This visualization product displays the cigarette related items abundance of marine macro-litter (> 2.5cm) per beach per year from non-MSFD monitoring surveys, research & cleaning operations without UNEP-MARLIN data. EMODnet Chemistry included the collection of marine litter in its 3rd phase. Since the beginning of 2018, data of beach litter have been gathered and processed in the EMODnet Chemistry Marine Litter Database (MLDB). The harmonization of all the data has been the most challenging task considering the heterogeneity of the data sources, sampling protocols and reference lists used on a European scale. Preliminary processings were necessary to harmonize all the data: - Exclusion of OSPAR 1000 protocol: in order to follow the approach of OSPAR that it is not including these data anymore in the monitoring; - Selection of surveys from non-MSFD monitoring, cleaning and research operations; - Exclusion of beaches without coordinates; - Selection of plastic bags related items only. The list of selected items is attached to this metadata. This list was created using EU Marine Beach Litter Baselines, the European Threshold Value for Macro Litter on Coastlines and the Joint list of litter categories for marine macro-litter monitoring from JRC (these three documents are attached to this metadata); - Exclusion of surveys without associated length; - Normalization of survey lengths to 100m & 1 survey / year: in some case, the survey length was not 100m, so in order to be able to compare the abundance of litter from different beaches a normalization is applied using this formula: Number of plastic bags related items of the survey (normalized by 100 m) = Number of plastic bags related items of the survey x (100 / survey length) Then, this normalized number of plastic bags related items is summed to obtain the total normalized number of plastic bags related items for each survey. Finally, the median abundance of plastic bags related items for each beach and year is calculated from these normalized abundances of plastic bags related items per survey. Percentiles 50, 75, 95 & 99 have been calculated taking into account plastic bags related items from other sources data for all years. More information is available in the attached documents. Warning: the absence of data on the map does not necessarily mean that they do not exist, but that no information has been entered in the Marine Litter Database for this area.

The ODATIS Ocean Color MR product provides optical reflectance measurements as well as related physical, subsurface and biogeochemical parameters at 300 m spatial resolution along the entire French metropolitan coastal zone, according to the criteria defined by the ODATIS Scientific Expert Consortium (CES) dedicated to ocean color : https://www.odatis-ocean.fr/activites/consortium-dexpertise-scientifique/ces-couleur-de-locean. Product processing is performed from Level 1 to Level 3, and is reprojected on a regular square grid format. Data are temporally aggregated and provided as daily, 8 day and monthly products. The "Basic" version of the ODATIS MR product includes data from the MODIS sensor processed with the "NIR/SWIR" atmospheric correction method (Wang and Shi, 2007), as well as data from the MERIS and OLCI-A/B sensors processed with the Polymer atmospheric correction (Hygeos, https://www.hygeos.com/polymer). List of available parameters for each sensor: • MODIS : NRRS555, CHL-OC5, SPM-G, CDOM, T-FNU, SST-NIGHT • OLCI-A/B / MERIS : NRRS560, CHL-OC5, SPM-G, CDOM, T-FNU

This visualization product displays the type of litter in percent per net per year from research and monitoring protocols. EMODnet Chemistry included the collection of marine litter in its 3rd phase. Before 2021, there was no coordinated effort at the regional or European scale for micro-litter. Given this situation, EMODnet Chemistry proposed to adopt the data gathering and data management approach as generally applied for marine data, i.e., populating metadata and data in the CDI Data Discovery and Access service using dedicated SeaDataNet data transport formats. EMODnet Chemistry is currently the official EU collector of micro-litter data from Marine Strategy Framework Directive (MSFD) National Monitoring activities (descriptor 10). A series of specific standard vocabularies or standard terms related to micro-litter have been added to SeaDataNet NVS (NERC Vocabulary Server) Common Vocabularies to describe the micro-litter. European micro-litter data are collected by the National Oceanographic Data Centres (NODCs). Micro-litter map products are generated from NODCs data after a test of the aggregated collection including data and data format checks and data harmonization. A filter is applied to represent only micro-litter sampled according to research and monitoring protocols as MSFD monitoring. To calculate percentages for each type, formula applied is: Type (%) = (∑number of particles of each type)*100 / (∑number of particles of all type) When the number of micro-litters was not filled or was equal zero, it was not possible to calculate the percentage. Standard vocabularies for micro-litter types are taken from Seadatanet's H01 library (https://vocab.seadatanet.org/v_bodc_vocab_v2/search.asp?lib=H01 ). Some morphological types of micro-litters may have been sampled but were not defined by the protocole applied during the survey. They are represented as « undefined micro-litter items ». Warnings: - the absence of data on the map does not necessarily mean that they do not exist, but that no information has been entered in the National Oceanographic Data Centre (NODC) for this area. - since 03/07/2023, the preferred label « Undefined micro-litter items » has been integrated into the H01 library whereas the labels « microplastic items », « non-plastic man-made micro-particles (e.g. glass, metal, tar) » and «non-plastic filaments (natural fibres, rubber) » have been deprecated. When defined, the material or polymer type can be checked directly in the source data.

'''Short description:''' The NWSHELF_ANALYSISFORECAST_PHY_LR_004_001 is produced by a coupled hydrodynamic-biogeochemical model system with tides, implemented over the North East Atlantic and Shelf Seas at 7 km of horizontal resolution and 24 vertical levels. The product is updated daily, providing 7-day forecast for temperature, salinity, currents, sea level and mixed layer depth. Products are provided at quarter-hourly, hourly, daily de-tided (with Doodson filter), and monthly frequency. '''DOI (product) :''' https://doi.org/10.48670/mds-00367

Moving 6-year analysis and visualization of Water body silicate in the North Sea. Four seasons (December-February, March-May, June-August, September-November). Data Sources: observational data from SeaDataNet/EMODnet Chemistry Data Network. Description of DIVA analysis: Geostatistical data analysis by DIVAnd (Data-Interpolating Variational Analysis) tool, version 2.7.12. results were subjected to the minfield option in DIVAnd to avoid negative/underestimated values in the interpolated results; error threshold masks L1 (0.3) and L2 (0.5) are included as well as the unmasked field. The depth dimension allows visualizing the gridded field at various depths.

This set of data documents the radiocarbon dates (n=19) obtained thanks to the accelerator mass spectrometry method (AMS) at the LMC14/ARTEMIS French national facility on the cores (Multicorer, Kullenberg) retrieved from the West-Gironde mud patch (WGMP) during the JERICObent-7 cruise (10-15 July 2019; NR Côtes de la Manche, https://doi.org/10.17600/18001022). The WGMP registers very high sedimentation rates since the last 600 years (≥ 0.3 cm/yr) and is thus of great interest for palaeoceanographic investigations. At present, this depocenter marks the mid-shelf of the temperate Bay of Biscay off major French rivers from the Aquitaine basin. The fine mud deposits of the WGMP are of 3 to 4 meters thick and lie on palimpsest levels rich in gravels and shells. They cover a V-shaped structure, oriented SW-NE, which is attributed to the incision(s) of a paleovalley in the Cenozoic substrate, mainly linked to the paleo-Gironde routing changes during past glacials/interglacials, and its potential past convergences with the paleo-rivers of the Antioche perthuis (Seudre, Charente paleovalleys?) at that times. Detailed information on each sample is presented with the 14C results obtained by the Artemis AMS facility at LMC14 laboratory (Dumoulin et al. 2017- https://doi.org/10.1017/RDC.2016.116, Beck et al. 2024- https://doi.org/10.1017/RDC.2023.23). Raw ages are indicated together with calibration calculations using the last two versions of the Calib software (http://calib.org/, Calib 7 and 8) to show the dispersion of ages linked to the updating of calibration curves (Marine13, Intcal13, Marine20, Intcal 20). The calibrated ages finally retained for publications (used in the related Seanoe document - https://doi.org/10.17882/104237 - and published in Eynaud et al., 2025 for the ST3c core, https://doi.org/10.1016/j.gloplacha.2025.105039) are those obtained with the last Calib 8.1 version. Raw 14C ages were calibrated and converted to calendar ages using the IntCal20 calibration curve with a reservoir age correction of 400 years deduced from Radionuclide analyses (137Cs and 210Pb) at the top of the studied cores (see Schmidt, 2025, https://www.seanoe.org/data/00968/107979/). 

This visualization product displays plastic bags density per trawl. EMODnet Chemistry included the collection of marine litter in its 3rd phase. Since the beginning of 2018, data of seafloor litter collected by international fish-trawl surveys have been gathered and processed in the EMODnet Chemistry Marine Litter Database (MLDB). The harmonization of all the data has been the most challenging task considering the heterogeneity of the data sources, sampling protocols (OSPAR and MEDITS protocols) and reference lists used on a European scale. Moreover, within the same protocol, different gear types are deployed during bottom trawl surveys. In cases where the wingspread and/or number of items were/was unknown, it was not possible to use the data because these fields are needed to calculate the density. Data collected before 2011 are concerned by this filter. When the distance reported in the data was null, it was calculated from: - the ground speed and the haul duration using the following formula: Distance (km) = Haul duration (h) * Ground speed (km/h); - the trawl coordinates if the ground speed and the haul duration were not filled in. The swept area was calculated from the wingspread (which depends on the fishing gear type) and the distance trawled: Swept area (km²) = Distance (km) * Wingspread (km) Densities were calculated on each trawl and year using the following computation: Density of plastic bags (number of items per km²) = ∑Number of plastic bags related items / Swept area (km²) Percentiles 50, 75, 95 & 99 were calculated taking into account data for all years. The list of selected items for this product is attached to this metadata. Information on data processing and calculation is detailed in the attached methodology document. Warning: the absence of data on the map does not necessarily mean that they do not exist, but that no information has been entered in the Marine Litter Database for this area.

C-RAID: Comprehensive Reprocessing of Drifting Buoy Data (1979-2018) The C-RAID (Copernicus - Reprocessing of Drifting Buoys) project delivers a comprehensive global reprocessing of historical drifting buoy data and metadata, providing climate-quality observations for marine and atmospheric research. Dataset Overview The C-RAID dataset encompasses metadata from 21 858 drifting buoys deployed between 1979 and 2018. Of these, 17 496 buoys have undergone complete reprocessing with scientific validation in delayed mode, including comparison against ERA5 reanalysis. Project Context Managed by the WMO DBCP Drifting Buoys Global Data Assembly Centre (GDAC) through Ifremer, Météo-France, and Ocean Sciences Division of Fisheries and Oceans Canada, C-RAID focuses on enhanced quality control and delivery of climate-quality drifting buoy data for the Marine Climate Data System (MCDS). Objectives - Complete reprocessing and clean-up of the historical drifting buoy data archive - Recovery and rescue of missing datasets - Reprocessing of Argos data with improved positioning using Kalman filter algorithms - Homogenization of quality control procedures across marine and atmospheric parameters Funding & Governance C-RAID was funded by the Copernicus Programme through the European Environment Agency (Contract # EEA/IDM/15/026/LOT1), supporting cross-cutting coordination activities for the in-situ component of Copernicus Services. Stakeholders & Partnerships The project is led by the DB-GDAC consortium (Ifremer, Météo-France) in collaboration with EUMETNET's E-SURFMAR programme, NOAA AOML, and JCOMMOPS. Key Achievements - Reprocessing of approximately 24 000 buoy-years of observations - Recovery of missing datasets and metadata through data rescue efforts - Implementation of homogeneous, rich metadata and data formats - Enhanced Argos location accuracy using Kalman filter reprocessing - Standardized quality control and validation procedures Data Access & FAIR Principles C-RAID provides FAIR (Findable, Accessible, Interoperable, Reusable) data access through: - Web-based data discovery portal for human users - API services for data discovery, subsetting, and download (machine-to-machine access) Target Users The dataset serves major operational and research programmes including: - Copernicus Climate Change Service (C3S) - Copernicus Marine Environment Monitoring Service (CMEMS) - iQuam (in-situ SST Quality Monitor) - ICOADS (International Comprehensive Ocean-Atmosphere Data Set) - GHRSST (Group for High Resolution Sea Surface Temperature) - ISPD (International Surface Pressure Databank) - ICDC (Integrated Climate Data Center)  

Moving 6-year analysis of Water body phosphate in the NorthEast Atlantic for each season: - winter: January-March, - spring: April-June, - summer: July-September, - autumn: October-December. Every year of the time dimension corresponds to the 6-year centred average of each season. 6-year periods span from 1950/1955 until 2019/2024. Observation data span from 1950 to 2024. Depth levels (IODE standard depths): [0.0, 5.0, 10.0, 20.0, 30.0, 40.0, 50.0, 75.0, 100.0, 125.0, 150.0, 200.0, 250.0, 300.0, 400.0, 500.0, 600.0, 700.0, 800.0, 900.0, 1000.0, 1100.0, 1200.0, 1300.0, 1400.0, 1500.0, 1750.0, 2000.0]. Data sources: observational data from SeaDataNet/EMODNet Chemistry Data Network. Description of DIVAnd analysis: the computation was done with DIVAnd (Data-Interpolating Variational Analysis in n dimensions), version 2.7.12, using GEBCO 30 sec topography for the spatial connectivity of water masses. The horizontal resolution of the produced DIVAnd maps is 0.1 degrees. Horizontal correlation length varies from 250km in open sea regions to 50km at the coast. Vertical correlation length is defined as twice the vertical resolution. Signal-to-noise ratio was fixed to 1 for vertical profiles and 0.1 for time series to account for the redundancy in the time series observations. A logarithmic transformation (DIVAnd.loglin) was applied to the data prior to the analysis. Background field: a vertically-filtered profile of the seasonal data mean value (including all years) is substracted from the data. Detrending of data: no, advection constraint applied: no. Units: umol/l.

'''DEFINITION''' Ocean heat content (OHC) is defined here as the deviation from a reference period (1993-2014) and is closely proportional to the average temperature change from z1 = 0 m to z2 = 700 m depth: OHC=∫_(z_1)^(z_2)ρ_0 c_p (T_yr-T_clim )dz [1] with a reference density of = 1030 kgm-3 and a specific heat capacity of cp = 3980 J kg-1 °C-1 (e.g. von Schuckmann et al., 2009). Time series of annual mean values area averaged ocean heat content is provided for the Mediterranean Sea (30°N, 46°N; 6°W, 36°E) and is evaluated for topography deeper than 300m. '''CONTEXT''' Knowing how much and where heat energy is stored and released in the ocean is essential for understanding the contemporary Earth system state, variability and change, as the oceans shape our perspectives for the future. The quality evaluation of MEDSEA_OMI_OHC_area_averaged_anomalies is based on the “multi-product” approach as introduced in the second issue of the Ocean State Report (von Schuckmann et al., 2018), and following the MyOcean’s experience (Masina et al., 2017). Six global products and a regional (Mediterranean Sea) product have been used to build an ensemble mean, and its associated ensemble spread. The reference products are: • The Mediterranean Sea Reanalysis at 1/24 degree horizontal resolution (MEDSEA_MULTIYEAR_PHY_006_004, DOI: https://doi.org/10.25423/CMCC/MEDSEA_MULTIYEAR_PHY_006_004_E3R1, Escudier et al., 2020) • Four global reanalyses at 1/4 degree horizontal resolution (GLOBAL_MULTIYEAR_PHY_ENS_001_031): GLORYS, C-GLORS, ORAS5, FOAM • Two observation based products: CORA (INSITU_GLO_PHY_TS_OA_MY_013_052) and ARMOR3D (MULTIOBS_GLO_PHY_TSUV_3D_MYNRT_015_012). Details on the products are delivered in the PUM and QUID of this OMI. '''CMEMS KEY FINDINGS''' The ensemble mean ocean heat content anomaly time series over the Mediterranean Sea shows a continuous increase in the period 1993-2022 at rate of 1.38±0.08 W/m2 in the upper 700m. After 2005 the rate has clearly increased with respect the previous decade, in agreement with Iona et al. (2018). '''DOI (product):''' https://doi.org/10.48670/moi-00261