EMODnet Chemistry aims to provide access to marine chemistry data sets and derived data products concerning eutrophication, ocean acidification, contaminants and litter. The chosen parameters are relevant for the Marine Strategy Framework Directive (MSFD), in particular for descriptors 5, 8, 9 and 10. The datasets contain standardized, harmonized and validated data collections from seafloor litter. Datasets concerning seafloor litter data are loaded in a central database after a semi-automated validation phase. Once loaded, a data assessment is performed in order to check data consistency and potential errors are corrected thanks to a feedback loop with data originators. EMODnet seafloor litter data and database are hosted and maintained by ‘Istituto Nazionale di Oceanografia e di Geofisica Sperimentale, Division of Oceanography (OGS/NODC)’ from Italy. For seafloor litter, the harmonized datasets contain all unrestricted EMODnet Chemistry data on seafloor litter data. Data are formatted following Guidelines and forms for gathering marine litter data, which can be found at: https://dx.doi.org/10.6092/15c0d34c-a01a-4091-91ac-7c4f561ab508 The updated vocabularies of admitted values are available at: https://vocab.seadatanet.org/search https://vocab.ices.dk/ The harmonized datasets can be downloaded as EMODnet Sea-floor litter data format version 1.0, which is a csv file, tab separated values.

This visualization product displays the size of litter in percent per net per year from specific protocols different 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 a very specific protocol such as the Volvo Ocean Race (VOR) or Oceaneye. To calculate percentages for each size, formula applied is: Size (%) = (∑number of particles of each size)*100 / (∑number of particles of all size) When the number of micro-litters was not filled or was equal to zero, it was not possible to calculate the percentage. Standard vocabularies for micro-litter size classes are taken from Seadatanet's H03 library (https://vocab.seadatanet.org/v_bodc_vocab_v2/search.asp?lib=H03 ). Different protocols with different degrees of precision were used to classify the sampled micro-litters. Consequently, on the map, the distribution of micro-litter in the size classes depends on the protocol applied during the survey. 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 National Oceanographic Data Centre (NODC) for this area.

This daily High-Resolution (HR) Level 3 gridded wind product is derived from Copernicus Sentinel-1 SAR (Synthetic Aperture Radar) observations, over the North Western Atlantic ("ATL" area). It is based on the European Space Agency (ESA) Level-2 OCN products at the highest available resolution. Although L2-OCN products already contain wind vectors, those are calculated using the CMOD5.n Geophysical Model Function (GMF) applied to the co-polarized (co-pol) VV channel (emitting in Vertical polarization and receiving in Vertical polarization). This VV GMF was mapped from scatterometer sensors (Hersbach et al., 2007) which are only able to use co-pol measurements. However, these co-pol GMF are known to lose sensitivity for wind above 20 m/s. Therefore, wind based on such GMF alone, are known to under-estimate wind speed (Polverari et al., 2022). For the L3 products winds based on SAR, we take advantage of the available cross-polarized (cross-pol) VH channel (emitting in Vertical polarization and receiving in Horizontal polarization) for which GMF were specifically derived based on C-Band SAR (Mouche et al., 2017, Mouche et al., 2019). Winds estimated from the combination of both the co-pol and cross-pol channels are referred to as dual-polarization (or dual-pol) winds. As shown in Mouche et al. (2019), taking advantage of the dual polarization strongly improves the wind estimation for high wind conditions thanks to the much greater VH channel sensitivity compared to VV. These new wind estimations are then gridded with a 0.012 degree resolution (between 0.5 and 1.2 km in zonal direction depending on the latitude and 1.3 km in meridional direction) using a cylindrical equidistant projection, independently for ascending and descending satellite passes and for each satellite (so 4 wind fields are available per day for two satellites). This dataset is generated over all Sentinel-1 mission time series starting from March 2018 and updated in delayed mode with a 4-months delay. It is also produced for 4 other different European areas. This dataset is produced and disseminated in the frame of Copernicus Marine Service.

Moving 6-year analysis of Water body dissolved inorganic nitrogen 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 1971/1976 until 2019/2024. Observation data span from 1971 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 400km 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.

This dataset contains the dynamical outputs of a global ocean simulation coupling dynamics and biogeochemistry at ¼° over the year 2019. The simulation has been performed using the coupled circulation/ecosystem model NEMO/PISCES (https://www.nemo-ocean.eu/), which is here enhanced to perform an ensemble simulation with explicit simulation of modeling uncertainties in the physics and in the biogeochemistry. This dataset is one of the 40 members of the ensemble simulation. This study was part of the Horizon Europe project SEAMLESS (https://seamlessproject.org/Home.html), with the general objective of improving the analysis and forecast of ecosystem indicators.   See Popov et al. (https://os.copernicus.org/articles/20/155/2024/) for more details on the study.

The BioSWOT-Med campaign (Doglioli et al., 2023) was conducted aboard R/V L’Atalante from April 20 to May 15, 2023 in the Northwestern Mediterranean Sea, in the region of the North Balearic Front (NBF) to study interactions between fine-scale oceanic circulation and biogeochemical processes.  Three water masses were sampled across the NBF, northern ('A'), southern ('B'), and frontal ('F'). Each Lagrangian station consisted of a 24-hour sampling period following the displacement of a water parcel (Doglioli et al., 2024). Vertical profiles down to 500 m were collected every 6 hours at 06:00 ('T1'), 12:00 ('T2'), 18:00 ('T3'), and 00:00 ('T4') UTC, for a total of 28 Lagrangian stations: first between April~24-28 (A1, F1, B1), and again between May~4-7 (B2, F2, A2), with a final station in southern waters (B3) on May~12-13. B2 and B3 stations were located inside an anticyclonic eddy. Hydrological profiles were obtained using a Sea-Bird CTD, with data averaged to a 1~m vertical resolution, they include potential temperature (°C), practical salinity, fluorescence-derived chlorophyll-a (µg/L) and oxygen (µmol/kg).  Samples for nitrate + nitrite and phosphate (µM) were collected from Niskin bottles and analyzed onboard within 2-12~hours using a segmented flow analyzer (AAIII HR Seal Analytical) following (Aminot et al., 2007). Quantification limits (QL) were 0.05 µM for nitrate and 0.02 µM for phosphate. Phosphate concentrations at a nanomolar level analyses were performed in the laboratory using a high-sensitivity method combining a 1 m Liquid Waveguide Capillary Cell (LWCC) and an auto-analyzer (Zhang et al. 2002), achieving a detection limit of 0.002µM.  A BGC-Argo float (WMO: 1902605 - Provor CTS4 SUNA) equipped with a CTD and SUNA nitrate sensor was deployed near station B2 and sampled the anticyclonic eddy. To better resolve the photic and nutricline layers, the standard sampling cycle was modified to a 6-hour frequency, reaching depths of 300-400~m. The BGC-Argo float nitrate dataset spans May~2-16 and includes 55~profiles, with a 0.5 µM limit of quantification. It passed through a nitrate calibration procedure against 8 ship-made  profiles at B2 and B3. Data export in NetCDF format - Dataset at the 7 Lagrangian stations (28 vertical profiles for each variable, 4 at each station):  ‘BioSWOT-Med_LS_Date_Time.nc’ (with day, time, longitude and latitude);  ‘BioSWOT-Med_LS_Nutrients.nc’ (with nitrate, phosphate and phosphate at nanomolar level concentrations and depths);  'BioSWOT-Med_LS_CTD.nc' (with temperature in situ, practical salinity, chlorophyll-a and oxygen concentrations, photosynthetically active radiations and depth). - Dataset of the BGC-Argo float including 55 vertical profiles recorded between May 2 and 16:  'BioSWOT-Med_BGC-Argo' (with day and time, longitude, latitude; nitrate concentrations with associated depth; temperature in situ and practical salinity associated depth; chlorophyll-a concentrations with associated predepthssure; and oxygen concentrations with associated depth). Contact list  Aude Joël (aude.joel@mio.osupytheas.fr), Sandra Nunige (sandra.nunige@mio.osupytheas.fr, for ship-made nutrient dataset), Riccardo Martellucci (rmartellucci@ogs.it, for the BGC-Argo float dataset) and Andrea Doglioli (andrea.doglioli@mio.osupytheas.fr, for the BioSWOT-Med cruise). References Aminot, A., & Kérouel, R. 2007. Dosage automatique des nutriments dans les eaux marines: méthodes en flux continu. Méthodes d’analyse en milieu marin. Ifremer. Doglioli, A.M., & Gregori, G. 2023. BioSWOT-Med cruise, RV L’Atalante. doi:10.17600/18002392. Doglioli, A., Grégori, G., D’Ovidio, F., Bosse, P. E., A., Carlotti, F., Lescot, M.,. . . Waggonet, E. (2024). Bioswot med. biological applicati.ons of the satellite surface water and ocean topography in the mediterranean. ref. rapport de campagne. université aix-marseille. (doi:10.13155/100060) Zhang, J.Z., & Chi, J. 2002. Automated analysis of nanomolar concentrations of phosphate in natural waters with liquid waveguide. Environ Sci Technol., 1;36(5), 1048–53. doi: 10.1021/es011094v.  

The ARCHYD dataset, which have been collected since 1988, represents the longest long-term hydrologic data sets in Arcachon Bay. The objectives of this monitoring programme are to assess the influence of oceanic and continental inputs on the water quality of the bay and their implications on biological processes. It also aims to estimate the effectiveness of management policies in the bay by providing information on trends and/or shifts in pressure, state, and impact variables. Sampling is carried on stations spread across the entire bay, but since 1988, the number and location of stations have changed slightly to better take into account the gradient of ocean and continental inputs. In 2005, the ARCHYD network was reduced to 8 stations that are still sampled by Ifremer to date. All the stations are sampled at a weekly frequency, at midday, alternately around the low spring tide and the high neap tide. Data are complementary to REPHY dataset. Physico-chemical measures include temperature, salinity, turbidity, suspended matters (organic, mineral), dissolved oxygen and dissolved inorganic nutrients (ammonium, nitrite+nitrate, phosphate, silicate). Biological measures include pigment proxies of phytoplankton biomass and state (chlorophyll a and phaeopigment).

This daily High-Resolution (HR) Level 3 gridded wind product is derived from Copernicus Sentinel-1 SAR (Synthetic Aperture Radar) observations, over the Mediterranean Sea ("MED" area). It is based on the European Space Agency (ESA) Level-2 OCN products at the highest available resolution. Although L2-OCN products already contain wind vectors, those are calculated using the CMOD5.n Geophysical Model Function (GMF) applied to the co-polarized (co-pol) VV channel (emitting in Vertical polarization and receiving in Vertical polarization). This VV GMF was mapped from scatterometer sensors (Hersbach et al., 2007) which are only able to use co-pol measurements. However, these co-pol GMF are known to lose sensitivity for wind above 20 m/s. Therefore, wind based on such GMF alone, are known to under-estimate wind speed (Polverari et al., 2022). For the L3 products winds based on SAR, we take advantage of the available cross-polarized (cross-pol) VH channel (emitting in Vertical polarization and receiving in Horizontal polarization) for which GMF were specifically derived based on C-Band SAR (Mouche et al., 2017, Mouche et al., 2019). Winds estimated from the combination of both the co-pol and cross-pol channels are referred to as dual-polarization (or dual-pol) winds. As shown in Mouche et al. (2019), taking advantage of the dual polarization strongly improves the wind estimation for high wind conditions thanks to the much greater VH channel sensitivity compared to VV. These new wind estimations are then gridded with a 0.012 degree resolution (between 0.5 and 1.2 km in zonal direction depending on the latitude and 1.3 km in meridional direction) using a cylindrical equidistant projection, independently for ascending and descending satellite passes and for each satellite (so 4 wind fields are available per day for two satellites). This dataset is generated over all Sentinel-1 mission time series starting from March 2018 and updated in delayed mode with a 4-months delay. It is also produced for 4 other different European areas. This dataset is produced and disseminated in the frame of Copernicus Marine Service.

Seasonal climatology of Water body chlorophyll-a for Loire river for the period 1971-2024 and for the following seasons: - winter: January-March, - spring: April-June, - summer: July-September, - autumn: October-December. Observation data span from 1971 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): 14000 (winter), 52000 (spring), 42000 (summer), 125000 (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: mg/m3.