented source-to-source compiler designed for Fortran-based fluid dynamics solvers used in ocean and weather models with regular grid structures. Poseidon employs a novel process called uplifting, which treats existing models and their coding standards as Fortran-embedded DSLs and requires minimal source code changes. This approach, which relies on co-design with model developers, allows Poseidon to robustly recover high-level information and semantics that are typically lost during the conversion of numerical algorithms to source code. By doing so, Poseidon can perform safe and holistic optimizations for specific HPC architectures using a data flow graph intermediate representation. It then generates Fortran source code augmented with parallel programming model directives, which can be further optimized by vendor or open source compilers.
We detail Poseidon's methodology and present initial results by performing architecture-specific auto-tuned kernel fusion and automatic parallelization on both CPUs and GPUs using OpenMP or OpenACC on a research code that implements the 2D fast barotropic solver of the CROCO 3D ocean simulation model. Our results demonstrate significant performance improvements and validate the effectiveness of Poseidon's optimization strategies.
Additionally, we discuss our ongoing research efforts for the automatic injection of communications, e.g., MPI, for latency hiding, and the implementation of automatic differentiation at the data flow graph level for data assimilation. These advancements are crucial for further improving the performance and scalability of ocean simulation models.
Furthermore, we outline our current progress and future plans for integrating Poseidon with the NEMO ocean model using an elegant annotations-based uplifter, and leveraging its optimization techniques.
How to cite: Rémy, J., Brémond, M., Brunie, H., Debreu, L., Ford, R. W., Henrichs, J., Lemarié, F., Mittermair, A., Porter, A. R., Schreiber, M., Schulz, M., Siso, S., and Vidard, A.: Poseidon: A Source-to-Source Compiler for Optimizing Ocean Simulation Models on Modern HPC Architectures, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-12230, https://doi.org/10.5194/egusphere-egu25-12230, 2025.
The SeSaM (Seasonal Sargassum Monitoring and Forecasting) project addresses the critical challenge of managing mass sargassum invasions in the Tropical Atlantic Ocean, providing key insights and forecasting tools for stakeholders. Mercator Ocean International has operationalized the NEMO-based model of sargassum distribution, initially developed by the French National Research Institute for Sustainable Development (IRD). Integrated into the NEMO4.2 framework, the model enables 7-month ensemble forecasts of the physical ocean (SST, currents) and the related sargassum distribution using initial conditions derived from Sentinel-3/OLCI satellite data provided by CLS (Collecte Localisation Satellites). The system delivers reliable predictions of Sargassum transport and seasonal evolution. Forecasts for 2020–2025 are accessible through the project platform. By 2025, these forecasts will also be available on the Digital Twin of the Ocean (DTO), through the EDITO platform (European DTO) with monthly updates. Future enhancements will include interactive user services within the DTO, enabling "what-if" scenarios to optimize collection strategies and support informed decision-making. This initiative is a key step toward mitigating the ecological and socio-economic impacts of Sargassum influxes while exploring its potential as a resource.
How to cite: Many, G., Ruggiero, G., Jouanno, J., Lucas, M., Gaudel, Q., and Lellouche, J.-M.: The SeSaM Project: Sargassum Forecasting and its Integration into the Digital Twin of the Ocean, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-11408, https://doi.org/10.5194/egusphere-egu25-11408, 2025.
Posters on site: Thu, 1 May, 10:45–12:30 | Hall X5
The ocean surface wind plays a key role in the exchange of heat, gases and momentum at the atmosphere-ocean interface. High-quality ocean surface wind records from scatterometers are available from 1991 onwards. Care has been taken to account for changes in scatterometer instrument types and spatial coverage over time, such that these records can be used to assess changes in the ocean surface wind over the past 30 years. On the other hand, modelled surface winds from global climate reanalyses (e.g. ERA) suffer from changes in the density and coverage of observational timeseries used in the data assimilation process. Still, global numerical weather prediction (NWP) model wind fields are widely used in the computation of ocean surface processes to study climate trends and variability in ocean variables.
A comparison of scatterometer observations and global NWP model wind fields reveals substantial, persistent local systematic errors in wind vector components and spatial derivatives. Temporally-averaged gridded differences between geolocated scatterometer wind data and ERA/NWP wind fields can be used to correct for persistent local model wind vector biases. By combining these scatterometer-based bias corrections with global, hourly ERA/NWP wind fields, high-resolution wind forcing products can be created for the ocean modelling community and other users.
In 2022, new hourly and monthly Level-4 (L4) surface wind products were introduced in the Copernicus Marine Service catalogue. These products include global bias-corrected 10-m stress-equivalent wind, surface wind stress fields and spatial derivatives. The bias corrections are calculated from Copernicus Marine Service Level-3 wind products for a combination of scatterometers and their collocated European Centre for Medium-range Weather Forecasts (ECMWF) model winds.
We used the monthly multi-year L4 product to identify long-term changes in ocean surface wind differences over the period 1995-2024. The spatial distribution of differences between scatterometer observations and collocated ECMWF ERA5 reanalysis are found to be highly consistent between different scatterometers and over time. Remaining small differences between individual scatterometers could be caused by different instrument characteristics, sampling, coverage and processing and may be further reduced by continued intercalibration efforts. Bias corrections for a single instrument display long-term variations of comparable magnitude to the scatterometer-model differences, which point to artificial changes in the ERA5 winds over time. Furthermore, regional local bias anomalies are found for climate phenomena like the El Niño Southern Oscillation. These artificial features should be taken into account in any long-term reanalysis of ocean surface wind fields.
How to cite: Giesen, R. and Stoffelen, A.: Multi-decadal variability in ocean surface wind differences between scatterometer observations and reanalysis model fields, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-8961, https://doi.org/10.5194/egusphere-egu25-8961, 2025.
Mercator-Ocean has developed a regional reanalysis over the Northeast Atlantic (IBI: Iberia, Biscay and Irish), called IBIRYS. The reanalysis was first delivered in 2015 in the framework of the MyOcean project, and has since been regularly updated, now delivered on the Copernicus Marine Service datastore. It also contributes to the annual Copernicus Ocean State Report, and Ocean Monitoring Indices are calculated from the reanalysis to monitor the health of the ocean.
NEMO modelling platform resolves ocean dynamics and thermodynamics, and the lower trophic levels’ ecosystem dynamics is simulated by the PISCES biogeochemical model. The two components are coupled “online”. The data assimilation system (Mercator Ocean assimilation system SAM2) allows constraining the physical model in a multivariate way with Sea Surface Temperature, together with all available satellite Sea Level Anomalies, and with in-situ observations. In addition to SAM2, a large bias correction is also applied. The new release of the reanalysis, expected to be on Copernicus products’ catalogue in 2025, is now at 1/36° resolution, and benefits from updates of the models (for physics and biogeochemistry), of the data assimilation system, and input data.
In this presentation, we present the assessment of the new reanalysis for both physical and biogeochemical components. We compare the new reanalysis to the former one, and to the Mercator Ocean global reanalysis GLORYS. We also assess physical and biogeochemical components in confrontation with classical observations (SST, in-situ profiles, etc).
How to cite: Levier, B., Escudier, R., Gutknecht, E., Reffray, G., Cailleau, S., Aznar, R., Ciliberti, S., Sotillo, M., and de Pascual, Á.: IBIRYS: a Regional High-Resolution Reanalysis (physical and biogeochemical) of the last 30 years (1993-2023) over the European Northeast Shelf, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-15937, https://doi.org/10.5194/egusphere-egu25-15937, 2025.
Although climate change is mainly observed on the Earth's surface, it is known that ocean circulation is also changing and the seabed is subject to temperature fluctuations. Seafloor sediments are often permeated by a methane hydrate phase whose stability depends primarily on temperature and pressure fields. Any change in the temperature of the seabed can alter the stability state of the methane hydrate. The dissociation of methane hydrate, a consequence of its unstable state, could release large amounts of methane into the water column. Methane, which could then impact submarine geologic hazards such as submarine landslides, and the eventual reaching of the atmosphere by methane would exacerbate ongoing climate change.
In this work, we computed the depth of the gas hydrate stability zone (GHSZ) at the global scale using data from the EU Copernicus Marine Service (CMS), and its changes in the period from 1993 to 2023 were analyzed at 5-year intervals. The aim was to investigate the impact of climate change on the methane hydrate stability zone.
We used oceanographic temperature and salinity data from the Global Ocean Physics Reanalysis dataset (GLORYS12V1), which was produced as part of CMS, depth data from GEBCO - The General Bathymetric Chart of the Oceans, and geothermal gradient data, derived from the heat flow data reported by Lucazeau (2019, Geochemistry, Geophysics, Geosystems, 20: 4001-4024, https://doi.org/10.1029/2019GC008389).
The depth of the gas hydrate stability zone was calculated from monthly data, which were then averaged over the 12 months of each year considered to obtain annual average values of GHSZ depth. The salinity and temperature data extracted from GLORYS12V1 have a resolution of 1/12 of a degree in longitude and latitude, resulting in a decomposition of the sea surface into approximately 9 million cells and referenced to 50 different depth levels. The availability of salinity and temperature data for the entire water column was essential for a more accurate calculation of seafloor pressure. The contribution to the seafloor pressure of each of the 50 layers into which the water column was divided was calculated using Stevino's law, rather than using the more commonly used dbar-meter approximation. It was also analyzed how the reanalysis data uncertainty obtained from the quality information document provided by CMS affected the final result of the gas hydrate stability zone depth estimate.
The high resolution and completeness of the data made it possible to obtain a relevant result on a global scale, in agreement with literature, showing that over the period considered, the number of model cells subject to GHSZ thinning is much greater than the number of cells subject to GHSZ thickening, particularly in the Southern Hemisphere.
How to cite: Riccucci, L., Camerlenghi, A., Salon, S., and Tinivella, U.: Using Copernicus global ocean reanalysis data to estimate the evolution of the gas hydrate stability zone, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-6665, https://doi.org/10.5194/egusphere-egu25-6665, 2025.
The western Black Sea basin is a region of scientific interest in terms of its past and present level of ecological degradation by anthropogenic influences among the European Seas. Its coastal areas are the subject of continuous remote monitoring and operational observing system, towards human activities harmonization. Integrated Coastal Zone Management (ICZM), as a long-term management tool integrated within Maritime Spatial Planning (MSP), was established to protect the population, sustain exploitation of coastal resources and mitigate the effects of climate change and marine hazards. In the same direction, the Ocean forecast systems and Earth Observation (EO) data can significantly contribute to the advance of oceanographic knowledge, but also to support maritime activities, including MSP/ICZM measures’ implementation in the area.
The Earth Observations data provided by Copernicus Marine Environment Monitoring Service (CMEMS), including the model data provided by several marine forecast systems, constitutes the source for several user-orientated, operational downstream services for specific activities in the western Black Sea basin.
In the present work, will be described, two CMEMS’ funded projects, develop based on a holistic approach that covers different elements with potential environmental impact. To deliver specific support at regional and national level, several serviced were developed, being supportive for the strategy concerning the Blue Growth in the region, by facilitating the access to key environmental variables related to safe navigation, marine pollution, coastal tourism, and beach management. In the present work certain modelling/EO-based results of CMEMS uses uptake projects, will be presented together with associated lessons learned, for future implementations in various areas and activities domains within the western Black Sea Basin.
How to cite: Mateescu, R., Silva, A., Vandenbulche, L., Vlasceanu, E., and Niculescu, D.: CMEMS’ Downstream Operational Services for the monitoring-modeling-management of the marine and coastal areas of the western Black Sea Basin , EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-20659, https://doi.org/10.5194/egusphere-egu25-20659, 2025.
Copernicus Marine Service Monitoring and Forecasting Centres (MFCs) are improving their models to resolve finer-scale oceanographic features, driven by a growing need for high-resolution, short-term ocean forecasts. A key limitation to forecast accuracy, however, stems from errors in the model forcings. These errors can be mitigated with Artificial Neural Networks (ANNs) that are trained with the increasing volume of remote sensing observations. ANNs allow to extract spatio-temporal patterns from these measurements, enabling the generation of enhanced forcings by integrating these correction patterns with existing operational forcings.
The Copernicus Marine Service Evolution CERAINE project (2024 – 2026) aims to improve short-term ocean and wave model forecasts within the European North-East Atlantic (NEA) region by enhancing the accuracy of their model forcings using ANNs. Two distinct ANN methodologies will be implemented. The first one will focus on correcting wind forcings, using Synthetic Aperture Radar (SAR) data for coastal zones and scatterometer data for offshore areas. These improved wind fields will subsequently be used as forcing inputs for both ocean physics and wave models. A second type of ANNs will be developed to correct surface ocean currents, which are important inputs for spectral wave models, using data acquired from High Frequency Radar deployed at coastal sites.
The NEA region, which encompasses the Copernicus Marine Service IBI (Iberian-Biscay-Ireland) and NWS (North-West-Shelf) products, has been chosen as the project's pilot area due to two key reasons: (i) the expected significant impact of the proposed forcing corrections on both coastal and offshore waters, and (ii) the availability of a comprehensive observational network in this region. The project will assess the impact of these ANN-derived forcings on the IBI-MFC NEA ocean and wave models through a series of sensitivity tests. CERAINE holds the potential for direct integration of its results into the IBI-MFC operational service and the subsequent extension of this approach to other Copernicus Marine MFC target regions.
This contribution will show the on-going development of the wind and surface currents ANNs, and their updated validation under a set of recent events.
How to cite: Garcia-Leon, M., Portabella, M., Garcia-Valdecasas, J. M., Makarova, E., Gómez, B., Aouf, L., Ciliberti, S., Dalphinet, A., Aquino, V., Alonso, A., Fernández, C., Aznar, R., and Sotillo, M.: Enhancing wave and ocean forecasts with Artificial Intelligence in the North-East Atlantic and Shelf Region – The Copernicus Marine Service Evolution CERAINE project, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-8976, https://doi.org/10.5194/egusphere-egu25-8976, 2025.
Both uncertainty assessment and validation have shown that the current global products of phytoplankton functional types (PFT) on Copernicus Marine Service for the Arctic Ocean (AO) bear larger gaps and higher uncertainties compared to that in the low latitude oceans. In the framework of Copernicus Marine Service Evolution Program, we propose a project ML-PhyTAO to exploit marine big data-driven machine learning (ML) methods in the PFT monitoring for high latitudes, and aim to set up an improved algorithm for better quantifications of multiple PFTs in the AO. A large marine data set (including bio-optical, biogeochemical, and physical data) obtained from various sources will be exploited as inputs for algorithm training and validation. The ML-PhyTAO is expected to deliver improved gap-free products of several key PFTs (diatoms, haptophytes, dinoflagellates, chlorophytes and prokaryotes) with uncertainty assessment to complement the current ocean colour/ biogeochemical data sets for the AO on the Copernicus Marine Service Data Store. Such PFT data set with improved accuracy will allow reliable long-term monitoring and trend analyses for the surface phytoplankton community structure, helping in detecting potential shifts and changes in phytoplankton diversity in the AO under the Arctic amplification effect. In this work we will demonstrate the framework of the project and present our latest outcome from the project by showing our first results on the experiments of ML methods using our well compiled training data sets including the in situ PFT data, satellite and model simulated data/products from Copernicus Marine Service covering various optical/physical/biogeochemical parameters.
How to cite: Xi, H., Prat, A., Mehdipour, E., Bretagnon, M., Mangin, A., and Bracher, A.: A Machine Learning based approach towards products of Phytoplankton functional Types in the Arctic Ocean (ML-PhyTAO), EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-19280, https://doi.org/10.5194/egusphere-egu25-19280, 2025.
Non-collaborative vessels identification is a strategical interest both for the civil and military world. Indeed, boats involved in illegal activities can become unrecognizable from other receiving antennas by switching off their AIS, thus resulting as “dark vessels”.
Satellite imagery can in principle support the detection of dark vessels through the automatic identification of their wakes, but these patterns and their visibility are strongly influenced by meteo-marine conditions. In this direction, the UEIKAP (Unveil and Explore the In-depth Knowledge of earth observation data for maritime Applications) Project, funded by the Italian Ministry of University and Research, is developing an Artificial Intelligence (AI) system for the automatic identification of dark vessels from optical and SAR (Synthetic Aperture Radar) images. In particular, this contribution focuses on the creation of the dataset used for the training of the AI based on data from Marine Copernicus Ocean and other publicly available repositories. The AI requires an extensive satellite image dataset of vessels and related wakes to be trained, with an analogue dataset of similar wake patterns caused by external phenomenon and not by the vessel itself. Both are built with a number of 1500 optical images of wakes and 1000 non-wakes images in 4 different bands integrated with ancillary data. The same procedure is applied also for SAR images. A crucial role is played by Marine Copernicus data in assessing the environmental conditions that can control pattern formation on the sea surface and its visibility, supporting the interpretation of satellite images and the disambiguation of wake and wake-like patterns
In practice, for each image depending on its acquisition time and location, our algorithm retrieves the gridded fields of key atmospheric and oceanographic variables, computes derived quantities and stores the whole information in a self-explanatory and interoperable netCDF file, additionally generating 2D plots of the extracted variables. More specifically, hourly atmospheric fields (10 m wind components, total cloud cover, and total precipitation) at 1/4° spatial grid resolution are retrieved from the ERA5 reanalysis via the Copernicus Climate Service (C3S). Oceanographic quantities such as wave spectral parameters, surface current velocity components, potential temperature, surface and near-surface salinity and temperature (upper 10m) are collected from Copernicus Marine Service (CMEMS) with hourly to daily frequency and spatial resolution ranging from 1/24° to 1/5°. Wave steepness, surface and near-surface potential density anomaly and its horizontal gradients, as well as surface current convergence and near-surface buoyancy frequency are additionally computed in the process. Although the final aim of this operation has been conceived for a specific scope, the code can easily be used for a broader set of applications with different meteo-Oceanografic information and different regions and conditions.
How to cite: Vavasori, P., Braga, F., Carmen Cristofano, A., Del Prete, R., Di Vaia, M., Fadini, A., Franciosa, F., Graziano, M. D., Iervolino, S., Mazzeo, A., Menegon, S., Scarpa, G. M., Sperandeo, M., Vernengo, G., Villa, D., and Bonaldo, D.: Using metocean repositories to support the creation of large datasets for AI applications , EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-20106, https://doi.org/10.5194/egusphere-egu25-20106, 2025.
The EDITO platform serves as the foundational framework for building the European Digital Twin of the Ocean, seamlessly integrating oceanographic data, processes and services on a single and comprehensive platform. The platform provides scalable computing resources co-located with a DataLake including both Copernicus Marine and EMODNET data, enabling near-data computing. We provide a STAC API to expose data and a Virtual Co Environment to exploit it. This enables single-click integration from data browsing to a cloud computing context. Within this context, users can benefit from EDITO capabilities such as data storage, CPU and GPU computing, frameworks, etc. Our presentation will showcase this direct integration through the EDITO viewer.
How to cite: Gasperi, J., Bertin, M., Gaudel, Q., Delaney, C., Lyobard, S., Tyberghein, L., and Arnaud, A.: Ease near-data computing with the EDITO Platform, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-21571, https://doi.org/10.5194/egusphere-egu25-21571, 2025.
Posters virtual: Wed, 30 Apr, 14:00–15:45 | vPoster spot 4
EGU25-8649 | Posters virtual | VPS18
Investigating vertical mixing and lateral diffusion parameterizations in the Mediterranean SeaWed, 30 Apr, 14:00–15:45 (CEST) | vP4.14
The Mediterranean Sea, with its unique characteristics as a semi-enclosed and highly stratified basin, serves as a natural laboratory for studying oceanic processes of global relevance. Vertical mixing is a fundamental process regulating the transfer of mass, heat, and nutrients between water column layers, influencing dynamical and biogeochemical processes, and controlling the exchange with the overlying atmosphere. Due to its turbulent nature acting on small spatial and temporal scales, vertical mixing remains challenging to simulate in modern ocean circulation models. Moreover, the interaction between vertical mixing and horizontal diffusion/advection is essential in shaping the transport and distribution of heat, nutrients, and pollutants in marine environments. Finding the optimal vertical mixing parameterizations alongside horizontal advection and diffusion schemes in an ocean circulation model, able to simulate the available observations, presents significant challenges due to the need for consistent scaling, numerical stability, and accurate representation of multi-scale processes.
Here, we use the same system setup as the Mediterranean Forecasting System of the Copernicus Marine Service, that is NEMO (v4.2) general circulation model, including tides, coupled with the WaveWatch III wave model. The model features a horizontal resolution of 1/24° (approximately 4 km) and 141 unevenly spaced vertical levels. We investigate the performance of different numerical vertical closure schemes – a Richardson-number-dependent, a one-equation and a two-equation models – as well as the effect of different lateral advection and diffusion schemes. The role played by the enhanced vertical diffusion due to Camarinal Sill at the Strait of Gibraltar in controlling the exchange of water masses between the Atlantic Ocean and the Mediterranean Sea is also investigated. We validate our model by assessing our ability to reproduce physical processes and by comparing it with in-situ data throughout the Mediterranean basin, across varying seasons and years.
How to cite: Gualtieri, L., Borile, F., Burchard, H., Oddo, P., Miraglio, P., Clementi, E., Goglio, A. C., and Pinardi, N.: Investigating vertical mixing and lateral diffusion parameterizations in the Mediterranean Sea, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-8649, https://doi.org/10.5194/egusphere-egu25-8649, 2025.
