EUMETSAT, the European Organisation for Meteorological Satellites, is expanding its scope beyond supporting meteorology, environment and climate monitoring, to oceanography. To this end, EUMETSAT operates satellites and data processing systems, to provide services which are of high value to ocean monitoring and prediction, especially to the Copernicus Marine Environment Monitoring Service (CMEMS). Key sea and sea ice parameters operated by EUMETSAT secretariat and Ocean and Sea Ice Satellite Application Facilities for different timeliness are either redistributed by CMEMS or used to improve their user services.

EUMETSAT's current geostationary and polar Programmes, as well as the European Copernicus Programme of which EUMETSAT is a delegated entity, provide operational observations of the sea and sea ice.

The Meteosat geostationnary Programme (MSG and soon MTG) provides sea surface temperature and radiative fluxes from the SEVIRI instrument, and in the future from the FCI and IRS instruments. It is complemented by the polar Programmes EPS, and soon EPS-SG, which provide additional parameters of sea ice, sea surface temperature, sea surface radiative fluxes and wind vectors from AVHRR, ASCAT, IASI and in the future from MetImage, SCA, MWI,IASI-NG.

The Jason-CS Programme and the Copernicus Agreement with the EU have entrusted EUMETSAT with operation of the Copernicus Sentinel-3 and Jason-CS/Sentinel-6 satellites, and thus added ocean colour information and further surface topography and surface temperature products.

The Copernicus Sentinel-3 mission is today flying in constellation, jointly operated by ESA and EUMETSAT. Each Sentinel-3 satellite carries OLCI, SLSTR and topography payload, providing a wide range of operational products related to ocean topography (and related parameters), sea and sea ice surface temperature and ocean colour.

Sentinel-6 is a collaborative Copernicus mission implemented and co-funded by the European Commission, the European Space Agency, EUMETSAT, and the US, through NASA and NOAA.  The two successive Copernicus Sentinel-6 satellites (A and B), launched in November 2020 and to be launched 2025, will fly the same specific non-sun-synchronous low-Earth orbit as the series of European/US TOPEX/Poseidon and Jason satellites to continue the high-precision ocean altimetry mission delivered for more than 30 years.

In this presentation, we will present in details EUMETSAT contributions to observations used by CMEMS, the recent innovations in the EUMETSAT stream of marine satellite data, and planned evolutions responding to CMEMS needs for ocean monitoring and prediction.

How to cite: Obligis, E.: EUMETSAT significant contribution to CMEMS, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-3350, https://doi.org/10.5194/egusphere-egu23-3350, 2023.

The Mediterranean Monitoring and Forecast Center of the Copernicus Marine Service (Med-MFC) provides operational, regular and systematic reference information for the blue (Physics -Med-PHY- and Wave -Med-WAV) and green (Biogeochemistry -Med-BGC) state of the Mediterranean Sea. Based on state of the art modelling developments, the Med-MFC delivers Near Real Time (NRT) analysis and short-term (10 days) forecast and consistent Multi-Year (MY) Reanalysis reconstructions and their Interim extensions from 1987 (Med-PHY), 1993 (med-WAV) and 1999 (Med-BGC) till month minus one.

This work aims at providing a detailed description and a quality assessment of recent modelling upgrades which have been implemented in the latest operational systems since November 2022.

In particular, the major modelling advancements for each system are the following:

• Med-PHY NRT system: improvements in both the hydrodynamic model with a better tidal representation and data assimilation components including a new Mean Dynamic Topography, assimilation of 7km filtered altimeter data and ingestion of newly available altimeter data (Hy-2A/B and Sentinel-6A); delivery of a new variable: vertical velocity.
• Med-BGC NRT system includes the novel bio-optical configuration of the Biogeochemical Flux Model (BFM) and its coupling with the atmospheric light spectral model OASIM. Further, the 3DVarBio assimilation system is upgraded to include oxygen profiles from BGC-Argo.
• Med-WAV NRT system upgrades include: (1) implementation and tuning of WAM Cycle6, (2) implementation of Charnock parameter reduction for strong winds and (3) ingestion of newly available altimeter data into the data assimilation system (Sentinel-6A).
• All the 3 Reanalysis time series have been extended until June 2021.

The model evolutions have been extensively qualified by comparing model results from a series of sensitivity numerical experiments with respect to best available satellite and insitu observations in order to provide a reliable validation assessment. All the evolutions have provided, to a different extent, an overall product quality increase by means of a decreased error and bias with respect to the previous version of the systems when comparing modelling data to observations and previous literature.

How to cite: Clementi, E., Coppini, G., Cossarini, G., Korres, G., Drudi, M., Aydogdu, A., Bolzon, G., Cretí, S., Denaxa, D., Feudale, L., Goglio, A. C., Grandi, A., Lazzari, P., Lecci, R., Mariani, A., Masina, S., Oikonomou, C., Pistoia, J., Salon, S., and Teruzzi, A.: The Copernicus ocean forecasting system for the Mediterranean Sea: description and quality assessment of recent evolutions, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-13228, https://doi.org/10.5194/egusphere-egu23-13228, 2023.

Operational systems provide daily surface velocities that reproduce as closely as possible the state of the ocean, a field that lays at the base of many diverse applications such as routing or search and rescue. There’s a growing need to assess different systems’ ability to reproduce ocean dynamical processes covering a range of spatio-temporal scales so to inform on their suitability for use in a vast range of users’ applications.

Here we present an initiative for putting in place a multi-metric validation platform for the comparison of ocean currents making use of a number of service evolution developments and concepts (MEDSUB py_eddy_tracker, HIVE…). Such tool is aimed at being operable in any region of interest, applicable to any Copernicus Marine products on the Wekeo DIAS cloud access service.

We show an intercomparison of the mesoscale eddy field of different Copernicus Marine systems in the IBI area, together with a range of statistical metrics on surface currents (Eulerian and Lagrangian) comparing against drifting buoys’ velocity measurements. The use of this platform is illustrated with the case of the Grande America catastrophe within the Bay of Biscay in March 2019 to analyse the currents and in fine to help decision-making. Such approach is shown to provide relevant user-oriented uncertainty information for a range of applications.

How to cite: van Gennip, S., Dubost, F., Gouvenou, P., Smith, G., Surcel-Colan, D., Ngueto, Y. F., Régnier, C., Cailleau, S., Levier, B., Law-Chune, S., and Drevillon, M.: Validation and intercomparison of ocean surface circulation analyses and forecasts, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-15318, https://doi.org/10.5194/egusphere-egu23-15318, 2023.

The rapid decline of the Arctic sea ice cover is a primary indicator of Earth’s changing climate. The variability of ice-covered area plays a crucial role in the modulating the ocean-atmosphere exchange. Knowledge of ice properties and their variability is necessary for an adequate simulation of those fluxes. Yet the response of September sea ice area or extent (SIA/SIE) is underestimated compared to observations in many global climate models.

Global ocean reanalyses provide consistent and comprehensive records of sea ice variables and are of pivotal significance for climate studies also in polar regions.  We present the temporal and spatial variability of Arctic sea ice area in the CMEMS ensemble of global ocean reanalyses (GREP), from 1993 onward. We assess the accuracy of GREP in reproducing the evolution in time and space of total sea ice and discriminating between the marginal ice zone (MIZ) from consolidated pack ice. The MIZ properties markedly differ from the thicker, quasi-continuous ice cover of the inner pack, strongly influencing various atmosphere–ocean fluxes, especially the heat flux. The MIZ has become a significant component of contemporary Arctic sea ice cover, with a summer area comparable to that occupied by pack ice. The trend towards the MIZ is set to accelerate.

Compared to satellite products (OSISAF and CDR), GREP provides consistent estimates of recent changes in the Arctic sea ice area and properly reproduces observed interannual and seasonal variability, linear trend, as well as record highs and lows. For sea ice classes, the ensemble spread is comparable to the spread among observational estimates that is as large as the ensemble spread. GREP is shown to properly represent the variability of MIZ area during the growing and melting seasons, as well as their minima and maxima. More evident discrepancies between GREP and satellite products occur during summer, when the MIZ amount increases, causing a spread widening among individual reanalyses.

Our analysis suggests that GREP can be used to get a robust estimate of current Arctic sea ice state and recent trends in sea ice properties.

How to cite: Iovino, D., Selivanova, J., and Cocetta, F.: Arctic marginal ice zone changes in the GREP ensemble reanalysis product, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-12484, https://doi.org/10.5194/egusphere-egu23-12484, 2023.

Sea ice information for the near coastal areas of the Greenlandic waters is of high importance for
the local communities and the maritime industry. The “truth” within sea ice information has
traditionally been associated with Manual Ice Charts; however, the demand for accurate forecasts
is increasing.
At first, this study will introduce a variety of satellite-based Copernicus marine service products
waters with a special focus on a novel automated ice chart that runs on a daily basis at the Danish
Meteorological Institute (DMI). The new product is based on a Convolutional Neural Network
(CNN), which combines passive microwave and SAR imagery in order to optimize retrieval. By
doing so, it produces the best possible sea ice concentration with a resolution comparable to the
manual ice charts.
Secondly, this study presents an improved operational forecast system for the Arctic sea ice
focusing on the Greenlandic waters. The physical basis of the system is close to the Arctic Marine
forecasting system within the Copernicus Marine System. This presentation will present the
forecast system and introduce the first attempts to assimilate a combination of level two data from
the automated ice charts gap-filled with level 2 passive microwave data.
We validate the sea ice edge forecast systems and the individual remotely sensed observational
products by computing the Integrated Ice Edge Error metric. This comparison is focused primarily
on the initial state and secondly on a comparison with the initial state.

How to cite: Ribergaard, M. H., Rasmussen, T. A. S., Ponsoni, L., Kreiner, M. B., Buus-Hinkler, J., Hansen, T. W., and Nielsen-Englyst, P.: Sea ice information for the Greenlandic community, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-16314, https://doi.org/10.5194/egusphere-egu23-16314, 2023.

The current reanalysis and forecasting products provided by the Baltic Monitoring and Forecasting Centre (BAL-MFC) are based on an online one-way coupled NEMO-ERGOM system. Specifically, they use the 3D ocean-ice model NEMO v4.0 in combination with the sea ice and thermodynamic model SI3 and the biogeochemical model ERGOM in a version from 2015 developed at the Leibniz Institute for Baltic Sea Research (IOW). This contribution will highlight the status of the current system with respect to biogeochemical parameter modelling in the Baltic Sea. Furthermore, the advancements towards including biogeochemical ensemble based data assimilation into the products will be presented. For this, the Parallel Data Assimilation Framework PDAF v2.0 is used. The recent introduction of PDAF-OMI, the Observation Module Infrastructure, allows for a modular implementation of different observation types, thus ensuring that the data assimilation of both the physical parameters (satellite sea-surface temperature; temperature and salinity profiles) and the biogeochemical parameters (currently oxygen and nutrients profiles) can be done using the same code.

Validation results of the NEMO-ERGOM-PDAF system with profile assimilation of dissolved oxygen, nitrate and phosphate will be presented. The validation focusses on the influence of the biogeochemical data assimilation on the oxygen and nutrient conditions in the deep basins of the Baltic Sea, which are typically anoxic. 

How to cite: Morrison, H. E., Spruch, L., Düsterhöft-Wriggers, W., Lindenthal, A., and Nerger, L.: Modelling of biogeochemical parameters in the Baltic Sea with a NEMO-ERGOM model system and ensemble based data assimilation, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-11397, https://doi.org/10.5194/egusphere-egu23-11397, 2023.

The CMEMS Monitoring and Forecasting Center for the Baltic Sea (BAL-MFC) uses NEMO coupled to ERGOM to compute reanalysis and forecasts for the Baltic Sea. Operationally, in situ observations of nutrients and oxygen are assimilated using the parallel data assimilation framework (PDAF, https://pdaf.awi.de) using a fixed ensemble read from model snapshots. In the EU-project SEAMLESS, the operational model setup build the basis for enhancements by a fully dynamical data assimilation approach. For this, the coupled NEMO-ERGOM model system is augmented by the data-assimilation functionality of PDAF and NEMO-ERGOM is run in ensemble mode. Using an ensemble of 30 members, satellite surface temperature and chlorophyll observation are assimilated daily. We assess the impact of the assimilation on the forecast skill with a focus on the biogeochemical variables. In addition, additional ecosystem indicators, like trophic efficiency, pH, and phytoplankton community structure are analyzed. The developments on the data assimilation system are in wide parts generic an can also be applied with other model configurations or components. While the developments in SEAMLESS are independent from the BAL-MFC operational developments, it is planned to make them available to the operational service.

How to cite: Sun, Y. and Nerger, L.: Assimilation of satellite temperature and chlorophyll observations for improved ecosystem predictions in the Baltic Sea, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-3451, https://doi.org/10.5194/egusphere-egu23-3451, 2023.

To better understand the global ocean biogeochemical processes, it is crucial to strengthen the spatial coverage of high-quality biogeochemical variables. In this context, we provide high-quality nutrients (nitrate, phosphate and silicate) and carbonate system variables (total alkalinity, dissolved inorganic carbon, pH and partial pressure of carbon dioxide) profiles for BGC-Argo floats equipped with oxygen sensors and data qualified in delayed mode. These variables are derived using neural network models called CANYON-B and CONTENT for nutrients and carbonate system variables, respectively. For the Mediterranean Sea, we deliver these variables from a regional dedicated model called CANYON-MED. These variables are distributed from September 2002 to August 2022 as part of CMEMS MOBTAC service. The last update of the product will be available in CMEMS portal from March 2023.

At the global scale, nitrate, phosphate and silicate are retrieved with an accuracy (from the root mean squared difference) of 0.68, 0.051, 2.3 µmol kg^-1_, respectivelyand the carbonate system variables, i.e., total alkalinity, dissolved inorganic carbon, pH and partial pressure of carbon dioxide are retrieved with an accuracy of 6.2 µmol kg^-1, 6.9 µmol kg^-1, 0.013 (unitless), and 15 µatm, respectively. The global models (CANYON-B and CONTENT) have also been validated with independent data collected from recent various oceanic cruises not used for the development of the methods (from GLODAPv2.2021 database) and the Hawaii Ocean Time series (HOT). These independent validations demonstrate the validity of these models for global ocean applications. The nitrate and pH products were again validated against measured nitrate and pH from BGC-Argo floats equipped with oxygen sensors. Overall validation results were quite satisfactory at global and regional spatial scales.

Currently, the profiles are available for BGC-Argo floats with concurrent profiles of temperature, salinity and oxygen qualified in delayed mode. This product will be also available from near real-time observations from 2024.

How to cite: Renosh, P. R., Sauzède, R., and Claustre, H.: Global ocean product of profiles of nutrients and carbonate system variables within the framework of Copernicus Multi Observations Thematic Assembly Center (MOBTAC), EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-13556, https://doi.org/10.5194/egusphere-egu23-13556, 2023.

The sea level observations from satellite altimetry are characterised by a sparse spatial and temporal coverage. For this reason, along-track data are routinely interpolated into daily grids provided by the Copernicus Marine Service. These are strongly smoothed in time and space and are generated using an optimal interpolation routine requiring several pre-processing steps and covariance characterisation.

In this study, we assess the potential of Random Forest Regression to estimate daily sea level anomalies. One-year-long records of along-track sea level are used to build a training dataset whose predictors are the neighbouring observations. The validation is based on the comparison against daily averages from tide gauges. The generated dataset is on average 10% more correlated to the tide gauge records than the commonly used product from Copernicus. As an example, four time series estimated from satellite altimetry from this study (ML, blue) and CMEMS (orange) at the closest point to four tide gauges (green) are shown in the attached figure. Also shown as text is the Root Mean Square Error (RMSE) of the altimetry dataset considering the tide gauges as ground-truth. Moreover, improvements in the temporal characterisation of the sea level variability will be shown by means of a coherence analysis to be spread over all subannual periods. While the current Copernicus daily sea level anomalies are more optimised for the detection of spatial mesoscales, we show how the methodology of this study can improve the characterisation of sea level variability, particularly in the coastal zone.

Our study fits into the use of Copernicus Marine Service data in the context of pan-European coastal zone monitoring, since this innovative machine-learning based technique is validated along the coast of the North Sea. A publication of this study is in advanced state of review in Ocean Dynamics, a pre-print of the first draft is freely available from https://doi.org/10.48550/arXiv.2207.11962.

How to cite: Passaro, M. and Juhl, M.-C.: On the potential of mapping sea level anomalies from Copernicus Marine Service with Random Forest Regression, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-1478, https://doi.org/10.5194/egusphere-egu23-1478, 2023.

Statistical analysis of extreme wave heights over the globe requires long and sufficiently resolved time series of data that have so far only been available in model reanalyses. In recent years, time series of altimetry observations that allow us to perform this study have become available.

Global maps of extreme significant wave heights were produced over 2002-2020 using a level-4 gridded CMEMS product merging CMEMS significant wave height along-track measurements from 7 altimetric satellites. ERA5 reanalysis data, developed by the ECMWF and available from 1950 onwards, were used as a means of comparison.

The extreme significant wave heights were first analyzed using quantiles such as the 95th percentiles. A second approach based on the Peak-Over-Threshold and the Generalized Pareto Distribution allowed us to estimate 100-year significant wave heights. Global maps obtained on CMEMS altimetric were eventually compared with maps obtained on ERA5 reanalysis.

Extreme wave heights estimated with both approaches show a spatial structure similar to the maxima in the climatological mean but with greater magnitude. Largest trends are exhibited in the Southern Ocean, where the wave heights tend to increase significantly in all results, while the North Atlantic and North Pacific exhibit more complex patterns of trends.

How to cite: Laloue, A., Ghantous, M., and Faugere, Y.: Statistical analysis of extreme waves from satellite altimetry from 2002 to 2020, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-7808, https://doi.org/10.5194/egusphere-egu23-7808, 2023.

Ocean wave forecasting is highly demanded by end-users. There is a pressing need for reliable forecasts, to be applied in emergency services, harbour logistics, search-and-rescue operations, renewable energy or pollutant transport. In addition to this wide variety of uses, the coastal zone represents a modelling challenge due to the joint superposition of physical processes that make it a highly dynamic environment (including wind, waves, circulation and air-sea-land interactions).

In the observational side, remote sensing products such as those derived from Satellite Synthetic Aperture Radar (SAR, e.g. from the Sentinel missions) and High Frequency Radar (HFR, e.g. available at the Copernicus Marine Service - In Situ TAC) offers vast quantities of high-resolution spatio-temporal fields. However, their applicability within the operational ocean forecasts services is not straightforward.

The Copernicus Marine Service Evolution KAILANI project (2022 - 2024) aims to enhance the Copernicus Marine regional wave forecasts by improving the forcings required by spectral wave models: i.e. wind forcings and surface current fields. This enhancement comes from blending remote sensing observations with wind and surface currents forecasts. Artificial Intelligence Neural Networks (ANNs) has been proposed as the basis for this blending, as they allow to extract complex spatio-temporal features from remote-sensing data.

The impact on bias and error reduction would be assessed by testing these blended fields under a preoperational environment. The Iberia-Biscay-Ireland (IBI) area has been selected for this Proof of Concept, due to the good coverage of HFR along its coastline. Selection of pilot study sites in areas at the Cantabrian Sea (macrotidal), the Canary Islands (mesotidal), the NW Mediterranean (microtidal), and in the hot spot that is the Gibraltar Strait will ensure that KAILANI applicability ranges different environments.

This methodology focuses on the post-processing of the forcings. Then, it could be a complement for Data Assimilation algorithms. If successful, the proposed KAILANI methodology could be exportable to different Copernicus Marine Monitoring and Forecasting Centers (MFCs); without significant changes in their numerical codes and operation chain. Finally, the expected enhancement of the delivered coastal wave spectra and their integrated parameters (i.e. wave height, period and direction) will be key to foster downstream nearshore applications.

How to cite: García-León, M., Aouf, L., García-Valdecasas, J., Toledano Lozano, C., Dalphinet, A., García-Valdecasas, J. M., Terrés Nícoli, J. M., Aznar, R., López Collantes, J. M., and G. Sotillo, M.: Enhancing coastal wave forecasts by improving forcings with deep learning – The Copernicus Marine Service Evolution KAILANI project, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-7632, https://doi.org/10.5194/egusphere-egu23-7632, 2023.

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. SeaWiFS, MODIS-AQUA, MERIS, 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 by Copernicus Marine to support different types of end users.  

With the High-Resolution Coastal Service (HROC), Copernicus Marine provides high resolution ocean colour products based on Sentinel-2/MSI data for European coastal waters.  It offers 12 different products which are categorized in three groups: 1) near real time (NRT) daily products, 2) aggregated monthly products and 3) gap-filled daily products. The products are generated for the coastal waters (20km stripe for the coastline) of all European Seas and are provided in a 100m spatial resolution. The primary variable from which it is virtually possible to derive all the geophysical and transparency products is the spectral Remote Sensing Reflectance (RRS). This, together with the Particulate Backscatter Coefficient (BBP), constitute the category of the optics products. The spectral BBP product is generated from the RRS products using a quasi-analytical algorithm. The transparency products include turbidity (TUR) and Suspended Particulate Matter (SPM) concentration. They are retrieved through the application of automated switching algorithms to the RRS spectra adapted to the local water conditions. With this approach we address the high variability of different water types with small scale changes. The geophysical product consists of the Chlorophyll-a concentration (CHL) retrieved via a multi-algorithm approach with optimized quality flagging. High-Resolution products are available from the 1^st of January 2020 to current day, and we will present our experiences after 2 years of operational processing together with an overview of the integrated service improvements (e.g. improvements of flagging, cloud shadow identification and flagging of bottom reflection) and planned improvements for 2023. This includes the development of a correction procedure for the strong detector banding that can be observed over water in S2/MSI imagery, especially in the eastern part of the swath for summer/high sun images. In this procedure the per-band and per-detector geometry will be considered to generate corrected L1C imagery which can then be processed by the HROC processor.

The functionality and the handling of the products will be demonstrated by examples of use cases. It will be highlighted how the products can serve eutrophication monitoring for the EU Water Framework Directive (WFD) in the Southern North Sea or for spatial planning applications in the Baltic Sea. The combination with in-situ data and other spatial information is key for a holistic picture of the environment.

How to cite: van der Zande, D., Stelzer, K., Lebreton, C., Dille, A., Vanhellemont, Q., Böttcher, M., Shevchuk, R., Ruddick, K., and Brockmann, C.: The Copernicus Marine High-Resolution Coastal Service: status and evolutions, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-12602, https://doi.org/10.5194/egusphere-egu23-12602, 2023.