OS4.9 | The Copernicus Marine Service and the future European Digital Twin of the Ocean
EDI
The Copernicus Marine Service and the future European Digital Twin of the Ocean
Convener: Stephanie Guinehut | Co-conveners: Anna Teruzzi, Andrea Storto, Julien Brajard, Benjamin JacobECSECS
Orals
| Tue, 16 Apr, 14:00–15:45 (CEST)
 
Room L2
Posters on site
| Attendance Mon, 15 Apr, 10:45–12:30 (CEST) | Display Mon, 15 Apr, 08:30–12:30
 
Hall X4
Posters virtual
| Attendance Mon, 15 Apr, 14:00–15:45 (CEST) | Display Mon, 15 Apr, 08:30–18:00
 
vHall X5
Orals |
Tue, 14:00
Mon, 10:45
Mon, 14:00
The Copernicus Marine Service provides regular and systematic reference information on the physical (including sea-ice and wind waves) and biogeochemical states of the global ocean and European regional seas. This capacity encompasses the description of the current ocean state, the prediction of the ocean state a few days ahead, and the provision of consistent retrospective data records for recent decades. In the coming years, Copernicus Marine will prepare the implementation of the next generation of ocean monitoring and forecasting systems and new services for the coastal ocean and for marine biology. Copernicus Marine will also progressively embrace the new capabilities of digital services in synergy with the EU Digital Twin of the Ocean (DTO) developments. The EU DTO will connect and interoperate, on a common digital platform, a large variety of ocean and coastal numerical models, allowing for global, regional-to-coastal model configurations and the co-development of new simulations and what-if-scenarios for enhanced on-demand ocean forecasting and ocean climate prediction.
The session focuses on the main Copernicus Marine Service research and development activities on ocean modelling; data assimilation; processing of observations, impact and design of in-situ and satellite observing systems; verification, validation, and uncertainty estimates; monitoring and long-term assessment of the ocean physical and biogeochemical states. The session also includes research activities that are required to prepare the next generation of ocean monitoring and forecasting systems (improved Arctic monitoring, ensemble forecasting, higher resolution, regional ocean climate projections, use of artificial intelligence techniques) and new services for the coastal ocean and for marine biology. The session will also encompass research activities that are required for the development of the European DTO, including the next generation of ocean models combining artificial intelligence and high-performance computing, dedicated infrastructures, and platforms as well as protocols and software and the definition of what-if-scenarios.
Presentations are not limited to research teams directly involved in the Copernicus Marine Service and the future European DTO. Participation from external teams from relevant Horizon Europe projects, from downstream applications and contributing to reinforcing global capacity in ocean forecasting and digital integration is strongly encouraged.

Orals: Tue, 16 Apr | Room L2

Chairpersons: Stephanie Guinehut, Benjamin Jacob, Anna Teruzzi
14:00–14:05
A blue & white ocean
14:05–14:15
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EGU24-18063
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ECS
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On-site presentation
Tore Wulf, Jørgen Buus-Hinkler, Suman Singha, Mads Hvid Ribergaard, Till Soya Rasmussen, and Matilde Brandt Kreiner

The Arctic’s unprecedented transformation due to anthropogenic warming necessitates close monitoring of sea ice to understand and address climate change impacts. As the sea ice retreats and becomes thinner, increased human activity in the region emphasizes the urgent need for detailed, near real-time sea ice information as well as improved sea ice forecasts for maritime safety and planning.

Current methods of Arctic sea ice retrieval relies on passive microwave (PMW) sensors, which offer global coverage but struggle to capture fine-scale features and changes in the sea ice. Synthetic Aperture Radar (SAR) imagery, with its high spatial resolution and independence from sunlight and clouds, is pivotal in the year-round mapping of Arctic sea ice conditions that is carried out manually at the national ice services. Yet, automating SAR-based sea ice retrieval remains challenging due to inherent ambiguities in the observations.

Recent advances in deep learning vision methodologies show promise in SAR-based sea ice retrievals. A robust pan-Arctic SAR-based sea ice retrieval system can serve maritime sectors, national ice services, and local communities by providing timely, high-resolution sea ice information. Furthermore, SAR-based sea ice retrievals can be assimilated in numerical ocean and sea ice models, improving sea ice forecasts crucial for local communities and maritime sectors.

Here, we present a comprehensive deep learning approach to retrieve high-resolution sea ice concentration and calibrated uncertainties from Sentinel-1 SAR and AMSR-2 PMW observations at a pan-Arctic scale for all seasons. Daily pan-Arctic sea ice products based on our methodology will be operationally provided as part of the Copernicus Marine Service portfolio by the end of 2024. Further, we are in the process of producing daily pan-Arctic products for the entire Sentinel-1 era, which began with the launch of Sentinel-1A in 2014. 

Lastly, we present preliminary results for the impact of assimilating level-2 SAR-based sea ice concentrations gap-filled with level-2 PMW-based sea ice concentration in the HYCOM-CICE coupled ocean-sea-ice forecasting system for the pan-Arctic region. 

How to cite: Wulf, T., Buus-Hinkler, J., Singha, S., Ribergaard, M. H., Rasmussen, T. S., and Kreiner, M. B.: Retrieving Sea Ice Information in the Pan-Arctic Region from Synthetic Aperture Radar, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18063, https://doi.org/10.5194/egusphere-egu24-18063, 2024.

14:15–14:25
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EGU24-17414
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On-site presentation
Sammy Metref, Maxime Ballarotta, Clément Ubelmann, Maxime Beauchamp, and Clément Busché

The SLICING (Sea Level Innovations and Collaborative Intercomparison for the Next-Generation products) project is a Copernicus Service Evolution project that responds to the evolving landscape of sea level processing. SLICING promotes a novel approach centered on open and collaborative data challenges for altimetric product developments and assessments. With a focus on fostering collaboration and methodological advancement, SLICING aligns with the objectives of the Copernicus Marine Service (CMEMS) and the overarching spirit of the European Digital Twin of the Ocean (DTO).

 

With the growing influence of artificial intelligence in oceanography and the advances of oceanographic observations, such as the new SWOT satellite, the surge in innovative methodologies and processing techniques is huge. However, these scattered efforts and the lack of generic and open comparisons is still a hindrance to reliably inform operational process chains. SLICING proposes a structured framework for the comparison of state-of-the-art methods and operational products to assess processing techniques and improve altimetry products. This framework not only aims to enhance the quality of observation and mapping processing for CMEMS but also provides a blueprint for the CMEMS Sea Level Thematic Assembly Centre evolution. By formulating altimetric processing problems as data challenges on collaborative platforms, SLICING attempts to provide a link between scientific innovation and operational implementation, addressing the gap between research and production. These challenges, rooted in rigorous software development practices, transcend mere method testing. They act as catalysts for collaboration, bringing together scientists around key operational altimetric processing issues.

 

In this presentation, we show examples of open comparisons for preprocessing the new SWOT data and mapping conventional altimetry. Through these examples, we offer a comprehensive overview of the strides made during the SLICING project, shedding light on advancements in sea level processing and the facilitation of collaborative data challenges. This overview can serve as a valuable exploration into the dos and don'ts that emerged from the project, offering insights into effective strategies for fostering collaborations and enhancing the quality of oceanographic products. By distilling the lessons learned, this broader perspective is intended to guide future initiatives, both within the CMEMS and in the broader context of the European DTO. Indeed, through shared problem formulation, evaluation metrics, and reproducible practices, the work carried out in the SLICING project exemplifies how the spirit of collaborative data challenges aligns with the DTO's vision of a unified digital platform.

 

How to cite: Metref, S., Ballarotta, M., Ubelmann, C., Beauchamp, M., and Busché, C.: Leveraging data challenges to enhance Copernicus Marine Service products and align with the future European Digital Twin of the Ocean., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17414, https://doi.org/10.5194/egusphere-egu24-17414, 2024.

14:25–14:35
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EGU24-6692
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Virtual presentation
Mehmet Ilicak, Diana Azevedo, Eric Jansen, Salvatore Causio, Leonardo Lima, Adil Sozer, Aljaz Maslo, Sergio Creti, Francesco Trotta, Giovanni Coppini, and Nadia Pinardi

The Black Sea Physical Analysis and Forecasting System (BSFS) operates within the Black Sea Monitoring and Forecasting Centre (BLK-MFC) as part of the Copernicus Marine Service (CMEMS). Here we present ongoing research and development activities for the future generations of the BSFS. The current system has the 1/40-degree horizontal grid NEMO ocean model featuring 121 vertical levels. Significant enhancements encompass the integration of biharmonic horizontal viscosity instead of the traditional Laplacian constant viscosity. This adaptation effectively mitigates small-scale grid noise, thereby elevating accuracy in representing mesoscale eddies.

A notable advancement includes the implementation of a two-way nested domain surrounding the Bosphorus Strait, employing the NEMO-AGRIF mesh refinement algorithm. This newly constructed high-resolution Bosphorus Strait domain has a 1/200-degree horizontal resolution, facilitating much better resolution of the strait's bathymetry.

Further refinements encompass recent developments targeting improvements in the model's eddy kinetic energy (EKE), relative vorticity fields, and minimized drift below the thermocline which is crucial for longer integration in a reanalysis scope. A concurrent effort involves the ongoing development of a new domain encompassing the Azov Sea, coupled with a sea-ice model. This initiative involves the utilization of different bulk formulas, enabling the incorporation of sea ice fluxes and AGRIF mesh refinement capabilities.

Testing of the enhanced domain configuration involves rigorous assessments aimed at validating the efficacy of these updates, ensuring a comprehensive evaluation of the system's performance.

How to cite: Ilicak, M., Azevedo, D., Jansen, E., Causio, S., Lima, L., Sozer, A., Maslo, A., Creti, S., Trotta, F., Coppini, G., and Pinardi, N.: Advancements in the Ongoing Development of the Black Sea Physical Analysis and Forecasting System, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-6692, https://doi.org/10.5194/egusphere-egu24-6692, 2024.

14:35–14:45
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EGU24-16783
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On-site presentation
Clement Bricaud, Jerome Chanut, Romain Bourdalle Badie, Mary Malicet, and Yann Drillet

In the framework of the Copernicus Marine Environment Monitoring Service, Mercator Ocean International operates a global high-resolution forecasting systems at the resolution of 1/12°. Increasing resolution appears necessary to improve the quality of service and to satisfy the users’ needs in the operational application (Le Traon, 2019). Resolving scales below 100 kilometers, and in particular sub mesoscale processes (1-50 km), appears to be essential to better represent the circulation in the open ocean (Chassignet, 2017), and, to improve the large-scale representations thanks to a more explicit energy transfers between finer and larger scales (Fox-Kemper Baylor, 2019). A deeper understanding of their various contributions (geostrophic flows, tidal motions, waves, inertial currents) and their role in the global ocean kinetic energy budget will improve the knowledge of these energy transfers between different scales.  

In 2019, it has been decided to go towards higher resolution and develop a new global sub mesoscale-permitting model. Benefiting from the context of the European H2020 IMMERSE project, a new 1/36° global configuration (2 to 3 km resolution), based on the NEMO 4.2 OGCM, has been developed. Thanks to the resolution increase, this model can resolve the Rossby radius in almost all open oceans areas at global scale quite everywhere and to span a large part of the internal wave spectrum. 

In 2022, a hierarchy of multi-year simulations at 1/4°, 1/12° and 1/36° resolution and with/without explicit tide representation has been performed: for each resolution, after a 3-years spin up without tidal forcing, 2 twin 3-years runs have been realized: one without tidal forcing and one forced by the 5 tidal components K1, O1, S2, M2, N2. These models are driven at the surface by the 8km/1hour ECMWF IFS system. Atmospheric pressure forcing has been activated. 

In 2023, in the framework of the EDITO-Model Lab project, the development of a near real-time demonstrator has been started. The system is based on the new 1/36° global configuration and constrained by a spectral nudging to the CMEMS/MOI global 1/12° real-time system (for temperature , salinity , horizontal velocities and  sea ice concentration).

We propose a first evaluation of the benefits due to the resolution increase and tidal forcing. Circulation, energy, tidal representation and mixing of the experiments are compared to each other’s. 

How to cite: Bricaud, C., Chanut, J., Bourdalle Badie, R., Malicet, M., and Drillet, Y.: Development of a near real-time demonstrator based on a very high-resolution global ocean model, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16783, https://doi.org/10.5194/egusphere-egu24-16783, 2024.

14:45–14:55
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EGU24-7146
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ECS
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On-site presentation
Shun Ohishi, Takemasa Miyoshi, and Misako Kachi

Various ocean analysis products have been produced and used for geoscience research. In the Pacific region, there are four high-resolution regional analysis datasets [JCOPE2M (Miyazawa et al. 2017) and FRA-ROMS II (Kuroda et al. 2017) with 3D-VAR; NPR-4DVAR (Hirose et al. 2019) with 4D-VAR; and DREAMS with a Kalman filter (Hirose et al. 2013)], but there are no EnKF-based analysis datasets to the best of the authors’ knowledge.

Recently geostationary satellites such as Himawari-8 and -9 have been providing sea surface temperatures (SSTs) at high spatiotemporal resolution. To use these data effectively, we have developed an eddy-permitting EnKF-based ocean data assimilation system at horizontal resolution of 0.25° with a short assimilation interval of 1 day and demonstrated that the combination of three schemes [incremental analysis update (IAU; Bloom et al. 1996), relaxation-to-prior perturbation (RTPP; Zhang et al. 2004), and adaptive observation error inflation (AOEI; Minamide and Zhang 2017)] significantly improved dynamical balance and analysis accuracy (Ohishi et al. 2022a, b). With the recent enhancement of computational resources, we have developed higher-resolution eddy-resolving ocean data assimilation systems at horizontal resolution of 0.1° and produced ensemble analysis products for the western North Pacific (WNP) and Maritime Continent (MC) regions called the LETKF-based Ocean Research Analysis (LORA)-WNP and -MC, respectively (Ohishi et al. 2023). The validation results show that the LORA has sufficient accuracy for geoscience research and various applications such as fisheries and marine transport. Since March 2023, the LORA-WNP and -MC have been released at JAXA-RIKEN Ocean Analysis website (https://www.eorc.jaxa.jp/ptree/LORA/index.html).

How to cite: Ohishi, S., Miyoshi, T., and Kachi, M.: LETKF-based Ocean Research Analysis (LORA): A new ensemble ocean analysis dataset, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7146, https://doi.org/10.5194/egusphere-egu24-7146, 2024.

A coastal & green ocean
14:55–15:05
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EGU24-5334
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ECS
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On-site presentation
Marie Montero, Hubert Loisel, Daniel S.F Jorge, Marine Bretagnon, Julien Demaria, Aurélien Prat, Ana Gabriela Bonelli, Lucile Duforêt-Gaurier, and Antoine Mangin

Carbon monitoring from space is critical for the reporting and verification of carbon stocks and changes in both coastal and open ocean waters. In the frame of the OCROC project, funded by the Copernicus 2 – 1st Service Evolution Call for Tenders (2022-2024), we focus on the particulate (POC) and dissolved (DOC) organic carbon of surface oceanic and coastal waters, which represent the two components of the total organic carbon (TOC) pool in the ocean. The present presentation is mainly dedicated to the estimation of DOC, the main contributor to TOC, over open ocean waters. An enhanced version of the Ocean and Land Color Instrument's (OLCI) DOC algorithm of Bonelli et al. (2022) is presented and adapted to historical and present ocean color sensors. This algorithm employs two different Artificial Neural Network (ANN) algorithms depending on the Optical Water Classes, and four input parameters namely the absorption coefficient of Colored Dissolved Organic Matter (acdom(443)) chlorophyll-a concentration (Chl-α),  Sea Surface Temperature (SST), and Mixed Layer Depth (MLD). In this new version of the algorithm SST and MLD are both delivered by COPERNICUS (Multi Observation Global Ocean ARMOR3D L4 analysis and multi-year reprocessing).  Each of the four input parameters is provided at a distinct time lag to enhance the accuracy of the model. Furthermore, a revisited “match-up” database, compared to the one used in Bonelli et al. (2022), is utilized to validate the algorithm across multiple ocean color missions.

How to cite: Montero, M., Loisel, H., Jorge, D. S. F., Bretagnon, M., Demaria, J., Prat, A., Bonelli, A. G., Duforêt-Gaurier, L., and Mangin, A.: Estimates of the dissolved organic carbon concertation from remote sensing in the frame of the OCROC project., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5334, https://doi.org/10.5194/egusphere-egu24-5334, 2024.

15:05–15:15
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EGU24-380
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ECS
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On-site presentation
Gabriela Martinez Balbontin, Julien Jouanno, and Rachid Benshila

Accurate biogeochemical forecasting of the oceans is crucial for ecosystem and fisheries management. In this study, we propose a methodology for chlorophyll forecasting at a seasonal scale by leveraging physical ocean forecasts and autoencoders, a type of convolutional neural network. Chlorophyll-a is a key indicator of phytoplankton biomass, and it offers the advantage of being relatively easy to measure at a large scale using satellite-based color sensors. Specifically, this approach focuses on estimating surface chlorophyll concentrations in the Tropical Atlantic from forecasted physical properties of the ocean: sea surface temperature and salinity, sea surface height, and mixed layer depth. 

The proposed method is trained on the GlobColour dataset, a cloud-free, merged chlorophyll concentration output from various sensors, from 1998 to 2009. Seven-month forecasts are performed for the period 2010–2020, with monthly initialization. We show that we can skillfully integrate data from the ECMWF’s long-range forecasting system, SEAS5, to predict multiannual and seasonal chlorophyll levels. Evaluation against 2010–2020 GlobColour data demonstrates the autoencoder’s skill in capturing spatial and temporal patterns. Seasonal performance was assessed for regions of interest, including the Equatorial and Senegal-Mauritania upwelling regions, the Inter-Tropical Convergence Zone (ITCZ), and the Northern Atlantic. The neural network consistently outperforms the biogeochemical reanalysis of reference in measured skill and has the additional advantage of being less resource-intensive than traditional models. 

These results further confirm the potential of deep-learning techniques in operational oceanographic applications. Future work will focus on expanding this approach to generating global-scale, multi-nutrient forecasts in the context of the European Digital Ocean Twin (EDITO) project, which aims to provide an environment to exploit this type of machine-learning based simulation algorithms. 

How to cite: Martinez Balbontin, G., Jouanno, J., and Benshila, R.: Deep-Learning Based Seasonal Chlorophyll Forecasting in the Tropical Atlantic , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-380, https://doi.org/10.5194/egusphere-egu24-380, 2024.

15:15–15:25
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EGU24-20729
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ECS
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On-site presentation
Carolina Amadio, Anna Teruzzi, Gloria Pietropolli, Luca Manzoni, Gianluca Coidessa, and Gianpiero Cossarini

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

How to cite: Amadio, C., Teruzzi, A., Pietropolli, G., Manzoni, L., Coidessa, G., and Cossarini, G.: Combining Neural Networks and Data Assimilation to enhance the spatial impact of Argo floats in the Copernicus Mediterranean biogeochemical model, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20729, https://doi.org/10.5194/egusphere-egu24-20729, 2024.

15:25–15:35
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EGU24-1338
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Virtual presentation
Olivier Titaud, Anna Conchon, Laurène Mérillet, Sarah Albernhe, and Héloïse Magliano

Since mid-2019, meso-zooplankton and micronekton reanalyses (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. Now MICRORYS products use a global configuration of SEAPODYM at 1/12° daily resolution. This product has evolved considerably since the first delivery. We propose here to review the state of the art of this product. Some case studies and the developments that are expected soon, especially those concerning a new computational grid that bypasses the problem at the poles will be presented.

How to cite: Titaud, O., Conchon, A., Mérillet, L., Albernhe, S., and Magliano, H.: Zooplankton and Micronekton products from the Copernicus Marine Service catalogue: state of the current product and development plan, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1338, https://doi.org/10.5194/egusphere-egu24-1338, 2024.

15:35–15:45
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EGU24-12551
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ECS
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On-site presentation
Manuel Garcia-Leon, Lotfi Aouf, José María García-Valdecasas, Alice Dalphinet, Juan Asensio, Roland Aznar, José María Terrés, Tania López Pérez, and Marcos G Sotillo

Coastal stakeholders are adding ocean forecasts in their daily operations. The Copernicus Marine Service - Monitoring and Forecasting Centres (CMS - MFCs) are evolving to meet these user new demands. For instance, the wave forecast service at the Iberian-Biscay-Ireland area (IBI-WAV) is being upgraded with increases in model resolution (from 1/20º to 1/40º) and the delivery of new variables (e.g. maximum wave height). 

Enhancing coastal forcings (winds and surface currents) reinforces these forthcoming upgrades. Higher model resolution benefits local-scale phenomena representation (i.e. wind wave growth or wave refraction due to currents), but errors in the forcings may degrade the expected performance. The Copernicus Marine Service Evolution project KAILANI (2022-2024) aims to improve the accuracy of these operational forcings by correcting them with Artificial Neural Networks (ANNs). These ANNs are fed with remote sensing data as target datasets, allowing to predict complex spatial patterns by using the same forcings as predictors.

Three pilot sites have been selected to develop this methodology: (i) the Galician area (NE-Atlantic, macrotidal), (ii) the Canary Islands (NE-Atlantic, mesotidal) and (iii) the Ebro Delta (NW Mediterranean, microtidal).

The ANN for coastal winds has been trained with Satellite Synthetic Aperture Radar (SAR; data from the ESA Sentinel-1 mission). Due to the nature of the data (i.e. good spatial coverage, but with revisit times up to several days), the ANN architecture consists of a Generative Adversarial Network (GAN) that uses Convolutional layers for addressing the spatial dimension. The ANN is able to downscale ECMWF-IFS wind fields from 1/10º to 1/40º resolution, adding spatial features learnt a priori from SAR data. The ANN-predicted winds present lower speed bias (up to 30% in specific areas) and RMSD (up to 10%) than original ECMWF-IFS winds.  

Surface currents are predicted with ANNs based on Autoencoders (AE), using hourly-averaged HF-Radar data as target dataset (retrieved from Copernicus Marine In-Situ TAC). Spatial and time dimension are addressed with Convolutional and Long Short-term Memory (LSTM) layers, respectively. The input data includes (i) IBI-PHY currents and (ii) atmospheric forcings from ECMWF-IFS. The AE improves error metrics respect IBI-PHY, showing speed and directional biases close to 2 cm/s and 7º (achieving bias decreases of 45% and 60% in some areas, respectively).

These ANN-driven wind and currents forcings will be used in pre-operational tests by the IBI-WAV service. If successful, this methodology could be transferred into operations of the IBI NRT wave forecast system, as well as to be extended in other CMS regional MFCs. 

How to cite: Garcia-Leon, M., Aouf, L., García-Valdecasas, J. M., Dalphinet, A., Asensio, J., Aznar, R., Terrés, J. M., López Pérez, T., and G Sotillo, M.: Enhancement of coastal winds and surface ocean currents with deep learning – The Copernicus Marine Service Evolution KAILANI project, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12551, https://doi.org/10.5194/egusphere-egu24-12551, 2024.

Posters on site: Mon, 15 Apr, 10:45–12:30 | Hall X4

Display time: Mon, 15 Apr, 08:30–Mon, 15 Apr, 12:30
Chairpersons: Stephanie Guinehut, Julien Brajard, Anna Teruzzi
Copernicus Marine at the core
X4.10
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EGU24-16173
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ECS
Valentina Giunta, Corinne Derval, Laurence Crosnier, and Muriel Lux

The Copernicus Marine Service is one of the six pillar services of the Copernicus program. It follows a user-driven process by taking into consideration user feedback to consistently improve its portfolio of products and services. Mercator Ocean International (here MOi) is entrusted by the European Union to implement the Copernicus Marine Service over the 2021-2027 period. Consequently, MOi is maintaining a permanent dialogue with users to collect their requirements and support them in the use of the service. Public Core users, such as policy stakeholders and regional sea conventions, are the main target, but Copernicus Marine Service is open to all communities (Core and non-Core users). Thus, MOi manages and analyses feedback from all users on the current service and their requirements for the service evolution. The user feedback process is dynamic and constantly evolving to target specific audiences and expertise. Currently, user needs are being collected through diverse channels and sources, such as through the User Support team, but also through training and surveys. To plan the service evolution, feedback from groups with specific expertise is needed to help fill the gap in what is being offered and to improve the data quality. As an example of these target audiences, the Champion User Advisory Group (CUAG), formed by active users of Copernicus Marine Service, and the National Marine Stakeholders Group, formed by member states, were consolidated. These groups allow regular interactions and communication among expert users and policymakers, which have been proven to be resourceful sources of feedback that help towards better services and data products. Among the main needs expressed by users, increasing spatial and temporal resolution of global models and reanalysis products, having longer ocean forecasts, and improving quality data are the top priorities.  With the added value of feasibility studies, these inputs are considered and evaluated internally and discussed with the producer's centers to ensure that the planned roadmap is aligned with the user requirements. Additionally, knowledge gaps and cutting-edge scientific developments are identified to plan the service evolution activities in the short, intermediate, and long term to better serve marine policy implementation and scientific research. In conclusion, the goal of this user-driven approach is to give Copernicus Marine Service the capacity to effectively answer users’ needs on ocean monitoring and forecasting at European and global levels. 

How to cite: Giunta, V., Derval, C., Crosnier, L., and Lux, M.: Designing and delivering user-driven products and services through Copernicus Marine Service , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16173, https://doi.org/10.5194/egusphere-egu24-16173, 2024.

X4.11
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EGU24-15653
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Claire Gourcuff, Alan Berry, Fiona Carse, Dimitris Kassis, Birgit Klein, Kjell Arne Mork, Giulio Notarstefano, Violeta Slabakova, Colin Stedmon, Andreas Sterl, Virginie Thierry, Laura Tuomi, Pedro Velez, Waldemar Walczowski, and Simo-Matti Siiriä

The Argo Programme is a major component of both the Global Ocean Observing System (GOOS) and the Global Climate Observing System (GCOS), providing near-real time data for ocean and atmospheric services and high-quality data for climate research. Although originally designed to provide temperature and salinity profiles in the upper 2 km of the ice-free ocean, the array has been expanded into seasonal ice zones. In addition, regional pilot programmes have demonstrated that some Argo floats can now measure biogeochemical parameters to address oceanic uptake of carbon, acidification, and deoxygenation (BioGeoChemical, BGC-Argo) and some floats are also able to make measurements throughout the water column down to 6000 m depth (Deep-Argo). These new BGC-Argo and Deep-Argo Missions, together with the initial Core-Argo Mission form the new global, full-depth and multidisciplinary OneArgo programme (Roemmich et al. 2019).

Euro-Argo aims at maintaining ¼ of the global OneArgo array, with a regional perspective focusing on European marginal seas (Mediterranean, Black and Baltic seas) and the European part of the Arctic seas.

The Euro-Argo strategy focuses on providing sustained high quality oceanic data to the scientific community for better understanding of the role of the Ocean in the Earth’s climate. Addressing issues of climate change along with expanding floats’ capabilities and coverage are at the centre of the Euro-Argo strategy. Another domain of grand challenges is related to the health of the oceanic ecosystem and its impacts on society. The recent technological advances in biogeochemical instrumentation on Argo floats have greatly improved the ability to address ecosystem monitoring, and gather data in the European marine areas to support climate and biodiversity policies set up by the European Union. Moreover, Argo is a major source of information for operational centres such as the Copernicus Marine and Climate Services and the European Centre for Medium-Range Weather Forecasts (ECMWF) in Europe, for the provision of ocean and weather forecasts and seasonal predictions. Euro-Argo supports the enhancement of monitoring and observing systems at regional scales for model-assimilation and model-validation purposes. In particular, the extensions of Argo into the deep ocean and ecosystem parameters offer new possibilities and will help to constrain and improve the models and resulting products.

Within this context, Euro-Argo is currently revising its deployment and coverage strategy for the next decade, taking into consideration specific European needs in terms of in situ ocean observations, while contributing to the global OneArgo new ambitious design.

We will present this strategy and provide some highlights on the challenges for the years to come.

How to cite: Gourcuff, C., Berry, A., Carse, F., Kassis, D., Klein, B., Mork, K. A., Notarstefano, G., Slabakova, V., Stedmon, C., Sterl, A., Thierry, V., Tuomi, L., Velez, P., Walczowski, W., and Siiriä, S.-M.: European contribution to the OneArgo array, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15653, https://doi.org/10.5194/egusphere-egu24-15653, 2024.

A blue & white ocean
X4.12
|
EGU24-19810
Ioanna Karagali, Magnus Barfod Suhr, Pia Nielsen-Englyst, Wiebke Kolbe, and Jacob Høyer

Satellite missions carrying Thermal Infrared (TIR) and Passive Microwave Sensors (PMW) allow for high-resolution Sea Surface Temperature (SST) and Sea-Ice Surface Temperature (IST) retrievals under clear skies (TIR) and all weather retrievals (PMW) albeit with coarser resolution. This allows the continuous provision of SST and IST to operational Numerical Weather Prediction systems, climate models and to the wider scientific community. DMI is a Production Unit (PU) for the Sea Ice (SI) and SST Thematic Assembly Centers (TAC) of the Copernicus Marine Monitoring Service (CMS) providing a suite of level 4 SST products for the Arctic Ocean, the Baltic and North Sea daily, hourly and as multi-year products.

The L4 Near-Real-Time (NRT) SST product SST-BAL-SST-L4-NRT-OBSERVATIONS-010-007-b is a daily, multi-sensor, gap-free, optimally interpolated product derived from night-time SST retrievals at high resolution (0.02o), available from 2016 onward. The L4 Multi-Year SST product SST-BAL-SST-L4-REP-OBSERVATIONS-010-016 is a daily, multi-sensor, level 4 optimally interpolated product using infra-red satellite observations from the ESA CCI and Copernicus C3S projects and high resolution sea ice information from SMHI and the SI TAC available from 1982 to 2022. The L4 Near-Real-Time Diurnal SST product SST-BAL-PHY-SUBSKIN-L4-NRT-010-034 is an hourly, gap-free satellite sub-skin SST analysis using L2P and L3 single-sensor SST data as input.

For the Arctic Ocean, the L4 NRT SST/IST product ARC-SEAICE-L4-NRT-011-008 is a daily, multi-sensor, gap-free and optimally interpolated analysis of sea surface and sea-ice surface temperatures at a resolution of 0.05o extending north of 58 oN and available from 2018 onwards. The corresponding MY product, ARC-SEAICE-L4-NRT-011-016, is the first combined SST and IST analysis of the Arctic available from 1982 and up to 2023.

Within the current C3S portfolio, DMI will provide the SST ECV, i.e. a global (up to 90o latitude), sub-skin product (20 cm) with a 0.05o spatial resolution. The aim of the present study is to provide an overview of the available products and their performance along with insights on future developments and products.

How to cite: Karagali, I., Barfod Suhr, M., Nielsen-Englyst, P., Kolbe, W., and Høyer, J.: Arctic Ocean, North and Baltic Sea GHRSST-compliant SST and IST products for the Copernicus Marine Service, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19810, https://doi.org/10.5194/egusphere-egu24-19810, 2024.

X4.13
|
EGU24-18271
Till Rasmussen, Mads Hvid Ribergaard, and Imke Sievers

The maritime industry continues to expand in the waters around Greenland. Apart from fisheries, which by far is the most important income for Greenland, another important element is transportation of goods and tourist, which in many locations are dependent on the conditions at sea. During the last two winters (2022 and 2023) severe sea ice conditions have been seen in Disko Bay. Especially in 2022, there were discussions on whether or not to fly in supplies instead of using the usual transportation on the ocean. A trustworthy high-resolution forecast of ocean and sea ice conditions could have remedied this decision.

Currently automated retrievals of observations from remote sensing and forecast model are doing a reasonable job when describing the current conditions and forecasting the short-term offshore conditions, however users are often interested in near shore coastal areas, where resolution matters. The near coastal environment is often not well resolved in Arctic/global models forecast models.

This study aim at developing a high-resolution (sub kilometer scale) operational coastal marine forecasting system built on the shoulders of already existing Copernicus services for the area of Disko Bay on the west coast of Greenland. In combination with already, existing products such as automated and manual ice charts it will improve the warning system for the area. A side effect is that the ice service will produce more frequent ice charts for Disko Bay, which will benefit the existing Copernicus Marine Service.

The seamless physical downscaling from the Copernicus Marine Services system to the near coastal area in Disko Bay will utilize boundary conditions from the Arctic Marine forecasting system. The system will be forced by a high-resolution none hydrostatic atmospheric forecast from the Danish Meteorological Institute at 2½km resolution. The study is funded by the Copernicus user demonstration program named “COP-INNO-USER”.

This presentation will focus on the developments within the service, benefits and challenges. It will also discuss how to integrate the results into operations at the Danish Meteorological Institute.

 

How to cite: Rasmussen, T., Hvid Ribergaard, M., and Sievers, I.: Disko Bay ocean and sea ice forecast, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18271, https://doi.org/10.5194/egusphere-egu24-18271, 2024.

X4.14
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EGU24-15360
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ECS
Ida Margrethe Ringgaard

A regional reanalysis is like a good local restaurant: it builds on local knowledge and focus is on local specialities. For the Baltic Sea, one of the most important local ‘specialities’, or features, is the gateway: the narrow and shallow Danish Straits where the salty North Sea water mass meets with the fresh Baltic Sea water. If this very important process of inflow of saline and oxygen-rich water from the North Sea into the Baltic Sea is not modelled correctly, the results will be of insufficient quality, and not represent the ocean accurately. Currently, global ocean models cannot run with sufficiently high resolution, nor do they focus on local features required to simulate the Baltic Sea adequately. This requires a regional ocean model. Here we present the CMEMS high-resolution ocean reanalysis for the Baltic Sea covering the 30 year period 1993 to 2023. The reanalysis consists of the physical state as well as the bio-geo-chemical state and the waves. Preliminary results from 2 on-going tasks will also be presented: 1) extending the reanalysis back in time to 1980 and 2) expanding the data assimilation from the present parameters (SST and in-situ temperature and salinity profiles) to include sea ice concentration, nutrients and oxygen.

How to cite: Ringgaard, I. M.: Baltic Sea reanalysis from Copernicus Marine Service – soaked in local knowledge, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15360, https://doi.org/10.5194/egusphere-egu24-15360, 2024.

X4.15
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EGU24-21102
Annabelle Ollivier, Patricia Zunino, Romain Husson, Adrien Nigou, Alexandre Philip, and Gerald Dibarboure

In the frame of the second phase of the Copernicus Marine Service, starting in 2022, the WAVE Thematic Assembly Centre (TAC), a partnership between CLS and CNES, is responsible for the provision of a near-real-time wave service that started in July 2017. Near-real-time wave products derived from altimetry and SAR measurements are processed and distributed onto the Copernicus Marine Service catalogue.

This presentation will describe the existing products – along-track Level 3 and gridded Level 4 – and their applications such as near-real-time assimilation in wave forecasting systems, validation of wave hindcasts, etc.

In 2023, nadir data from SWOT mission and S6 were added to the constellation, enlarging the number of missions and techniques proposed in this TAC.

R&D work with internal users show that improving nadir data resolution near cost to 5Hz data enlarge the observability of coastal zones and high variability areas.

The product quality from CFOSAT mission dedicated to wave observation get better and better, with non wave signal filtering and a wider observability of wavelength between 30m and 1000m.

Working on the complementarity of observation between the different missions, Sentinel1, altimetry, CFOSAT and now SWOT appears as the new challenge.

The gridded Level-4 SWH and Spectral product directly benefit from the merging of information for NRT products.

How to cite: Ollivier, A., Zunino, P., Husson, R., Nigou, A., Philip, A., and Dibarboure, G.: Improved product quality in WAVE-TAC Copernicus Marine Service, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-21102, https://doi.org/10.5194/egusphere-egu24-21102, 2024.

X4.16
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EGU24-5332
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ECS
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Konstantinos Kampouris and Gerasimos Korres

An ensemble wave prediction system (EPS) at a 1/16o grid horizontal resolution is being developed for the Mediterranean Sea, based on the WAM Cycle 6 wave model implementation. Open boundary conditions are provided by a North Atlantic wave model at 1/6o resolution. Uncertainty is forced in the Med-waves EPS (in both the Mediterranean and the North Atlantic wave models), through a reduced size ensemble of 10m winds provided from the ECMWF atmospheric EPS (50 members + 1 control run) at approximately 18 km spatial resolution with a forecast horizon of 10 days ahead. The nominal ECMWF EPS ensemble size (50 ensemble + 1 control members) is reduced to 23+1 members using clustering techniques (k-means method). The Mediterranean 10-day ensemble wave forecasts are verified for a 6-month period (Jan-Jun 2022) against available satellite and wave buoys observations, as well as reference cases, like the forecast of the NRT Med-waves of the Copernicus Marine Service. A variety of both deterministic and probabilistic metrics are used in the verification process, in order to access as many forecast quality attributes as possible and to best determine the performance of the EPS. In general, the wave EPS shows a good forecast skill, which after the first 3-4 forecast days becomes even better than the skill of the deterministic Med-waves Copernicus Marine forecast system, indicating the importance of the ensemble approach as the forecast ranges increase.

How to cite: Kampouris, K. and Korres, G.: A wave ensemble prediction system for the Mediterranean Sea, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5332, https://doi.org/10.5194/egusphere-egu24-5332, 2024.

X4.17
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EGU24-18710
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ECS
Charikleia L.G. Oikonomou and Gerasimos Korres

The Med-WAV system of the Mediterranean component (MED MFC) of the Copernicus Marine Environment Service has consistently been providing high-resolution wave product analyses, forecasts, and reanalyses. Accurately predicting wave parameters, particularly during storms, is crucial for ensuring maritime safety, the resilience of offshore structures, and managing coastal hazards. Consequently, since November 2023, the Mediterranean Sea Waves Analysis and Forecast product (MEDSEA_ANALYSISFORECAST_WAV_006_017, Korres et al., 2023) has been delivering estimates of the maximum crest-to-trough height, utilising the methodology proposed by Benetazzo et al. (2021). The system's ability to represent short-term maximum wave statistics is assessed through a comprehensive evaluation against buoys positioned in the western part of the basin, accessible via Copernicus Marine in-situ TAC (2023) (product INSITU_GLO_WAV_DISCRETE_MY_013_045). The results confirm that the operational system adeptly estimates maximum wave height over the Mediterranean Sea in accordance with the quality metrics identified in previous literature.

References

Korres, G., Oikonomou, C., Denaxa, D., & Sotiropoulou, M. (2023). Mediterranean Sea Waves Analysis and Forecast (Copernicus Marine Service MED-Waves, MEDWAΜ4 system) (Version 1) [Data set]. Copernicus Marine Service (CMS). https://doi.org/10.25423/CMCC/MEDSEA_ANALYSISFORECAST_WAV_006_017_MEDWAM4

Benetazzo A., Barbariol F., Pezzutto P., Staneva J., Behrens A., Davison S., Bergamasco F., Sclavo M. and Cavaleri L. (2021). Towards a unified framework for extreme sea waves from spectral models: rationale and applications. Ocean Eng. 219, 108263. https://doi.org/10.1016/j.oceaneng.2020.108263

Copernicus Marine in situ TAC (2023). Copernicus Marine In Situ - Global Ocean Wave Observations Reanalysis. SEANOE. https://doi.org/10.17882/70345

How to cite: Oikonomou, C. L. G. and Korres, G.: Near-real-time maximum wave height estimates over the Mediterranean Sea, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18710, https://doi.org/10.5194/egusphere-egu24-18710, 2024.

X4.18
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EGU24-10659
Eric de Boisseson, Hao Zuo, Marcin Chrust, Philip Browne, Magdalena Balmaseda, and Patricia de Rosnay

Ocean and sea-ice reanalyses are reconstructions of historical ocean and sea-ice states by ingesting observations into simulated model states through data assimilation methods. Reanalysis provides invaluable information for climate monitoring and is an essential component in long-term prediction such as seasonal to decadal forecasts. The Ocean ReAnalysis System-6 (ORAS6) is the 6th generation of ocean and sea-ice reanalysis system developed at ECMWF. ORAS6 is forced by hourly ERA5 atmospheric fields and uses an ensemble variational ocean data assimilation (EDA) to produce an 11-member ensemble of ocean reanalyses. Both the new EDA system and the use of the latest reprocessed input datasets help making better use of ocean observations to provide ocean states with improved fit to observations both at the surface and the subsurface, a better representation of the daily cycle of the surface temperature and more accurate ocean transports. ORAS6 sea-ice states are produced using a new multi-category sea ice model assimilating sea-ice concentration observations and show improved fit to satellite observations. This increased complexity came with its lot of technical challenges but now opens the door for the future assimilation of new sea-ice variables such as sea-ice thickness and new diagnostics such as snow depth over sea-ice that will benefit from future satellite missions.

Ocean and sea-ice states from ORAS6 will be used to initialise the ocean component of the ECMWF operational coupled ensemble forecasts and provide the lower boundary conditions for the upcoming ERA6 atmospheric reanalysis produced by the Copernicus Climate Change Service (C3S). This presentation will feature results from the first stream of production of ORAS6 covering the most recent decade as well as a preview of ORAS6 streams covering the rest of the satellite-observed decades as well as the pre-satellite period with a focus on performance evaluation against the current ECMWF operational system-5 (ORAS5).

How to cite: de Boisseson, E., Zuo, H., Chrust, M., Browne, P., Balmaseda, M., and de Rosnay, P.: ECMWF 6th generation ocean and sea-ice reanalysis system (ORAS6), EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10659, https://doi.org/10.5194/egusphere-egu24-10659, 2024.

A coastal & green ocean
X4.19
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EGU24-15466
Janne-Markus Rintala, Socratis Loucaides, Matt Mowlem, Laurent Coppola, Leymarie Edouard, Ute Schuster, Meike Becker, Juanjo Dañobeitia, Nadine Lanteri, Richard Sanders, Tommi Männistö, Laura Sinikallio, Katri Ahlgren, Yann-Hervé de Roeck, and Kutsch Kutsch and the GEORGE-Project

The ocean observing research infrastructures (RIs) in Europe (i.e. ICOS, EMSO, Euro-Argo) have successfully implemented a world-leading system of standardised Ocean observations over the past 15 years, building on more than a century of experiences by the involved marine institutes. This community has joined forces in the GEORGE project to take their observation to the next level of technology: GEORGE aims to develop an already existing observations network with novel state-of-the-art biogeochemical, multi-platform observing system operated across ERICs that can carry out integrated biogeochemical observations for characterisation of the Ocean carbon system. We have brought together 28 partners from leading European ocean-observing technology developers, academia, and the observing community. In addition to improving the measurement technologies of the existing RI’s, GEORGE will also streamline data treatment, e.g., quality control and the data flow to repositories, as well as adopt the novel methods developed for knowledge sharing to endorse rigorous learning without boundaries to ensure the sustainability of future ocean observations.

How to cite: Rintala, J.-M., Loucaides, S., Mowlem, M., Coppola, L., Edouard, L., Schuster, U., Becker, M., Dañobeitia, J., Lanteri, N., Sanders, R., Männistö, T., Sinikallio, L., Ahlgren, K., de Roeck, Y.-H., and Kutsch, K. and the GEORGE-Project: GEORGE-project provides next-generation multiplatform ocean observing technologies for RIs, a joint data flow from the sea bed to the surface ocean, and applies novel tools for knowledge sharing., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15466, https://doi.org/10.5194/egusphere-egu24-15466, 2024.

X4.20
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EGU24-17473
Antoine Mangin, Quentin Jutard, Aurélien Prat, Julien Demaria, and Marine Bretagnon

Since 1997, remote sensing of the ocean colour has routinely documented ecosystems health and productivity on a global scale. Therefore, these observations, especially chlorophyll-a concentration, are particularly important not only for the management of living marine resources but also for climate studies as the ocean might act as a sink or a source of carbon for the atmosphere. In such a context, reliable evaluations of trends, whether seasonal, annual, or especially interannual variations, are critical.

There are several products of surface chlorophyll concentrations derived from ocean colour sensing available through the Copernicus Marine Service. Some of them are more adapted to specific regional seas and use adapted algorithms for chlorophyll retrieval. There also exist chlorophyll products at global scale that are built with different assumptions each of them aiming at building the best time series (from 1997 up to now) for climate analysis. Moreover, some products offer uncertainty estimates and/or quality indicators that are useful for trend computations. We will present an intercomparison of trend evaluations made with these different products at different time scales (annual and interannual). Differences will be commented on and explained.

How to cite: Mangin, A., Jutard, Q., Prat, A., Demaria, J., and Bretagnon, M.: Evaluation of annual and interannual trends of marine Chlorophyll concentration, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17473, https://doi.org/10.5194/egusphere-egu24-17473, 2024.

X4.21
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EGU24-20382
Hongyan Xi, Marine Bretagnon, Julien Demaria, Antoine Mangin, and Astrid Bracher

In the framework of Copernicus Marine Service Evolution Program, our project GLOPHYTS aims at establishing a complete and systematic approach for a consistent long-term monitoring of surface ocean phytoplankton function types (PFTs) on global scale. The current global PFT products available on CMEMS are generated based on remote sensing reflectance from multi-sensor merged and Sentinel-3 OLCI data and OSTIA sea surface temperature product, using a set of empirical-orthogonal-function based PFT algorithms that were previously developed and recently updated within GLOPHYTS. These products provide global chlorophyll a data with per-pixel uncertainty for five PFTs spanning from 2002 until today. A correction and merging scheme has been applied to these PFT data sets of different sensors to generate long-term consistent satellite PFT products, which are expected to act as potentially important ocean monitoring indicators (OMI). In providing inter-annual variation and trend analyses of the surface phytoplankton community structure, the OMI is likely to help in the assessment of the ocean health. In the context of this study, we present the PFT time series on global scale and for some key regions, e.g.  the Arctic Ocean. For the latter, we will also show the perspective of improving PFT estimations using machine learning techniques. The proposed improved Arctic PFT products can supplement the current ocean colour data sets for the Arctic Ocean in the Copernicus Marine Service.

How to cite: Xi, H., Bretagnon, M., Demaria, J., Mangin, A., and Bracher, A.: Time series of major phytoplankton functional types serving as an Ocean Monitoring Indicator (OMI) for Copernicus Marine Service  , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20382, https://doi.org/10.5194/egusphere-egu24-20382, 2024.

X4.22
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EGU24-18174
Dimitry van der Zande, Aida Alvera-Azcárate, Joppe Massant, and Kerstin Stelzer

High-quality satellite-based ocean colour products can provide valuable support and insights in the management and monitoring of coastal ecosystems. Today’s availability of Earth Observation (EO) data is unprecedented including traditional medium resolution ocean colour systems (e.g. Sentinel-3/OLCI) and high-resolution land sensors (e.g. Sentinel-2/MSI). Each of these sensors offers specific advantages in terms of spatial, temporal or radiometric characteristics, enabling the provision of different types of ocean colour products. This is also reflected in the portfolio of the Copernicus Marine service providing a number of different OC products to support different types of end users. While “traditional” ocean colour sensors like Sentinel-3 OLCI provide daily temporal resolution, the sensors onboard these satellites do not measure at the necessary high spatial resolution to resolve complex coastal dynamics. High spatial resolution sensors, like MSI onboard Sentinel-2 (10m - 60m resolution), are able to resolve these small scales, but their temporal revisit time is far from optimal (about 5 days considering the Sentinel-2 A & B constellation). Additionally, both high spatial resolution datasets and traditional ones are hindered by the presence of clouds, resulting in a large amount of missing data.

Given the high complementarity of these two measurement strategies, we present a methodology to derive daily cloud-free multi-resolution ocean colour products from the synergistic use of Sentinel-2 and Sentinel-3 data by applying DINEOF (Data Interpolating Empirical Orthogonal Functions). A key processing step in the gap-filling procedure is the harmonization between the ocean colour products (e.g. chlorophyll-a concentration -CHL-, Turbidity -TUR-) between the Sentinel-2/MSI and Sentinel-3/OLCI sensor. Due to differences between the sensors regarding spectral band sets and viewing geometry, CHL algorithms used for Sentinel-3/OLCI cannot be directly transferred to Sentinel-2/MSI resulting in the chlorophyll-a products often having diverging values between both sensors. To increase the coherency between the Sentinel-2/MSI and Sentinel-3/OLCI CHL products, a machine learning technique (LightGBM) was used to transfer the more complex CHL algorithms (e.g. band ratio algorithms, switching algorithms, other machine learning algorithms) from Sentinel-3/OLCI to Sentinel-2/MSI. Subsequently, DINEOF is used to generate the daily multi-resolution products by using the daily OLCI products to support gap-filling in the high-resolution 5-daily coastal products and retaining the high spatial resolution of Sentinel-2/MSI data and the high temporal resolution of OLCI data in the final product.

The machine learning and multi-resolution gap-filling approach will be demonstrated and validated in different regions (e.g. North Sea, North Adriatic Sea) to ensure suitability of the approach for integration into the operational high resolution COPERNICUS Marine Service. An analysis of TUR and CHL daily products at 100m resolution will be presented, alongside an analysis of the spatial and temporal scales retained by the approach. This work was performed in the Copernicus Marine Service Evolution Project MultiRes (21036-COP-INNO-SCI)

How to cite: van der Zande, D., Alvera-Azcárate, A., Massant, J., and Stelzer, K.: Multi-Resolution Ocean Color roducts to support the Copernicus Marine High-Resolution Coastal Service , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18174, https://doi.org/10.5194/egusphere-egu24-18174, 2024.

X4.23
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EGU24-20542
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ECS
Exploring Physical and Biogeochemical Variability in the Southeast Bay of Biscay: insights from a glider mission and the analysis of complementary multiplatform data
(withdrawn)
Ivan Manso-Narvarte, Anna Rubio, Almudena Fontán, Marina Chifflet, Asier Nieto, Ainhoa Caballero, and Julien Mader
X4.24
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EGU24-14472
Fei Chai

With over 2 billion people relying on the marine resources, the East Asian seas have nourished rapid economic growth over the past decades. But this comes at the expense of ocean health. Coastal-SOS - “Coastal Zones Under Intensifying Human Activities and Changing Climate: A Regional Programme Integrating Science, Management and Society to Support Ocean Sustainability”, a UN Ocean Decade endorsed project aims to provide solutions for the sustainable development of coastal ocean through effective integration of science, governance, and society. Numerical modelling is a key programmatic effort, serving synthesis analysis, mechanistic studies, and most importantly, predictions, which will contribute to construct the next generation of product: the data-model fully integrated Digital Twin Ocean. One of the expected outcomes of this project is a decision-making support system and toolbox aided by numerical modelling and the Digital Twin Ocean initiative that will result in integrated coastal management and development of marine spatial planning and ecosystem conservation practices. I will review the existing observational data and modelling work in Xiamen Bay and Changjiang Estuary which are two pilot sites and discuss plan of constructing a Digital Twin Ocean in these regions.

How to cite: Chai, F.: Digital Twin Ocean for China Coastal Seas, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14472, https://doi.org/10.5194/egusphere-egu24-14472, 2024.

Posters virtual: Mon, 15 Apr, 14:00–15:45 | vHall X5

Display time: Mon, 15 Apr, 08:30–Mon, 15 Apr, 18:00
Chairpersons: Stephanie Guinehut, Benjamin Jacob, Julien Brajard
A blue, white, coastal & green ocean
vX5.16
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EGU24-13185
Rianne Giesen and Ad Stoffelen

The ocean surface wind plays a key role in the exchange of heat, gases and momentum at the atmosphere-ocean interface. It is therefore crucial to accurately represent the wind forcing in physical ocean model simulations. A comparison of scatterometer observations and global numerical weather prediction (NWP) model wind fields revealed substantial local systematic errors in wind vector components and spatial derivatives. The widespread use of NWP model winds in the computation of ocean surface processes implies that these biases propagate into modelled air-sea fluxes, surface waves and currents.

Temporally-averaged gridded differences between geolocated scatterometer wind data and NWP wind fields can be used to correct for persistent local NWP wind vector biases. By combining these scatterometer-based bias corrections with global, hourly 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. The hourly real-time product covers the past two years and uses ECMWF operational model forecasts. The hourly and monthly multi-year products currently span the period from August 1999 to 3 months before present-day and are based on the ECMWF ERA5 reanalysis. In 2024, the multi-year products will be extended backward to 1991, covering a period of more than 30 years. The spatial bias correction fields are found to be highly consistent between different scatterometers and over time. Compared to the uncorrected ECMWF winds, the L4 winds correspond better to moored buoy observations and independent scatterometer observations. Like any Copernicus Marine Service product, the wind products are freely and openly available for all operational, commercial and research applications.

How to cite: Giesen, R. and Stoffelen, A.: Multi-decadal surface wind forcing products for the Copernicus Marine Service, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-13185, https://doi.org/10.5194/egusphere-egu24-13185, 2024.

vX5.17
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EGU24-10942
Stefania Angela Ciliberti, Axel Alonso, Arancha Amo-Baladron, Lluis Castrillo, Manuel Garcia, Romain Escudier, Bruno Levier, Elodie Gutknecht, Guillaume Reffray, Lotfi Aouf, Alice Dalphinet, Louna Louise, Roland Aznar, Marcos Sotillo, and Sylvain Cailleau

Qualification and validation of operational ocean products are fundamental processes and vital part of the Copernicus Marine Service for evaluating added value of any new or upgraded release and for monitoring forecasting systems skills in operations. These have an important impact on both users and model developers, in providing a comprehensive understanding of forecasting systems reliability. As cross-cutting activity at production units’ level, and as providers of analysis and forecast ocean products for the Iberia-Biscay-Ireland (IBI) and Northwest Shelf (NWS) regions in the frame of the Copernicus Marine Service, we are continuing to incrementally evolve evaluation methods of forecasting products by improving our capacity in analysing ocean model data using newly available in-situ and satellite observations.

In this presentation, an overview of today capacity in assessing operational ocean model products derived from the Northeast Atlantic and Shelf Seas regions model is presented, including evaluation of ongoing numerical experiments, with an outlook on future product quality evolution. Starting from the NARVAL tool, currently used by the IBI Monitoring and Forecasting Centre for assessing daily operational production of physical and biogeochemical variables, we show how new digital tools can support regional fit-for-purpose assessment and perform multi-model/multi-parameter/multi-frequency verification (with a particular focus on biogeochemical variables) by accessing, using, and interoperating operational products available in the target regions through the Copernicus Marine Data Store.

This work presents the operational daily evaluation and monitoring of the IBI and NWS Blue and Green Ocean products, with a focus on recent systems upgrades and on forecast performances. Evolutions of product quality tools will include integration of new product types - like interim and multi-year regional datasets - with implementation of new metrics, and development of a new digital validation service where users (e.g., end users and intermediate users, including operational teams) will have access to NWS operational systems skills.

How to cite: Ciliberti, S. A., Alonso, A., Amo-Baladron, A., Castrillo, L., Garcia, M., Escudier, R., Levier, B., Gutknecht, E., Reffray, G., Aouf, L., Dalphinet, A., Louise, L., Aznar, R., Sotillo, M., and Cailleau, S.: Progresses in assessing the quality of the Copernicus Marine near real time Northeast Atlantic and Shelf Seas models application., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10942, https://doi.org/10.5194/egusphere-egu24-10942, 2024.

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Lőrinc Mészáros, Felix Lucas Dols, Joanna Staneva, Jacob Benjamin, Johannes Pein, Wei Chen, Giovanni Coppini, Gianandrea Mannarini, Ivan Federico, Mario Leonardo Salinas, Momme Butenschön, Jens Murawski, Jun She, Nadia Pinardi, Jacopo Alessandri, Marco Seracini, and Ghada El Serafy

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.

How to cite: Mészáros, L., Lucas Dols, F., Staneva, J., Benjamin, J., Pein, J., Chen, W., Coppini, G., Mannarini, G., Federico, I., Leonardo Salinas, M., Butenschön, M., Murawski, J., She, J., Pinardi, N., Alessandri, J., Seracini, M., and El Serafy, G.: Underlying models for the European Digital Twin Ocean, a demonstration of three Focus Applications, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20156, https://doi.org/10.5194/egusphere-egu24-20156, 2024.