OS4.6

The CMEMS In Situ TAC (INSTAC) integrates in situ observations from various platforms, (e.g. profiling floats, gliders, drifters, saildrones, research vessels, ferryboxes, fixed stations, tides gauges, sea mammals, high-frequency radar), providing physical and biogeochemical ocean data at local, regional and global scales, with an increasing data integration from the polar and coastal regions.

The INSTAC quality-controlled data in both delayed mode and near-real time are contributing to support the operational oceanography (e.g. model forecasting, analysis and reanalysis, satellite calibration, downstream services) and to monitor the 4-dimensional ocean at various spatial and temporal scales. The INSTAC multi-year products provide an essential information on the ocean state, variability and changes and allow addressing long-term variations (climate) analysis as well as detecting remarkable events. Hence, the INSTAC group has contributed substantially to the elaboration of the annual CMEMS Ocean State Report (OSR, Von Schuckmann et al., 2016, 2018, 2019, 2020, 2021).

A general overview of the INSTAC contributions to the CMEMS OSR is presented, highlighting its capacity to describe, analyze and understand the ocean state and variability of both physical and biogeochemical components from the sea surface to the deep ocean, from the coastal to open sea waters, from tropical to polar regions, from semi-enclosed seas to the global ocean, from short-term to long-term temporal scales. The INSTAC team contributes to the CMEMS Ocean Monitoring Indicators reporting, investigates the ocean circulation variability, analyses the impact of climate change on marine ecosystem and ocean circulation, and develops operational applications and services.

Maintaining the current observational network, integrating new platforms, enhancing the spatial and temporal resolutions, improving methodologies and developing new metrics (e.g. quality control, data assimilation), developing new products, INSTAC will continue to serve the overall need to understand and predict the ocean state and variability, in line with the present and future scientific, societal and environmental challenges.

How to cite: Szekely, T., Juza, M., Gourrion, J., Rotllán-García, P., Pouliquen, S., Tarot, S., and Tintoré, J.: The CMEMS In Situ TAC multi-year and multi-variate products to monitor and understand the ocean variability, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-8803, https://doi.org/10.5194/egusphere-egu21-8803, 2021.

The In Situ Thematic Assembly Center (In Situ TAC) for the Copernicus Marine Environment Monitoring Service (CMEMS) is the only data component in the system, out of a total of fifteen, in charge of delivering quality-checked in situ observations in both near real time (NRT products) and delay mode (REP products) for their use in the characterisation of ocean state and variability, assimilation and/or validation activities carried out by the metocean community. 

These in situ observations are gathered by a wide range of platforms (tide gauges, buoys, vessels, CTDs, profilers, gliders, drifters, HF radars, saildrones etc) and include many different parameters (Temperature, Salinity, Sea Level, Currents, Waves, Oxygen, Chlorophyll, Nutrients, Carbon etc). They are made available through known networks and regional data providers to a set of Production Units (PUs) or dedicated Data Centers (Ifremer, PdE, HCMR, IMR, IO-BAS, BSH, SMHI, UiB, CNR, AZTI) where they are quality-checked and homogenized before delivery in terms of format, quality control conventions and standards.

Unlike most of the products available in the CMEMS catalog (90%), in situ  data products do not naturally provide a regular temporal and spatial coverage or resolution. Indeed, these in situ observations can be available at fixed locations, or on a trajectory, or in a gridded area, at fixed depths or on profiles and the transmitting equipment can be configured to report data in different time samplings. Such a  complexity has traditionally prevented 82% of the In Situ TAC products from fully taking advantage of  CMEMS centralized improvements  in terms of the visualization of datasets (WMS) and subsetting (Subsetter). 

To overcome  this situation, a first version of the CMEMS In Situ TAC Dashboard was released in 2017. This tool provides a user-friendly interface which enables the discovery, subsetting, sharing and downloading of files containing in-situ observations from In Situ TAC multiparameter NRT products. The tool relies on a set of python scripts which process homogenized metadata on an hourly basis as well as complementary information submitted by Sea Data Net (provider overview). The resulting information is then accessible through  the interface with the aid of a json-server REST API, which allows users to make queries and filter the information according to their interest.

In 2020, the current release of the CMEMS In Situ Dashboard has been officially approved as an “Advanced Visualization Tool” by CMEMS and is now showcased as a complementary tool to the official viewer. Future developments will explore its extension to the whole In Situ product family (beyond the present In Situ multiparameter NRT datasets), the improvement of data visualization options (currently using EMODnet widget services) and the implementation of data discovery capabilities.

How to cite: Rotllán-García, P., Manzano, F., and Sotiropoulou, M. and the CMEMS In Situ Thematic Assembly Center: In Situ TAC Dashboard, an Advanced Tool for visualizing CMEMS In Situ products, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-2336, https://doi.org/10.5194/egusphere-egu21-2336, 2021.

We present the in-situ biogeochemical data products distributed by the Copernicus Marine Service since 2018. The products offer available data of chlorophyll, oxygen, and nutrients (nitrate, silicate and phosphate), both in near-real time and as re-processed data, collected across the globe. The re-processing involves careful quality control utilizing tailored automated quality control procedures combined with visual inspection of questionable values by experts. Moreover, oxygen data are provided with uniform units for modelers (µmol/l) and other oceanic applications and monitoring purposes (µmol/kg) The products integrate observations aggregated from the Regional EuroGOOS consortium, as well as from SeaDataNet2, National Data Centers (NODCs) and JCOMM global systems, among others.

We highlight some use cases, including a study showing an overall decline in the nutrient concentration (nitrate and silicate) of the Atlantic Water flowing though the Nordic Seas en-route to the Arctic Ocean, during the period 1990-2019. Moreover, the study shows indications of a delayed-response reduction further downstream in the Arctic Water exiting the Arctic Ocean through Fram Strait. Other use cases include the study of variability in the concentration of dissolved oxygen in the Mediterranean Sea, showing an association with dynamical processes.

The in-situ near-real time biogeochemical product is updated every month whereas the re-processed product is updated two times per year. Products are delivered on NetCDF4 format compliant with the CF1.7 standard and well-documented quality control procedures.

How to cite: Lien, V. S., Øie Nilsen, J. E., Perivoliotis, L., Sotiropoulou, M., Denaxa, D., Ehrhart, S., Seppälä, J., and Racapé, V.: BioGeoChemical product provided by the Copernicus Marine Service, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-5625, https://doi.org/10.5194/egusphere-egu21-5625, 2021.

In order to be able to predict the future ocean climate and weather, it is crucial to understand what happened in the past and the mechanisms responsible for the ocean variability. This is particularly true in a complex area such as the Mediterranean Sea with diverse dynamics such as deep convection and thermohaline circulation or coastal hydrodynamics. To this end, effective tools are reanalyses or reconstructions of the past ocean state. 

Here we present a new physical reanalysis of the Mediterranean Sea at high resolution, developed in the Copernicus Marine Environment Monitoring Service (CMEMS) framework. The hydrodynamic model is based on the Nucleus for European Modelling of the Ocean (NEMO) combined with a variational data assimilation scheme (OceanVar).

The model has a horizontal resolution of 1/24° and 141 vertical z* levels and provides daily and monthly 3D values of temperature, salinity, sea level and currents. Hourly ECMWF ERA-5 atmospheric fields force the model and daily boundary conditions in the Atlantic are taken from the global CMCC C-GLORS reanalysis. 39 rivers model the freshwater input to the basin plus the Dardanelles. The reanalysis covers 33-years, initialized from SeaDataNet climatology in January 1985, getting to a nominal state after a two-years spin-up and ending in 2019. In-situ data from CTD, ARGO floats and XBT are assimilated into the model in combination with satellite altimetry data.

This reanalysis has been validated and assessed through comparison to in-situ and satellite observations as well as literature climatologies. The results show an overall improvement of the skill and a better representation of the main dynamics of the region compared to the previous, lower resolution (1/16°) reanalysis. Temperature and salinity RMSE is decreased by respectively 12% and 20%. The deeper biases in salinity of the previous version are corrected and the new reanalysis present a better representation of the deep convection in the Gulf of Lion. Climate signals show continuous increase of the temperature due to climate change but also in salinity.

The new reanalysis will allow the study of physical processes at multi-scales, from the large scale to the transient small mesoscale structures.

How to cite: Escudier, R., Clementi, E., Omar, M., Cipollone, A., Pistoia, J., Drudi, M., Grandi, A., Lecci, R., Aydogdu, A., Masina, S., Coppini, G., and Pinardi, N.: A high resolution reanalysis for the Mediterranean Sea, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-11420, https://doi.org/10.5194/egusphere-egu21-11420, 2021.

The GLORYS12V1 system is a global eddy-resolving physical ocean and sea ice reanalysis at 1/12° resolution covering the 1993-present altimetry period, designed and implemented in the framework of the Copernicus Marine Environment Monitoring Service (CMEMS). All the essential ocean physical variables from this reanalysis are available with free access through the CMEMS data portal.

The GLORYS12V1 reanalysis is based on the current CMEMS global real-time forecasting system, apart from a few specificities that are detailed in this manuscript. The model component is the NEMO platform driven at the surface by atmospheric conditions from the ECMWF ERA-Interim reanalysis. Ocean observations are assimilated by means of a reduced-order Kalman filter. Along track altimeter sea level anomaly, satellite sea surface temperature and sea ice concentration data and in situ temperature and salinity (T/S) vertical profiles are jointly assimilated. A 3D-VAR scheme provides an additional correction for the slowly-evolving large-scale biases in temperature and salinity.

The performance of the reanalysis is first addressed in the space of the assimilated observations and shows a clear dependency on the time-dependent in situ observation system, which is intrinsic to most reanalyses. The general assessment of GLORYS12V1 highlights a level of performance at the state-of-the-art and the reliability of the system to correctly capture the main expected climatic interannual variability signals for ocean and sea ice, the general circulation and the inter-basins exchanges. In terms of trends, GLORYS12V1 shows a higher than observed  warming trend together with a lower than observed global mean sea level rise.

Comparisons made with an experiment carried out on the same platform without assimilation show the benefit of data assimilation in controlling water masses properties and their low frequency variability. Examination of the deep signals below 2000 m depth shows that the reanalysis does not suffer from artificial signals even in the pre-Argo period.

Moreover, GLORYS12V1 represents particularly well the small-scale variability of surface dynamics and compares well with independent (non-assimilated) data. Comparisons made with a twin experiment carried out at ¼° resolution allows characterizing and quantifying the strengthened contribution of the 1/12° resolution onto the downscaled dynamics.

In conclusion, GLORYS12V1 provides a reliable physical ocean state for climate variability and supports applications such as seasonal forecasts. In addition, this reanalysis has strong assets to serve regional applications and should provide relevant physical conditions for applications such as marine biogeochemistry. In a near future, GLORYS12V1 will be maintained to be as close as possible to real time and could therefore provide a relevant reference statistical framework for many operational applications.

How to cite: Lellouche, J.-M., Bourdalle-Badie, R., Greiner, E., Garric, G., Melet, A., Bricaud, C., Legalloudec, O., Hamon, M., Candela, T., Regnier, C., and Drevillon, M.: The Copernicus global 1/12° oceanic and sea ice reanalysis, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-14961, https://doi.org/10.5194/egusphere-egu21-14961, 2021.

Ocean reanalyses are becoming increasingly important to reconstruct and provide an overview of the ocean state from the past to the present-day. These products require advanced scientific methods and techniques to produce a more accurate ocean representation. In the scope of the Copernicus Marine Environment Monitoring Service (CMEMS), a new Black Sea (BS) reanalysis, BS-REA (BSE3R1 system), has been produced by using an advanced variational data assimilation method to combine the best available observations with a state-of-the-art ocean general circulation model. The hydrodynamical model is based on Nucleus for European Modeling of the Ocean (NEMO, v3.6), implemented for the BS domain with horizontal resolution of 1/27° x 1/36°, and 31 unevenly distributed vertical levels. NEMO is forced by atmospheric surface fluxes computed via bulk formulation and forced by ECMWF ERA5 atmospheric reanalysis product. At the surface, the model temperature is relaxed to daily objective analysis fields of sea surface temperature from CMEMS SST TAC. The exchange with Mediterranean Sea is simulated through relaxation of the temperature and salinity near Bosporus toward a monthly climatology computed from a high-resolution multi-year simulation, and the barotropic Bosporus Strait transport is corrected to balance the variations of the freshwater flux and the sea surface height measured by multi-satellite altimetry observations. A 3D-Var ocean data assimilation scheme (OceanVar) is used to assimilate sea level anomaly along-track observations from CMEMS SL TAC and available in situ vertical profiles of temperature and salinity from both SeaDataNet and CMEMS INS TAC products. Comparisons against the previous Black Sea reanalysis (BSE2R2 system) show important improvements for temperature and salinity, such that errors have significantly decreased (about 50%). Temperature fields present a continuous warming in the layer between 25-150 m, within which there is the presence of the Black Sea Cold Intermediate Layer (CIL). SST exhibits a positive bias and relatively higher root mean square error (RMSE) values are present in the summer season. Spatial maps of sea level anomaly reveal the largest RMSE close to the shelf areas, which are related to the mesoscale activity along the Rim current. The BS-REA catalogue includes daily and monthly means for 3D temperature, salinity, and currents and 2D sea surface height, bottom temperature, mixed layer fields, from Jan 1993 to Dec 2019.  The BSE3R1 system has produced very accurate estimates which makes it very suitable for assessing more realistic climate trends and indicators for important ocean properties.

How to cite: Lima, L., Ciliberti, S. A., Aydogdu, A., Escudier, R., Masina, S., Azevedo, D., Peneva, E., Causio, S., Cipollone, A., Clementi, E., Cretì, S., Stefanizzi, L., Lecci, R., Palermo, F., Coppini, G., Pinardi, N., and Palazov, A.: The new Black Sea Reanalysis System within CMEMS, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-9599, https://doi.org/10.5194/egusphere-egu21-9599, 2021.

In the Arctic, the sea surface salinity (SSS) has a key role in processes related to mixing, sea ice melt and freeze. However, due to insufficient salinity observations, uncertainties in present Arctic ocean forecasts and reanalysis are still large. Thanks to the European Space Agency’s (ESA) Soil Moisture and Ocean Salinity (SMOS) mission, two successive versions of regional gridded SSS products for the Arctic Ocean have been developed by the Barcelona Expert Centre (BEC). These two SSS products (V2 and V3) are available from the BEC (http://bec.icm.csic.es/) and the Arctic+Salinity project funded by the ESA (https://arcticsalinity.argans.co.uk).
In this study, we show the impacts of assimilating the SMOS SSS  in a coupled ocean and sea ice forecasting system.

TOPAZ4, the Arctic component of the Copernicus Marine Environment Monitoring Services (CMEMS), is a coupled ice-ocean data assimilative system, using the Ensemble Kalman Filter (EnKF) to assimilate jointly all available ocean and sea ice observations over the whole Arctic. Via the CMEMS portal, TOPAZ4 provides the products of both reanalysis and operational forecasts. Two parallel runs of TOPAZ4 are integrated from July to December in 2016, during which either the V2 or V3 SSS data product is assimilated in addition to other available data sources (altimeter data, SST, sea ice concentration, sea ice drift, T/S profiles, sea ice thickness). Independent in situ salinity profiles are used for validation of the model runs in three regions: 1) in the Beaufort Sea; 2) around Greenland; 3) in the Nordic Seas. Compared to the runs without SSS assimilation, the results show the reduction of a severe saline bias in the Beaufort Sea: 15.9% (V2) and 28.6% (V3), also the Root Mean Squared differences (RMSD) decreased by 10.8% (V2) and 16.2% (V3). Around Greenland, the SSS bias is decreased by 17.3% and the RMSD by 8.2% (V3 only). There are neither degradations or improvements for V2 both around Greenland and in the Nordic Seas. These basic statistics suggest the benefits of assimilating SMOS data on the TOPAZ4 outputs and the advantages from the V3 SSS product especially compared to the V2 product.

Keywords: Arctic Ocean; Sea Surface Salinity; TOPAZ4; In situ; RMSD;

How to cite: Xie, J., Raj, R. P., Bertino, L., Martínez, J., Gabarró, C., and Catany3, R.: Impacts of assimilating Arctic surface sea salinities from SMOS in a coupled ocean and sea ice reanalysis, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-2150, https://doi.org/10.5194/egusphere-egu21-2150, 2021.

As part of the phase 2 of the CMEMS Service Evolution, the BRONCO project (Benefits of dynamically modelled River discharge input for OceaN and COupled atmosphere-land-ocean systems) led to the creation of a new river discharge dataset that can be used as input for the NEMO ocean model. River runoffs into the ocean are taken from a global river discharge reanalysis dataset produced by the CEMS Global Flood Awareness System (GloFAS) driven by ERA5 forcing and called GloFAS-ERA5. This new reanalysis dataset has been evaluated using the latest ECMWF ocean analysis system - Ocean5 - over the 1979-2017 period. Comparisons to ocean observations, showed improved ocean state in the Atlantic Ocean in areas affected by large rivers such as the Amazon, the Mississippi and the St Lawrence, but also in the Mediterranean and the Baltic seas. Positive impact on the representation of the Atlantic Merdional Overturning Circulation is also seen. However, degradation of the ocean state can be detected over the Maritime Continent and on the west coast of Central America and Alaska. Such degradation of the ocean state can be alleviated via a retuning of the GloFAS-ERA5 river runoffs. The need for retuning suggests the existence of biases in the GloFAS-ERA5 reanalysis. Further investigation allowed to attribute those biases to spurious signals in both precipitation and snowmelt in the ERA5 atmospheric reanalysis. This result suggests that, the ocean analysis system can help evaluate the water cycle over land in atmospheric reanalysis products through river-ocean coupling further showcasing the value of an Earth system approach to reanalysis.

How to cite: de Boisseson, E., Zuo, H., Zsoter, E., Harrigan, S., Wetterhall, F., de Rosnay, P., and Prudhomme, C.: Evaluating a dynamically modelled river discharge as input for ocean systems through the monitoring of the ocean state from reanalysis, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-14450, https://doi.org/10.5194/egusphere-egu21-14450, 2021.

The Copernicus Marine Environment Monitoring Service (CMEMS) is delivering ocean satellite observations, in situ observations, together with ocean model reanalyzes, analyzes and forecasts from a unique web portal (Le Traon et al, 2019, https://doi.org/10.3389/fmars.2019.00234). Each one of these products is evaluated before its entry into service, and its quality is documented in a Quality Information Document (QUID). This information is complemented by regular quality metrics updates on the CMEMS website. Due to a relatively sparse observation network, in particular in subsurface, it is still a challenge to propose meaningful uncertainty estimates and forecast skills to the operational oceanography user’s community. In order to improve, and better target the scientific quality information provided to the various types of CMEMS users, several developments are ongoing which will be described in this presentation.

How to cite: Garcia Hermosa, I., Régnier, C., Drevillon, M., Garcia sotillo, M., and Sczcypta, C.: Verification and communication of the scientific quality of operational oceanography products of the Copernicus Marine Service, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-12640, https://doi.org/10.5194/egusphere-egu21-12640, 2021.

The first Copernicus Sentinel-3 satellite, Sentinel-3A, was launched in early 2016, and its twin Sentinel-3B in April 2018. The Sentinel-3 constellation is now fully operational with Sentinel-3B satellite flying in the same orbit plan with a phase difference of 140°. This constellation provides a unique consistent, long-term collection of marine and land data for operational analysis, forecasting and environmental and climate monitoring. The marine centre is part of the Sentinel-3 Payload Data Ground Segment, located at EUMETSAT. This centre together with the existing EUMETSAT facilities provides a routine centralised service for operational meteorology, oceanography, and other Sentinel-3 marine users as part of the European Commission's Copernicus programme. The EUMETSAT marine centre delivers operational Sea Surface Temperature, Ocean Colour and Sea Surface Topography data products based on the measurements from the Sea and Land Surface Temperature Radiometer (SLSTR), Ocean and Land Colour Instrument (OLCI) and Synthetic Aperture Radar Altimeter (SRAL), all aboard Sentinel-3 satellites. All products have been developed together with ESA and industry partners and EUMETSAT is responsible for the production, distribution, performance and future evolution of Level-2 marine products. We will give an overview of the scientific characteristics and algorithms of all marine Level-2 products, as well as instrument calibration and product validation results based on on-going Sentinel-3 Cal/Val activities. Information will be also provided about the current status of the product dissemination and the future evolutions that are envisaged. Also, we will provide information how to access Sentinel-3 data from EUMETSAT and where to look for further information.

How to cite: Obligis, E., Kwiatkowska, E., O'Carroll, A., and Scharroo, R.: Operational marine products from Copernicus Sentinel-3 missions, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-2246, https://doi.org/10.5194/egusphere-egu21-2246, 2021.

A new algorithm for classification of sea ice types on Sentinel-1 Synthetic Aperture Radar (SAR) data using a convolutional neural network (CNN) is presented.  The CNN is trained on reference ice charts produced by human experts and compared with an existing machine learning algorithm based on texture features and random forest classifier. The CNN is trained on a dataset from winter 2020 for retrieval of four classes: ice free, young ice, first-year ice and old ice. The accuracy of our classification is 91.6%. The error is a bit higher for young ice (76%) and first-year ice (84%). Our algorithm outperforms the existing random forest product for each ice type. It has also proved to be more efficient in computing time and less sensitive to the noise in SAR data.

Our study demonstrates that CNN can be successfully applied for classification of sea ice types in SAR data. The algorithm is applied in small sub-images extracted from a SAR image after preprocessing including thermal noise removal. Validation shows that the errors are mostly attributed to coarse resolution of ice charts or misclassification of training data by human experts.

Several sensitivity experiments were conducted for testing the impact of CNN architecture, hyperparameters, training parameters and data preprocessing on accuracy. It was shown that a CNN with three convolutional layers, two max-pool layers and three hidden dense layers can be applied to a sub-image with size 50 x 50 pixels for achieving the best results. It was also shown that a CNN can be applied to SAR data without thermal noise removal on the preprocessing step. Understandably, the classification accuracy decreases to 89% but remains reasonable.

The main advantages of the new algorithm are the ability to classify several ice types, higher classification accuracy for each ice type and higher speed of processing than in the previous studies. The relative simplicity of the algorithm (both texture analysis and classification are performed by CNN) is also a benefit. In addition to providing ice type labels, the algorithm also derives the probability of belonging to a class. Uncertainty of the method can be derived from these probabilities and used in the assimilation of ice type in numerical models. 

Given the high accuracy and processing speed, the CNN-based algorithm is included in the Copernicus Marine Environment Monitoring Service (CMEMS) for operational sea ice type retrieval for generating ice charts in the Arctic Ocean. It is already released as an open source software and available on Github: https://github.com/nansencenter/s1_icetype_cnn.

How to cite: Korosov, A., Boulze, H., and Brajard, J.: Convolutional Neural Networks for Classification of Sea Ice Types in Sentinel-1 SAR Data, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-10580, https://doi.org/10.5194/egusphere-egu21-10580, 2021.

SWIM CFOSAT innovative instrument has already shown its reliability and data quality interest through several publications since its launch in end 2018. Its nadir data are delivered to CMEMS since July 2019 in a L2P/L3. Similarly to other nadir missions AltiKa, Jason3, HY2B, S3…,  these easy to use products are based on a selection of valid data from quality criteria, and bias alignment to buoys networks. They are provided in near real time (3h) and with a 1Hz sampling.

In 2021, the CFOSAT project team is happy to provide to CMEMS, in addition to the mission full products, a  user friendly product, with preselected valid datasets of directional wave spectra and related parameters, and additional information directly derived from the calval expertises upstream. Thanks to it, non expert users should be able to have a simple access to this new product and easy compare it to SAR Wavemode L3 products already in the CMEMS catalogue.

This presentation is a user friendly approach to describe the added value, the future improvements planned and the potential of such product for non experts applications.

How to cite: Ollivier, A., Dibarboure, G., Husson, R., Goimard, G., Hauser, D., Tourain, C., and Aouf, L.: CFOSAT wave spectra joining the family of L2P-L3 CMEMS Wave products!, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-7813, https://doi.org/10.5194/egusphere-egu21-7813, 2021.

Global estimates of the ocean carbon sink are released with a yearly frequency as part of the global carbon budget. However, these global estimates hide important spatial and temporal variabilities that can only partly be resolved by direct in situ observations. In this work we explore options for future observational network design combining data streams from various platforms. Our objective is to identify an optimal observational network for surface ocean pCO₂ in the Atlantic Ocean and the Atlantic sector of the Southern Ocean. For this purpose, eleven Observation System Simulation Experiments (OSSEs) were performed. Each OSSE is a Feed-Forward Neural Network (FFNN) that is based on different data distributions and provides ocean surface pCO₂ for the period 2008-2010 with a 5-day time interval. Based on the geographical and time positions from three observational platforms, volunteering observing ships (VOS), Argo floats and OceanSITES moorings, pseudo-observations were constructed using the outputs from an online-coupled physical-biogeochemical global ocean model with a 0.25º nominal spatial resolution. The aim of this work was to find an optimal spatial distribution of observations to supplement the widely used Surface Ocean CO₂ Atlas (SOCAT) and to improve the accuracy of ocean surface pCO₂ reconstructions. OSSEs showed that the additional data from mooring stations and an improved coverage of the southern Hemisphere with biogeochemical ARGO floats corresponding to at least 25% of the density of active floats (2008-2010) would significantly improve the pCO₂ reconstruction and reduce the bias of derived estimates of sea-air CO₂ fluxes by 77%. The use of only SOCAT data results in a correlation coefficient of 0.67 compared to the ocean model output and a 26.08 𝜇atm standard deviation (25.34 𝜇atm for the model reference) over the chosen regions. While the best OSSE has a correlation coefficient of 0.85 and 24.89 𝜇atm for standard deviation. These results are close to the unrealistic benchmark case with total and only Argo float distribution over 2008-2010: 0.87 and 23.79𝜇atm. The reconstructed average pCO₂ over the whole region is also close to the model reference, ~370 𝜇atm and ~371 𝜇atm, respectively. The integrated air-sea fluxes fCO₂ are about -0.83 Pg/yr (best OSSE) and -0.76 Pg/yr (model reference). 

How to cite: Denvil-Sommer, A., Gehlen, M., and Vrac, M.: Observation System Simulation Experiments for surface ocean pCO2 reconstructions in the Atlantic Ocean, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-11442, https://doi.org/10.5194/egusphere-egu21-11442, 2021.

The neXtSIM-F forecast platform entered into service as part of CMEMS (as product ARCTIC_ANALYSISFORECAST_PHY_ICE_002_011) in July 2020, using the neXtSIM sea ice model . It is a stand-alone sea ice model, forced with atmospheric fields from ECMWF and with ocean fields from TOPAZ4. At that time (July 2021) the model was using the Maxwell Elasto Brittle (MEB) sea ice rheology in its dynamical core. In December 2020, the forecast was upgraded to use the Brittle Bingham Maxwell (BBM) rheology, result in significant improvements to the physical results and in numerical performance and stability. We will present results obtained using this new rheology.

How to cite: Williams, T., Korosov, A., Rampal, P., Einar, O., and Bertino, L.: Effects of using the BBM rheology in the neXtSIM-F forecast platform, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-2099, https://doi.org/10.5194/egusphere-egu21-2099, 2021.

The Mediterranean Analysis and Forecasting System operationally produces analyses and 10 days forecasts of the main physical parameters for the entire Mediterranean Sea and its Atlantic Ocean adjacent areas in the framework of the Copernicus Marine Environment Monitoring Service (CMEMS).

The system is composed by the hydrodynamic model NEMO (Nucleus for European Modelling of the Ocean) 2-way coupled with the third-generation wave model WW3 (WaveWatchIII) and forced by ECMWF (European Centre for Medium-range Weather Forecasts) atmospheric fields. The forecast initial conditions are produced by the OceanVar, a 3D variational data assimilation system which daily assimilates Sea Level Anomaly, vertical profiles of Temperature and Salinity from ARGO and XBT (upon availbility) observations. Moreover a heat flux correction using satellite SST is imposed.

The system has been recently upgraded by including tidal waves, so that the tidal potential is calculated across the domain for the Mediterranean Sea 8 major constituents: M2, S2, N2, K2, K1, O1, P1, Q1. In addition, tidal forcing is applied along the lateral boundaries in the Atlantic Ocean by means of tidal elevation estimated using the FES2014 global tidal model and tidal currents evaluated using TUGO (Toulouse Unstructured Grid Ocean) model. Moreover the data assimilation scheme now accounts for the tidal signal in the altimeter tracks.

The system has been validated comparing model results with satellite and in situ observations. A specific harmonic analysis has been performed comparing model sea level amplitudes and phases with respect to: tide gauges, TPXO global tidal model and literature, showing an overall good skill of all the considered tidal constituents. Moreover the ability of the system to predict sea level has been evaluated comparing the model solutions with respect to tide gauges in areas where recent extreme events occurred such as Venice Lagoon “Acqua Alta” in November 2019, Western Mediterranean Sea during Gloria storm in January 2020, Ionian Sea during Medicane Ianos in September 2020.

How to cite: Clementi, E., Goglio, A. C., Aydogdu, A., Pistoia, J., Escudier, R., Drudi, M., Grandi, A., Mariani, A., Lyubartsev, V., Lecci, R., Cretí, S., Masina, S., Coppini, G., and Pinardi, N.: The new Mediterranean Sea analysis and forecasting system including tides: description and validation, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-13531, https://doi.org/10.5194/egusphere-egu21-13531, 2021.

The Med-waves system has been implemented in the framework of the Mediterranean component (MED MFC) of the Copernicus Marine Environment Service (CMEMS) and generates high-resolution analysis, forecast, and reanalysis wave products for the Mediterranean Sea area. The system which is based on the WAM wave model is operational since 2017 and is continuously upgraded in order to represent better the Mediterranean wave dynamics with a high forecast skill. The purpose of this work is to present a description of the various improvements introduced to the system and their impact on the wave product quality. The validation of the system which is done by comparing the model output against buoys and satellite altimeters measurements shows the product quality changes (improvements) due to the different upgrades of the Med-waves system. Based on this upgraded system, we will also give the detailed characteristics of the new reanalysis wave product which is driven by atmospheric forcing from ECMWF ERA5 and provides hourly wave parameters from 1993.

How to cite: Ravdas, M., Zacharioudaki, A., and Korres, G.: The recent upgrade of CMEMS MEDWAVES wave system: description and evaluation., EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-13173, https://doi.org/10.5194/egusphere-egu21-13173, 2021.

The BS-MFC (Black Sea Monitoring and Forecasting Centre) since 2016 is guaranteeing production and delivery of high quality ocean analysis, forecast and reanalysis fields for essential variables, biogeochemical quantities and waves in the Black Sea region within the Copernicus Marine Service. A reliable and robust service infrastructure serves both the production systems and data delivery, through ad hoc technical interfaces, for an efficient update of the catalogue, which includes 22 datasets for physical variables, 22 for biogeochemical variables and 4 for waves. Additionally, a Local Service Desk is in charge for ensuring connections among BS-MFC, CMEMS and Users with the scope to support end-users in using BS-MFC data for downstream applications from the technical and scientific perspectives. The production centres are the core of the BS-MFC: Physics, Biogeochemistry and Waves units implemented, over the Copernicus 2 Programme, state-of-the-art and advanced numerical approaches to improve the quality of the near real time and multi year products. In the 2020, in particular, the BS-Physics team proposed a new reanalysis product, based on new version of the hydrodynamical core model, based on NEMO v3.6, with assimilation of CMEMS observations (e.g. insitu temperature and salinity profiles, including also historical dataset provided by SeaDataNet, and sea level anomaly satellite data) and forced by ECMWF ERA5. The BS-Physics team is working also on preparing the new version of the near real time system, that will provide spatial high resolution analysis and forecast products, using a new version based on NEMO v4.0, online coupled to data assimilation scheme, with optimal interface with the Mediterranean Sea. BS-Biogeochemistry team updated the overall catalogue, with new near real time system, based on NEMO v3.6 online coupled to BAHMBI model, with new carbonate model, able to assimilate new chlorophyll satellite data provided by the CMEMS OC TAC; regarding multi year product, the BS-Biogeochemistry team delivered new datasets, generated by the new NEMO-BAHMBI coupled system forced by ECMWF ERA5 – totally aligned with the near real time system, without data assimilation – for reconstructing the past biogeochemical sea state in the Black Sea. BS-Waves team updated the overall catalogue as well, with new near real time system based on state-of-the-art WAM Cycle 6.0, one-way coupled with hourly currents fields provided by the BS-Physics near real time system; a new reanalysis, from 1979 to 2019, has been also delivered, based on same core model as the near real time system, forced by ECMWF ERA5 atmospheric forcing, and able to assimilate the significant wave height provided by CMEMS SL TAC. Systems are monitored through a product quality dashboard, based on standards inherited from GODAE/Oceanpredict and MERSEA/MyOcean (which includes CLASS 1, 2 and 4 metrics).

How to cite: Palazov, A., Ciliberti, S. A., Lecci, R., Gregoire, M., Staneva, J., Peneva, E., Matreata, M., Masina, S., Coppini, G., Pinardi, N., Creti', S., Vandenbulcke, L., Behrens, A., Palermo, F., Marinova, V., Jansen, E., Lima, L., Aydogdu, A., Valcheva, N., and Agostini, P.: The BS-MFC service and system evolutions within Copernicus Marine Service, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-5435, https://doi.org/10.5194/egusphere-egu21-5435, 2021.

The Black Sea physical analysis and Forecasting System (BSFS) is part of the Black Sea Monitoring and Forecasting Centre (BS-MFC) for the Copernicus Marine Service (CMEMS). It provides analysis every day analysis and 10 days forecast fields for the blue ocean variables (including temperature, salinity, sea surface height, mixed layer depth and currents) in the Black Sea region since. In this work, we present the new version of the operational system that will be part of the next CMEMS  release. The hydrodynamical core model is based on NEMO v4.0, solved on 1/40º horizontal resolution spatial grid (including the overall Black Sea, the Bosporus Strait and part of the Marmara Sea) and 121 vertical levels with z-star. The core model uses ECMWF analysis and forecast atmospheric forcing and GPCP monthly climatological precipitation for computing heat, water and momentum fluxes. A total number of 72 rivers is accounted, as monthly climatology provided by SESAME project. The model implements a new representation of the Danube River with interannual river discharge datasets provided by the National Institute of Hydrology and Water Management. One of the main innovations of this system is the opening of the Bosporus Strait by using a box-approach in a portion of the Marmara Sea: it is achieved thanks to high resolution temperature, salinity, sea surface height, zonal and meridional velocity solutions provided by a novel implementation of the Marmara Sea model including straits based on Shyfem: it represents the optimal interface between the Mediterranean and the Black Sea. The hydrodynamical model is online coupled to an upgraded version of the OceanVar, the CMCC data assimilation scheme, able to assimilate SLA L3 satellite data, T/S in-situ profiles and SST from CMEMS TACs. The contribution focuses on model setup description, processing system and validation. To evaluate BSFS pre-operational run and monitor the operational production, we provide metrics as proposed within GODAE/Oceanpredict and MERSEA/MyOcean (which includes CLASS 1, 2 and 4 metrics).

How to cite: Ciliberti, S. A., Jansen, E., Azevedo, D., Gunduz, M., Ilicak, M., Pinardi, N., Coppini, G., Masina, S., Lecci, R., Causio, S., Stefanizzi, L., Creti', S., Lima, L., Aydogdu, A., Peneva, E., and Matreata, M.: Evolution of the Black Sea Physical Analysis and Forecasting System within CMEMS, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-6598, https://doi.org/10.5194/egusphere-egu21-6598, 2021.

In this contribution, we investigate the predictability properties of the ocean dynamics using an ensemble of medium range numerical forecasts. This question is particularly relevant for ocean dynamics at small scales (< 30 km), where sub-mesoscale dynamics is responsible for the fast evolution of ocean properties. Relatively little is known about the predictability properties of a high resolution model, and hence about the accuracy and resolution that is needed from the observation system used to generate the initial conditions.

A kilometric-scale regional configuration of NEMO for the Western Mediterranean (MEDWEST60, at 1/60º horizontal resolution) has been developed, using boundary conditions from a larger  North Atlantic configuration at same resolution (eNATL60). This deterministic model has then been transformed into a probabilistic model by introducing innovative stochastic parameterizations of model uncertainties resulting from unresolved processes. The purpose is here primarily to generate ensembles of  model states to initialize predictability experiments. The stochastic parameterization is also applied to assess the possible impact of irreducible model uncertainties on the skill of the forecast. A set of three ensemble experiments (20 members and 2 months ) are performed, one  with the deterministic model initiated with perturbed initial conditions, and two with the stochastic model, for two different amplitudes of model uncertainty. In all three experiments, the spread of the ensemble is shown to emerge from the small scales (10 km wavelength) and progressively upscales to the largest structures. After two months, the ensemble variance saturates over most of the spectrum (except in the largest scales), whereas the small scales (< 30 km) are fully decorrelated between the different members. These ensemble simulations are thus appropriate to provide a statistical description of the dependence between initial accuracy and forecast accuracy over the full range of potentially-useful forecast time-lags (typically, between 1 and 20 days).   

The predictability properties are statistically assessed using a cross-validation algorithm (i.e. using alternatively each ensemble member as the reference truth and the remaining 19 members as the ensemble forecast) together with a specific score to characterize the initial and forecast accuracy. From the joint distribution of initial and final scores, it is then possible to quantify the probability distribution of the forecast score given the initial score, or reciprocally to derive conditions on the initial accuracy to obtain a target forecast skill. In this contribution, the misfit between ensemble members is quantified in terms of overall accuracy (CRPS score), geographical position of the ocean structures (location score), and  spatial spectral decorrelation of the Sea Surface Height 2-D fields (spectral score). For example, our results show that, in the region and period  of interest, the initial location accuracy required (necessary condition) with a perfect model (deterministic) to obtain a location accuracy of the forecast of 10 km with a 95% confidence is about 8 km for a 1-day forecast, 4 km for a 5-day forecast, 1.5 km for a 10-day forecast, and this requirement cannot be met with a 15-day or longer forecast.

How to cite: Leroux, S., Brankart, J.-M., Albert, A., Molines, J.-M., Brodeau, L., Le Sommer, J., Penduff, T., and Brasseur, P.: Ensemble quantification of  short-term predictability  of the ocean fine-scale dynamics, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-12001, https://doi.org/10.5194/egusphere-egu21-12001, 2021.

How to cite: Vervatis, V., De Mey-Frémaux, P., Lemieux-Dudon, B., Karagiorgos, J., Ayoub, N., and Sofianos, S.: Ensemble generation of regional ocean physics and biogeochemical model uncertainties, empirical consistency and suitability for probabilistic forecasting, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-14154, https://doi.org/10.5194/egusphere-egu21-14154, 2021.

Mercator Ocean, based in Toulouse, France, provides operational oceanography services, and is entrusted by the European Commission to implement the Copernicus Marine Environment Monitoring Service CMEMS. As part of these services, Mercator Ocean develops and operates ocean analysis and forecasting systems based on the Ocean General Circulation Model NEMO, assimilating satellite and in situ observations of the Global Ocean Observing System. The global ocean 10-day forecasts are updated daily, and their horizontal resolution is 1/12° (~9km), which allows describing accurately the largest mesoscale features in the ocean. Biogeochemical Ocean forecasts are also produced, at a coarser resolution (~ 25km), providing information on large categories planktons and nutrients which are the first levels of the trophic chain in the ocean. The verification of these physical and biogeochemical forecasts is based on standards developed by the GODAE/Oceanpredict community, and by the CMEMS product quality working group. In this presentation, we will discuss the metrics which are used, and their representativeness depending on the variable and on the reference observations that are available.  In particular, recent results from the comparison of several forecast lengths with observed velocities will be shown.

How to cite: Drévillon, M., Regnier, C., Sczcypta, C., Levier, B., Perruche, C., and Van Gennip, S.: Verification of Mercator Ocean global ocean forecasts, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-12037, https://doi.org/10.5194/egusphere-egu21-12037, 2021.

Ocean reanalyses (ORAs) are used extensively in polar research, hence their realism should be assessed regularly. Here the ORAs performance in the Antarctic region is analyzed with specific emphasis on sea ice concentration and thickness. We used four global ocean-sea ice products: C-GLORSv7, FOAM-GLOSEA5v13, GLORYS2v4, and ORAS5, and their ensemble mean GREP (provided by CMEMS) within the 1993 to 2018 period. All ORAs use the NEMO ocean model in a global eddy-permitting configuration (1/4° horizontal resolution and 75 vertical levels) and are forced by the ECMWF ERA-Interim atmospheric reanalysis.

Here we examine the ability of ORAs to reproduce sea ice properties in the Southern Ocean taking into account regional characteristics and sea ice types. Seasonal and interannual variability of sea ice concentration (SIC) and sea ice thickness (SIT) is examined in the hemispheric domain and in five sub-regions for three different sea ice classes: pack ice (SIC ≥ 80%), marginal ice zone (MIZ) (15% ≤ SIC < 80%), and sparse ice (0 < SIC <15%).  Modeled sea ice properties are compared to a set of satellite products: NSIDC CDR, Ifremer/CERSAT, and EUMETSAT OSI-SAF for SIC and Envisat and CryoSat-2 for SIT, together with PIOMAS and GIOMAS reanalyses. We revealed shortcomings of reanalysis systems to be improved in the future representation of Antarctic sea ice. Additionally, we focused on the assessment of the GREP ensemble mean product. We found that for certain metrics GREP minimizes the single errors and outperforms individual members. The evidence from this study implies that GREP can be a feasible product for a number of applications.

How to cite: Selivanova, J. and Iovino, D.: Antarctic sea ice in global ocean reanalyses, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-9726, https://doi.org/10.5194/egusphere-egu21-9726, 2021.

Regional sea levels often behave significantly differently from the global average, making it difficult to establish future sea-level projections. In the Atlantic Ocean, the regional average steric (thermosteric, halosteric) sea level plays an important role in the variability of the overall trend, associated with heat and freshwater, redistribution due to circulation, and freshwater input from melting land ice and river runoff over the past two decades. This contribution varies in space and time. Based on sea level measurements obtained by satellite altimetry from CMEMS products and salinity and temperature data from Argo floats for the period 2005-2015, we found that the Gulf of Guinea and the Atlantic Niño boxes experienced a large thermosteric relative to the Amazon box, which experienced a larger halosteric contribution to sea-level change. This remarkably large halosteric contribution is associated with a cooling in the upper 700 m range. Currently, local atmospheric forcing, such as wind variability, may not explain this warming while the Tropical Northern Atlantic (TNA) index tends to explain the freshening.

How to cite: Kemgang Ghomsi, F. E., Raj, R. P., Rouault, M., and von Schuckmann, K.: Sea level variability on interannual, decadal and longer time scales along the tropical Atlantic, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-11960, https://doi.org/10.5194/egusphere-egu21-11960, 2021.

Enhanced intrusion of warm and saline Atlantic Water (AW) to the Arctic Ocean (AO) in recent years has drawn wide interest of the scientific community owing to its potential role in ‘Arctic Amplification’. Not only the AW has warmed over the last few decades , but its transfer efficiency have also undergone significant modifications due to changes in atmosphere and ocean dynamics at regional to large scales. The Nordic Seas (NS), in this regard, play a vital role as the major exchange of polar and sub-polar waters takes place in this region. Further, the AW and its significant modification on its way to AO via the Nordic Seas has large scale implications on e.g., deep water formation, air-sea heat fluxes. Previous studies have suggested that a change in the sub-polar gyre dynamics in the North Atlantic controls the AW anomalies that enter the NS and eventually end up in the AO. However, the role of NS dynamics in resulting in the modifications of these AW anomalies are not well studied. Here in this study, we show that the Nordic Seas are not only a passive conduit of AW anomalies but the ocean circulations in the Nordic Seas, particularly the Greenland Sea Gyre (GSG) circulation can significantly change the AW characteristics between the entry and exit point of AW in the NS. Further, it is shown that the change in GSG circulation can modify the AW heat distribution in the Nordic Seas and can potentially influence the sea ice concentration therein. Projected enhanced atmospheric forcing in the NS in a warming Arctic scenario and the warming trend of the AW can amplify the role of NS circulation in AW propagation and its impact on sea ice, freshwater budget and deep water formation.

How to cite: Chatterjee, S., Raj, R. P., Bertino, L., and Murukesh, N.: Influence of Nordic Seas dynamics on the Atlantic Water propagation and its impacts on sea ice concentration., EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-14798, https://doi.org/10.5194/egusphere-egu21-14798, 2021.

With the extensive use of ocean color (OC) satellite products, diverse algorithms have been developed in the past decades to observe the phytoplankton community structure in terms of functional types, taxonomic groups and size classes. There is a need to combine satellite observations and biogeochemical modelling to enable comprehensive phytoplankton groups time series data and predictions under the changing climate. A prerequisite for this is continuous long-term satellite observations from past and current OC sensors with quantified uncertainties are essential to ensure their application. Previously we have configured an approach, namely OLCI-PFT (v1), to globally retrieve total chlorophyll a concentration (TChl-a), and chlorophyll a concentration (Chl-a) of multiple phytoplankton functional types (PFTs). This algorithm is developed based on empirical orthogonal functions (EOF) using satellite remote sensing reflectance (Rrs) products from the GlobColour archive (https://www.globcolour.info/). The algorithm can be applied to both, merged OC products and Sentinel 3A OLCI data. Global PFT Chl-a products of OLCI-PFT v1 are available on CMEMS under Ocean Products since July 2020. Lately we have updated the approach and established the OLCI-PFT v2 by including sea surface temperature (SST) as input data. The updated version delivers improved global products for the aforementioned PFT quantities. The per-pixel uncertainty of the retrieved TChl-a and PFT Chl-a products is estimated and validated by taking into account the uncertainties from both input data (satellite Rrs and SST) and model parameters through Monte Carlo simulations and analytical error propagation. The uncertainty of the OLCI-PFT products v2 was assessed on a global scale. For PFT Chl-a products this has been done for the first. The uncertainty of OLCI-PFT v2 TChl-a product is in general much lower than that of the TChl-a product generated in the frame of the ESA Ocean Colour Climate Change Initiative project (OC-CCI). The OLCI-PFT algorithm v1 and v2 have also been further adapted to use a merged MODIS-VIRRS input. Good consistency has been found between the OLCI-PFT products derived from using input data from the different OC sensors. This sets the ground to realize long-term continuous satellite global PFT products from OLCI-PFT. Satellite PFT uncertainty, as provided for our products, is essential to evaluate and improve coupled ecosystem-ocean models which simulate PFTs, and furthermore can be used to improve these models directly via data assimilation.

How to cite: Xi, H., Losa, S. N., Mangin, A., Garnesson, P., Bretagnon, M., Demaria, J., A. Soppa, M., Hembise Fanton d'Andon, O., and Bracher, A.: Global chlorophyll a concentrations of phytoplankton functional types with detailed uncertainty assessment using multi-sensor ocean color and sea surface temperature products, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-9720, https://doi.org/10.5194/egusphere-egu21-9720, 2021.

Copernicus marine environment monitoring service (CMEMS) gives users access to a wide range of ocean descriptors. Both physics and biogeochemistry of the marine environment can be studied with complementary source of data, such as in situ data, modelling output and satellite observations at global scale and/or for European marginal seas. Among the ocean descriptors supplied as part of CMEMS, phytoplankton functional types (PFTs) describe the phytoplanktonic composition at global level or over European marginal seas. Studied phytoplankton assemblage is particularly important as it is the basis of the marine food-web. Composition of the first trophic level is a valuable indicator to infer the structure of the ecosystem and its health. Over the last decades, ocean colour remote sensing has been used to estimate the phytoplanktonic composition. The algorithms developed to estimate PFTs composition based on ocean colour observation can be classified in three categories: the spectral approaches, the abundance-based approaches (derived from the chlorophyll concentration) and the ecological approaches. The three approaches can lead to differences or, conversely, to similar patterns. Difference and similarity in PFTs estimation from remote sensing is a useful information for data assimilation or model simulation, as it provides indications on the uncertainties/variability associated to the PFT estimates. Indeed, PFT estimates from satellite observations are increasingly assimilated into ecological models to improve biogeochemical simulations, what highlights the importance to get an index or at least information describing the validity range of such PFTs estimates.

In this study, four algorithms (two abundance-based, and two spectral approaches) are compared. The aim of this study is to compare the related PFT products spatially and temporally, and to study the agreement of their derived PFT phenology. This study proposes also to compare PFT algorithms developed for the global ocean with those developed for specific regions in order to assess the potential strength and weakness of the different approaches. Once similarities and discrepancies between the different approaches are assessed, this information could be used by model to give an interval of confidence in model simulation.

How to cite: Bretagnon, M., Alvain, S., Bracher, A., Garnesson, P., losa, S., Mangin, A., Rêve, A.-H., Uitz, J., Xi, H., and Hembise Fanton d'Andon, O.: Intercomparison of Phytoplankton functional types dynamics from satellite observations, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-9855, https://doi.org/10.5194/egusphere-egu21-9855, 2021.

The Ocean Colour Instrument (OLCI) on-board the Sentinel-3A and 3B satellites with a 300 m spatial resolution has a major advantage compared to other satellite missions with a typical 1 km spatial resolution. The chlorophyll-a product derived from OLCI’s 300 m measurement facilitates many applications in marine and coastal ecology, from ecosystem modeling, to fisheries management, and monitoring of water quality. The OLCI 300 m chlorophyll-a swath data (Level-2) are operationally disseminated in NRT mode by the EUMETSAT agency. The Copernicus Marine Environment Monitoring Service (CMEMS) eases the usage of these Level-2 (swath data) by providing Level-3 (daily mapped gridded files) at global and regional level.

This study highlights the first release of a 300 m NRT global daily chlorophyll-a product based on the merging of OLCI S3A and S3B. It will be routinely disseminated in the frame of CMEMS in May 2021. Before this date, the resolution of the CMEMS Chlorophyll products was 4km at global level and 1km over some European regional seas This 300 m product will be based on the Copernicus-GlobColour processor already used by CMEMS for the Global chlorophyll-a product and the regional Atlantic daily interpolated product. The daily image will correspond to a large matrix of 32400x64800 pixels with chlorophyll-a data provided along the coastline (200 km). CMEMS provides to the end-user facilities to extract data on his area and period of interest.

This new product will take benefit of a new EUMETSAT’s Level-2 product baseline which should be switched operationally in NRT mode mid-February 2021. This new baseline improves mainly the System Vicarious Calibration (SVC) gains of both S3A and S3B and the associated quality flags. The Chlorophyll-a OC4ME algorithm has been also improved with the use of the Colour Index algorithm for clear water. The assessment of this new OC4ME chlorophyll-a product (based on tandem data) shows a very good correlation between S3A and S3B. A regression between a daily S3A and S3B global product provides a R2 of 0.98 with a respective slope and offset of 1.0 and 0.005. However, some limitations concerning the level-2 upstream products have been identified. Details about the merging procedure, inter-comparison with existing product and illustrations of results will be presented.

How to cite: Garnesson, P., Mangin, A., Demaria, J., Bretagnon, M., and Hembise Fanton d'Andon, O.: First release of the CMEMS Global coastal OLCI 300 meters Chlorophyll-a Product, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-6239, https://doi.org/10.5194/egusphere-egu21-6239, 2021.

The marine environment experiences temperature variability both in the short and long term due to a combination of variable surface heating, ocean transport and mixing effects. The impact of temperature anomalies on the marine ecosystem depends on their duration and amplitude compared with timescales of the ecological response and the susceptibility of various components of the ecosystem to the change. Even relatively short events can affect reproduction and growth, and potentially cause mortality when organism tolerance limits are exceeded.
We focus on sustained (lasting longer than 5 days) temperature events that are extreme relative to the phase of the seasonal cycle and consider both heatwaves and cold-spells. We used daily-mean near-bed temperatures from the CMEMS (https://marine.copernicus.eu/) northwest European Shelf reanalysis and analysis/forecast simulations to identify heatwaves and cold-spells for the period 1993 to 2019. Monthly fisheries landings data for 1993 to 2016 from the Cefas Fisheries Activity Database for England and Wales (https://www.gov.uk/guidance/fishing-activity-and-landings-data-collection-and-processing) were analysed to identify potential impacts of the extreme temperature events on fish and shellfish.
Widespread heatwaves and cold-spells occurred in the southern North Sea throughout the period 1993 to 2019 but with no significant trends in the extent or magnitude of events. Winter cold-spells occurred in 1994, 1996, 1997, 2010, 2011, 2013 and 2018 and there were widespread heatwaves in 1998, 2002, 2003, 2006, 2007 and 2014 to 2019. Statistical analysis of the fisheries landings data identified a link between extreme temperature events and key fish and shellfish stocks in the North Sea. Catches of sole and sea bass increased in years with cold-spells, while catches of red mullet and edible crabs decreased. For heatwaves, the impact on fisheries catch data lagged the temperature events by five years: sole, European lobster and sea bass catches increased whilst red mullet catches reduced. 

How to cite: Wakelin, S., Townhill, B., Engelhard, G., Holt, J., and Renshaw, R.: Marine heatwaves and cold-spells, and their impact on fisheries in the southern North Sea, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-7329, https://doi.org/10.5194/egusphere-egu21-7329, 2021.

The European Blue Growth perspective suggests a larger share in global economic production
and food security appointed to the marine and coastal zone and an increase of marine and coastal
infrastructures   and   operations.   However,   this   growth   must   be   aligned   with   increasing
environmental constraints as well as complying and restoring regulations and frameworks. The
compliance of growth and sustainability requires the adoption of economically and ecologically
efficient behaviours, based on a wider incorporation of available information and knowledge from
the industry and citizens alike. Marine and coastal managers must make decisions to maintain
the social, economic, and ecological health of marine and coastal areas while operating, planning
and managing their activities at sea.
The European funded FORCOAST project represents a step forward in this direction by bringing
the coastal water quality and met-ocean information closer to the target sectors: wild fisheries,
oyster   grounds   restoration,   and   bivalve   mariculture.   FORCOAST   will   develop,   test   and
demonstrate, in operational mode, novel Copernicus-based downstream information services that
will  incorporate  and  combine  Copernicus  Marine  Environment  Monitoring  Service  (CMEMS),
Copernicus Land  Monitoring Service (CLMS) and  Climate Change Monitoring Service  (CMS),
local monitoring data and advanced modelling in the service.
FORCOAST will provide consistent high-resolution data products for coastal applications, based
on a standardized data processing scheme. The services of FORCOAST will provide managerial
tools (e.g decision support, user warnings, on-demand case study) built upon those products and
implemented through cloud-processing infrastructures.
FORCOAST will develop and provide those services in eight pilot service uptake sites covering
five  different  regional  waters  (North  Sea,  Baltic  Sea,  Mediterranean  Sea,  Black  Sea and  the
coastal Atlantic Ocean). Each of those pilots gathers marine information producers (eg. models),
providers (dissemination) and user (operating SMEs), to ensure inter-sectoral consistency.
The outcome of FORCOAST is a novel commercial service that will provide Copernicus-based
downstream  information  coastal  services  to  a  variety  of  stakeholders,  which  will  result  in  an
operation, planning and management improvement of different marine activities in the sectors of
wild fisheries and aquaculture, having an economic and societal positive effect on the involved
parties.

*This  project  has  received  funding  from  the  European  Union’s  Horizon  2020  research  and  innovation
programme under grant agreement No 870465

How to cite: Rodriguez Galvez, L., El Serafy, G., Twigt, D., Rubio, A., Capet, A., Dabrowski, T., Delbare, D., and Fernandez, V.: FORCOAST - Earth Observation services for Wild Fisheries, Oystergrounds Restoration and Bivalve Mariculture along European Coasts*, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-15611, https://doi.org/10.5194/egusphere-egu21-15611, 2021.

Coastal zones experience huge variability due to combined influence of processes in ocean, atmosphere and land. At the same time, coastal areas are important for economic, social and environmental interests such as shipping, aquaculture and mussel fisheries. Nissum Broad and Lem Vig situated in Limfjord constitute one of the finest Flatoyster environments in Europe. The FORCOAST project of Limfjord area as part of Horizon 2020 research and innovation program is dealing with Copernicus-based downstream information services incorporating CMEMS products, local monitoring data and advanced modelling. Within the FORCOAST project, downstram application for the coastal areas and estuaries of the Limfjord are developed. In this study, the Limfjord domain in about 185m horizontal resolution with wet boundaries at Baltic Sea and the North Sea is considered. Sea level and inflows in Limfjord are largely dependent on boundary conditions at North sea and Baltic sea. Therefore, a tuning of boundary conditions of standalone setup is performed by linear scaling of boundary values. The applied ocean model is the HBM model (HIROMB-BOOS Model) which is also well suited for seemless nesting at various scales enabling to model the transition from the basin-scales to coastal- and estuary-scales. Therefore, the results of standalone setup are compared with two-way nested CMEMS Baltic Monitoring Forecasting Centre set-up with included Limfjord domain. The results show that both tuned standalone setup and nested setups are able to provide high quality sea level forecast for storm surge warning, temperature, salinity and currents. The model is able to handle the shallow thermoclines in summer as well as the strong tidal and wind driven transport through narrow straits in autumn and winter. Tuning of standalone setup enables to reach comparable performance in sea level and thermodynamics as of two-way nested setup at much lower computational cost.

How to cite: Frishfelds, V., Murawski, J., and She, J.: Tuning standalone setup of Limfjord with CMEMS boundary conditions, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-15344, https://doi.org/10.5194/egusphere-egu21-15344, 2021.

Keywords: eutrophication; high resolution ocean modeling ; Chla satellite data ; biogeochemistry

Maliakos Gulf corresponds to mesotrophic waters that can reach eutrophic conditions and are occasionally subject to Harmful Algal Blooms (HAB) (Varkitzi et al. 2018). At the same time, it is an important fish farming and aquaculture production area. A large issue is thus related to the monitoring and forecasting of the risk of occurrence of algae blooms in the Gulf. For this purpose, the present study couples predictions from a high-resolution numerical ocean model with satellite observation to improve the monitoring and anticipation of threats for the local fish farms induced by occasional eutrophication.

This solution is developed in the frame of the MARINE-EO project (https://marine-eo.eu/). It combines satellite observation with high-resolution ocean modelling to provide detailed information as a support to fish farms management and operations. It is implemented in an operational platform, which provides continuous information in real time as well as short term predictions. The deployed solution uses CMEMS physical products as an input data and offers to refine this solution in order to provide a local information on site using a downscaling strategy. High resolution satellite products and ocean modelling allow to include the impact of local coastal processes on currents and water quality parameters to provide a proper monitoring and forecasting solution at the scale of a specific fish farm.

To model specific eutrophication processes, a NPZD (Nutrients-Phytoplankton-Zooplankton-Detritus) biogeochemical model is used. Included in the MOHID Water modelling system, the water quality module (Mateus, 2006) considering 18 properties: nutrients and organic matter (nitrogen, phosphorus and silica biogeochemical cycles), oxygen and organisms (phytoplankton and zooplankton) was deployed in the western Aegean Sea. The simulated chlorophyll a concentrations are used to compute a risk level for the eutrophication occurrence. To complete this indicator, another risk level was based on the eutrophication variation following Primpas et al. (2010) formulation. In addition to model forecasts, ocean color observations from the Sentinel-2 MSI and Landsat-8 OLI sensors are used to provide high resolution chlorophyll a concentrations maps in case of bloom events. The processing chain uses the sixth version of the Quasi-Analytical Algorithm initially developed by Lee et al. (2002) and an empirical relation based on a database built using the HydroLight software to compute chlorophyll a concentration.

Two past eutrophication events monitored in situ (Varkitzi et al. 2018) were studied to assess the accuracy of the developed tool. Although few in situ data were available on environmental input (as rivers flow and nutrient concentrations), it was possible using statistics to reproduce qualitatively these blooms. Finally, an operational demonstration was conducted during 2 months of the 2020 autumn season, to showcase real time monitoring and predictive perspectives.

How to cite: Declerck, A., Delpey, M., Voirand, T., and Varkitzi, I.: MARINE-EO project: Monitoring and forecast of eutrophication around fish farms, a Maliakos Gulf case (Eastern Mediterranean)., EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-9961, https://doi.org/10.5194/egusphere-egu21-9961, 2021.

Coastal and marine environmental management is of vital importance in Italy.  Currently there is a growing interest in facilitating user uptake of satellite technologies and Copernicus ecosystem resources, also at non-technical local and regional governmental authorities, and a thematic working table dedicated to “Coastal” issues has been set up in the context of the Italian Copernicus User Forum (Geraldini et al., 2021).

The Italian Space Agency (ASI) has promoted the development of the thematic platform costeLAB as a tool dedicated to monitoring, management and study of coastal areas (sea and land). costeLAB hosts cutting edge tools for satellite image processing and geospatial integration with in-situ data, so as to allow an efficient access to archive data and facilitate direct engagement of users interested in deriving information according to their requirements. costeLAB is built in the framework of Progetto Premiale “Rischi Naturali Indotti dalle Attività Umana - COSTE”, n. 2017-I-E.0, funded by the Italian Ministry of University and Research (MUR), coordinated by ASI and developed by e-GEOS and Planetek Italia, with the National Research Council of Italy (CNR), Meteorological Environmental Earth Observation (MEEO) and Geophysical Applications Processing (G.A.P.) s.r.l. as subcontractors.

Operating in systematic and on-demand modes, costeLAB provides users with validated algorithms and advanced data management resources to analyse multi-mission and multi-sensor data – particularly Copernicus Sentinels and ASI’s COSMO-SkyMed Synthetic Aperture Radar data – and to generate products based on user-selected input parameters, without the need for large data volume transfers. costeLAB aligns with the concept of the European Space Agency’s Thematic Exploitation Platforms, and represents a mean to exploit the Italian Sentinel Collaborative Ground Segment equipped with Sentinel-1/2/3 data archives and programmable computing resources. The platform aims to support downstream applications from a wider user community including the Civil Protection, environmental protection agencies and regulators, coastal scientists, academics, practitioners, and the general public.

costeLAB offers a portfolio of about 30 products among which: coastline, defence works, coastal habitat maps, flooding, hydrocarbon beaching, chlorophyll, wave and wind fields. These products can be generated as “state”, “change”, “damage”, “hazard” or “exposition” maps according to the operational scenarios “baseline knowledge”, “ordinary monitoring”, “extraordinary monitoring” and “post-event”.

We show some of the platform products and how they address specific user needs towards downstream applications, in support to national policies and directives. Examples include products of “Marine Ecosystem” (i.e. “sea level” and “day sea surface temperature cycle”). Thanks to ad hoc Copernicus Marine Environment Monitoring Service (CMEMS) data integration function implemented in costeLAB, these products are generated from pre-processed input data made available in near real time through CMEMS.

costeLAB is also equipped with the “Virtual Laboratory” module, purposely designed as a collaborative environment allowing users (in particular, researchers and analysts) to access “Software as a Service” resources to test proprietary or shared processors, exploit costeLAB computing resources, generate and integrate products, publish results. An example of collaborative research including experiments with ASI’s PRISMA hyperspectral data is presented.

Geraldini et al. (2021) User Needs Analysis for the Definition of Operational Coastal Services. Water 13(1):92.

How to cite: Tapete, D., Candela, L., Coletta, A., Daraio, M. G., Guarini, R., Lopinto, E., Palandri, M., Pellegrino, D., Amodio, A., Giardino, C., and Bresciani, M.: costeLAB, the Italian thematic platform for coastal and marine downstream applications of institutional and research users in the context of Copernicus data exploitation, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-7069, https://doi.org/10.5194/egusphere-egu21-7069, 2021.

The role of coastal mesoscale variability in the modulation of surface along-shelf and cross-shelf exchanges in the SE Bay of Biscay has been demonstrated by several works, from land-based and satellite observations, including high resolution current fields from high-frequency (HF) radars. However, the characterization of physical processes and associated transports at subsurface levels from observations remains a challenge since observations are often too scarce to offer the required spatio-temporal resolution and coverage. In addition to the numerical modelling, the use of methods to reconstruct three-dimensional (3D) current fields from the combination of multiplatform data offers an alternative approach for the study of 3D properties of mesoscale coastal processes, and an improved background to explore bio-physical interactions. Studying the physical properties of coastal mesoscale structures at subsurface levels, where primary production and plankton concentration peak, is key to understand the coupling between physical and biological processes. In this work, we use a previously validated data-reconstruction method and different CMEMS products (coastal simulations, observations from HF radar, satellite, mooring) and glider data, to better characterize the 3D structure of a coastal mode-water eddy and its associated water volume transport. Different Lagrangian properties (maps of particle density, residence times, Lagrangian eddy kinetic energy) obtained at surface and subsurface levels provide a new insight into the water volume transports associated with the main coastal processes in the area.

How to cite: Manso, I., Rubio, A., Jordà, G., Carpenter, J., Merckelbach, L., Declerck, A., Delpey, M., Hernández-Carrasco, I., Mader, J., and Caballero, A.: Characterization of 3D coastal mesoscale structures and transports from multiplatform observations and a data reconstruction method, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-14304, https://doi.org/10.5194/egusphere-egu21-14304, 2021.

Keywords: marine litter; coastal ocean modeling; video monitoring; satellite observation; Bay of Biscay

The service “Floating Marine Litter Tracking”, or “FML-TRACK” is a downstream service from Copernicus Marine Service, aiming at providing an operational support to reduce Floating Marine Litter (FML) in the coastal area. More precisely, FML-TRACK aims at supporting FML reduction strategies both downstream (interception at sea with collect vessels and on beaches with cleaning facilities) and upstream (source identification and reduction), by tracking the dispersion of FML in estuaries and in the coastal ocean. Using a combination of innovative detection technologies and operational metocean modelling, the service produces tailored decision-aid indicators to monitor and guide FML collect operations, including day-to-day operation support in near real time. Guidance offered by these indicators help maximizing the amount of FML removed from the natural environment, while at the same time contributing to reduce the cost and impacts of operations (i.e. cost per kilogram of collected FML, fuel consumption, carbon footprint). Moreover, tracking technologies contribute to the reduction of FML emission at the source, by helping identifying most probable emission sectors depending on metocean conditions.

To achieve these purposes, FML-TRACK combines innovative detection solutions based on video monitoring in rivers and satellite imagery in the coastal area, together with metocean-based FML transport modelling. In the operational mode of the service, it provides a decision-aid dashboard supporting day-to-day FML collect operations. The dashboard offers indicators aiming at guiding FML collect operations, to monitor and optimize their efficiency. It especially provides a tracking of FML in the coastal area and a prediction of concentration hotspots to guide collect vessel at sea; and anticipate massive onshore arrivals to help beach cleaning at land.

The service was demonstrated in the coastal area of the South-Eastern Bay of Biscay, part of the Iberian-Biscay-Ireland regional seas. It took benefit of pre-existing components developed during the former LIFE LEMA program, which were further improved and complemented to bring the tool and service to a new stage, compatible with a realistic application in an operational context.

Main end-users of the service are coastal public administrations involved in the reduction of FML in their region. End-users can also be private companies operating sea or beach cleaning. Fishermen who can be involved in FML collect effort (actively or passively) may also use the service as a support to operations and/or to participate in the monitoring program. Finally, the service may also be of interest for NGOs and scientists committed to the study of and fight against FML, through either participation to the monitoring and/or use of the database for science, awareness and education.

How to cite: Delpey, M., Declerck, A., Epelde, I., Voirand, T., Manso-Navarte, I., Mader, J., Rubio, A., and Caballero, A.: Tracking floating marine litter in the coastal area by combining operational ocean modelling and remote observation systems., EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-11465, https://doi.org/10.5194/egusphere-egu21-11465, 2021.

IBISAR is a user-friendly science-based data downstream service that allows to visualize, compare and evaluate the performance of ocean current predictions in the Iberian-Biscay-Irish (IBI) regional seas. It is designed for emergency responders and Search and Rescue (SAR) operators, to facilitate decision-making by guiding users to identify the most accurate current prediction in near-real time. 

IBISAR service portfolio includes ocean surface current predictions from models, as well as the surface current observations from all the High-Frequency radars and satellite-tracked drifters available in the IBI region from the Copernicus Marine Environment Monitoring Service (CMEMS) portfolio. It also includes coastal and regional models from complementary databases.

The service is freely accessible under registration and offers a visualization interface to make data inter-comparison, and the skill assessment tool for evaluating the accuracy of the different predictions available in a specific area and period of interest, as defined by the user. IBISAR evaluates the performance of available models and HF radars by comparing them versus drifter trajectories based on a Lagrangian approach, providing a skill score easily interpretable to end-users. The validation of the skill assessment methodology envisaged by the IBISAR service has been applied and tested in 4 different pilot areas of the IBI region against more than 140 drifters.

Finally, it is worth mentioning that IBISAR service is the result of a CMEMS User Uptake project, which together with the CMEMS Service Evolution INCREASE project, complement operational activities and feed the upstream and downstream development of the CMEMS service in the coastal zones.

How to cite: Reyes Reyes, E.: IBISAR downstream service: one year of supporting emergency response at sea, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-14919, https://doi.org/10.5194/egusphere-egu21-14919, 2021.