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  • The SWOT KaRIn Level-3 Wind Wave product (L3_LR_WIND_WAVE) is an innovative product derived from the Unsmoothed L3_LR_SSH product (https://doi.org/10.24400/527896/A01-2024.003), which is based on the algorithm presented by Ardhuin et al. (2024; https://doi.org/10.1029/2024GL109658). L3_LR_WIND_WAVE takes advantage of the KaRIn Low Rate (LR) chain's ability to resolve waves with wavelengths greater than 500 meters (approximately 18 seconds) and provides detailed information on the characteristics of these wave regimes. This includes significant wave height (SWH), dominant wavelength, and wave propagation direction. These regimes are associated with long-period swells and extreme events that play a critical role in ocean dynamics, coastal processes, and maritime operations. The SWOT L3_LR_WIND_WAVE product is organized into two subproducts, "Light" and "Extended". The L2_LR_SSH "Light" product is described in this metadata sheet. The "Light" L3_LR_WIND_WAVE (also known as the "lightweight" product) includes the SWOT L3_LR_SSH 250-m SSHA spectrum, corrected for instrumental effects and expressed in both Cartesian and polar coordinates. It also includes the swell partition of the spectrum and the wave parameters integrated over this partition, for both the WW3 model and the KaRIn model (significant wave height, wavelength, and direction). The "Extended" L3_LR_WIND_WAVE includes the aforementioned variables plus the WW3 spectrum in the same frequency grid as the KaRIn spectrum and the KaRIn transfer functions used for correction, as well as some parameters derived from KaRIn observations (e.g., coherence, mean backscatter).

  • This visualization product displays the fishing & aquaculture related plastic items abundance of marine macro-litter (> 2.5cm) per beach per year from Marine Strategy Framework Directive (MSFD) monitoring surveys. 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 MSFD surveys only (exclusion of other 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); - Normalization of survey lengths to 100m & 1 survey / year: in some case, the survey length was not exactly 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. Sometimes the survey length was null or equal to 0. Assuming that the MSFD protocol has been applied, the length has been set at 100m in these cases. Percentiles 50, 75, 95 & 99 have been calculated taking into account plastic bags related items from MSFD 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.

  • This visualization product displays marine macro-litter (> 2.5cm) material categories percentages per beach per year from non-MSFD monitoring surveys, research & cleaning operations. 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; - Exclusion of surveys without associated length; - Some litter types like organic litter, small fragments (paraffin and wax; items > 2.5cm) and pollutants have been removed. 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 the "feaces" category: it concerns more exactly the items of dog excrements in bags of the OSPAR (item code: 121) and ITA (item code: IT59) reference lists; - 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 items (normalized by 100 m) = Number of litter per items x (100 / survey length) Then, this normalized number of items is summed to obtain the total normalized number of litter for each survey. To calculate the percentage for each material category, formula applied is: Material (%) = (∑number of items (normalized at 100 m) of each material category)*100 / (∑number of items (normalized at 100 m) of all categories) The material categories differ between reference lists (OSPAR, TSG-ML, UNEP, UNEP-MARLIN, JLIST). In order to apply a common procedure for all the surveys, the material categories have been harmonized. 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.

  • '''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

  • Seasonal climatology of Water body silicate for Loire river for the period 1950-2024 and for the following seasons: - winter: January-March, - spring: April-June, - summer: July-September, - autumn: October-December. Observation data span from 1950 to 2024. Depth levels (m): [0.0, 2.0, 4.0, 6.0, 8.0, 10.0, 15.0, 20.0, 25.0, 30.0, 35.0, 40.0, 45.0, 50.0, 60.0, 70.0, 80.0, 90.0, 100.0, 110.0, 120.0, 130.0]. 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 15 sec topography for the spatial connectivity of water masses. The horizontal resolution of the produced DIVAnd maps is 0.01 degrees. Horizontal correlation length is defined seasonally (in meters): 133000 (winter), 180000 (spring), 150000 (summer), 210000 (autumn). Vertical correlation length was optimized and vertically filtered and a seasonally-averaged profile was used (DIVAnd.fitvertlen). 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: the vertically-filtered data mean profile is substracted from the data. Detrending of data: no, advection constraint applied: no. Units: umol/l.

  • The ESA Sea State Climate Change Initiative (CCI) project has produced global daily merged multi-sensor time-series of along-track satellite altimeter significant wave height data (referred to as Level 3 (L3) data) with a particular focus for use in climate studies. This dataset contains the Version 4 Remote Sensing Significant Wave Height product, which provides along-track data at approximately 6 km spatial resolution. It has been generated from upstream Sea State CCI L2P products, edited and merged into daily products, retaining only valid and good quality measurements from all altimeters over one day, with simplified content (only a few key parameters). This is close to what is delivered in Near-Real Time by the CMEMS (Copernicus - Marine Environment Monitoring Service) project. It covers the date range from 1991-2023. The altimeter data used in the Sea State CCI dataset v3 come from multiple satellite missions (ERS-1, ERS-2,TOPEX-Poseidon, Envisat, CryoSat-2, Jason-1, Jason-2, Jason-3, SARAL, Sentinel-3 A, Sentinel-3 B, Sentinel-6 A), therefore spanning over a wider time range than previous version 3. The missions already retracked (with WHALES) in version 3 were not reprocessed, but extended when applicable. Many altimeters are bi-frequency (Ku-C or Ku-S) and only measurements in Ku band were used, for consistency reasons, being available on each altimeter but SARAL (Ka band). The version 4 of this dataset now supersedes the previous version 3.

  • This visualization product displays the single use plastics (SUP) related items abundance of marine macro-litter (> 2.5cm) per beach per year from non-MSFD monitoring surveys, research & cleaning operations. 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 processing 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 SUP 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). The selection was adapted to the Joint list of litter categories SUP identification and therefore contains some differences with the selection made for previously published versions of this product; - 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 SUP related items of the survey (normalized by 100 m) = Number of SUP related items of the survey x (100 / survey length) Then, this normalized number of SUP related items is summed to obtain the total normalized number of SUP related items for each survey. Finally, the median abundance of SUP related items for each beach and year is calculated from these normalized abundances of SUP related items per survey. Percentiles 50, 75, 95 & 99 have been calculated taking into account SUP 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.

  • This In Situ delayed mode product integrates the best available version of in situ oxygen, chlorophyll / fluorescence and nutrients data. The latest version of Copernicus delayed-mode BGC (bio-geo-chemical) product is also distributed from Copernicus Marine catalogue.

  • 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 spatial distribution of fishing related items 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 fishing related items (number of items per km²) = ∑Number of fishing related items / Swept area (km²) Then a grid with 30km x 30km cells was used to calculate the weighted mean of densities in each cell from the formula : Weighted mean (number of items per km²) = ∑ (Distance (km) * Density (number of items per km²)) / ∑ Distance (km) Percentiles 50, 75, 95 & 99 were calculated taking into account data for all years. More information on data processing and calculation are 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. This work is based on the work presented in the following scientific article: O. Gerigny, M. Brun, M.C. Fabri, C. Tomasino, M. Le Moigne, A. Jadaud, F. Galgani, Seafloor litter from the continental shelf and canyons in French Mediterranean Water: Distribution, typologies and trends, Marine Pollution Bulletin, Volume 146, 2019, Pages 653-666, ISSN 0025-326X, https://doi.org/10.1016/j.marpolbul.2019.07.030.