'''This product has been archived'''                For operationnal and online products, please visit https://marine.copernicus.eu '''Short description:''' Experimental altimeter satellite along-track sea surface heights anomalies (SLA) computed with respect to a twenty-year [1993, 2012] mean with a 5Hz (~1.3km) sampling. All the missions are homogenized with respect to a reference mission (see QUID document or http://duacs.cls.fr [http://duacs.cls.fr] pages for processing details). The product gives additional variables (e.g. Mean Dynamic Topography, Dynamic Atmosphic Correction, Ocean Tides, Long Wavelength Errors, Internal tide, …) that can be used to change the physical content for specific needs This product was generated as experimental products in a CNES R&D context. It was processed by the DUACS multimission altimeter data processing system. '''DOI (product) :''' https://doi.org/10.48670/moi-00137

This data set presents the resulting assessment grid (based on the EEA reference grid) with the classification of chemical status of the transitional, coastal and marine waters in the context of the Water Framework Directive (WFD) and the Marine Strategy Framework Directive (MSFD), providing a mapping of contamination 'problem areas' and 'non-problem areas' based on measurements of biological effects. This classification has been performed using the CHASE+ tool, with classifications of the of contaminant status of indicators of biological effects. The status is evaluated in five classes, where NPAhigh and NPAgood are recognised as ‘non-problem areas’ and PAmoderate, PApoor and PAbad are recognised as ‘problem areas’. Monitoring biological effects is restricted to a few indicators (e.g. imposex) and data coverage is currently limited. Biological effects have thus been addressed in only 134 assessment units, mostly in the Baltic Sea, the North Sea and the North-East Atlantic Ocean. This data set underpins the findings and cartographic representations published in the EEA report “Contaminants in Europe’s seas” (No 25/2018). See the mentioned report for further information.

Combination MPAs and monitoring stations for biodiversity elements

This vector dataset represents the benthic broad habitat types in Europe Seas potentially affected by the ship wakes. When navigating, the propellers of ships generate a turbulent mixing of the water that can produce sediment re-suspension in soft bottoms of shallow areas. This can increase the turbidity in those areas, affecting the seafloor organisms (especially those that are directly dependent on light, such as aquatic plants). It may also contribute to an increase of the the eutrophication level of the ecosystem (since the turbid waters may become warmer, which may turn into a reduction of dissolved oxygen in water). Finally, turbidity can produce an increase in the inputs of contaminants and microbial pathogens, since those can become attached to the suspended solids. The dataset has been prepared in the context of the development of the first European Maritime Transport Environmental Report (https://www.eea.europa.eu/publications/maritime-transport).

This dataset comprises the global frequency, classification and distribution of marine heat waves (MHWs) from 1996-2020, in Chauhan et al. 2023 (https://doi.org/10.3389/fmars.2023.1177571). The classification was done based on their attributes and using different baselines. Daily SST values were extracted from the NOAA-OISST v2 high-resolution (0.25°) dataset from 1982-2020. MHWs were detected using the method presented by Hobday et al. 2016 (https://doi.org/10.1016/j.pocean.2015.12.014), and by using the 95th percentile of the accumulated temperature distribution to flag the extreme events. A shifting baseline of 8-year rolling period was selected between the years 1982-1996, since this period shows relatively stable maximum values of temperature across different ocean regions. The shifting baseline aims to account for the decadal changes of westerly winds, temperatures and ocean gyres circulations. The classification was done using the KMeans clustering algorithm to identify the relevant features of MHWs and classify them into separate groups based on feature similarities. This algorithm takes MHW features, namely duration, maximum intensity, rate onset and rate decline, as input vectors and applies clustering in the 4-dimensional feature space where each data point represents an MHW event. Note that all the MHWs features are standardized because unequal variances can put more weight on variables with smaller variances. This record comprehends the geospatial datasets of: Average number of MHW days per year (i.e., the sum of all MHW days divided by the total number of years, 1996-2020). Average cumulative intensity per year (i.e., the sum of cumulative intensity divided by the total number of years, 1996-2020). Total number of MHW events across the different periods averaged on the total number of years (1989-2020). The period 1982-1988 was only used as an initial baseline without calculating MHWs. Spatial distribution of three MHW categories: moderate MHWs, abrupt and Intense MHWs and extreme MHWs; displaying the total number of MHW days normalized by the number of years considered (i.e., 1989-2020). Distribution of Extreme MHWs across the different periods (A) 1989-1996, (B) 1997-2004, (C) 2005-2012, (D) 2013-2020. The relative frequency (γ) is a ratio of extreme MHWs in a specific period and all extreme MHWs in the same cluster for all periods.

The "EMODnet Digital Bathymetry (DTM) - 2018" is a multilayer bathymetric product for Europe’s sea basins covering: • the Greater North Sea, including the Kattegat and stretches of water such as Fair Isle, Cromarty, Forth, Forties,Dover, Wight, and Portland • the English Channel and Celtic Seas • Western Mediterranean, the Ionian Sea and the Central Mediterranean Sea • Iberian Coast and Bay of Biscay (Atlantic Ocean) • Adriatic Sea (Mediterranean) • Aegean - Levantine Sea (Mediterranean). • Madeira and Azores (Macaronesia) • Baltic Sea • Black Sea • Norwegian and Icelandic Seas • Canary Islands (Macaronesia) • Arctic region and Barentz Sea The DTM is based upon more than 9400 bathymetric survey data sets and Composite DTMs that have been gathered from 49 data providers from 24 countries riparian to European seas. Also Satellite Derived Bathymetry data products have been included derived from Landsat 8 satellite images. The source reference layer in the portal viewing service gives metadata of the data sets used with their data providers; the metadata also acknowledges the data originators. The incorporated survey data sets itself can be discovered and requested for access through the Common Data Index (CDI) data discovery and access service that in September 2018 contained > 27.000 survey data sets from European data providers for global waters. This discovery service makes use of SeaDataNet standards and services and have been integrated in the EMODnet portal (https://emodnet.ec.europa.eu/en/bathymetry#bathymetry-services ). The Composite DTMs are described using the Sextant Catalogue Service that makes also use of SeaDataNet standards and services. Their metadata can be retrieved through interrogating the Source Reference map in the Central Map Viewing service (https://emodnet.ec.europa.eu/geoviewer/ ). In addition, the EMODnet Map Viewer gives users wide functionality for viewing and downloading the EMODnet digital bathymetry such as: • water depth (refering to the Lowest Astronomical Tide Datum - LAT) in gridded form on a DTM grid of 1/16 * 1/16 arc minute of longitude and latitude (ca 115 * 115 meters) • option to view depth parameters of individual DTM cells and references to source data • option to download DTM in 58 tiles in different formats: EMO, EMO (without GEBCO data), ESRI ASCII, ESRI ASCII Mean Sea Level, XYZ, NetCDF (CF), RGB GeoTiff and SD • option to visualize the DTM in 3D in the browser without plug-in • layer with a number of high resolution DTMs for coastal regions • layer with wrecks from the UKHO Wrecks database. The EMODnet DTM is also available by means of OGC web services (WMS, WFS, WCS, WMTS), which are specified at the EMODnet Bathymetry portal. The original datasets themselves are not distributed but described in the metadata services, giving clear information about the background survey data used for the DTM, their access restrictions, originators and distributors and facilitating requests by users to originator.

EMODnet Chemistry aims to provide access to marine chemistry datasets and derived data products concerning eutrophication, acidity and contaminants. The importance of the selected substances and other parameters relates to the Marine Strategy Framework Directive (MSFD). This aggregated dataset contains all unrestricted EMODnet Chemistry data on potential hazardous substances, despite the fact that some data might not be related to pollution (e.g. collected by deep corer). Temperature, salinity and additional parameters are included when available. It covers the Northeast Atlantic Ocean (40W). Data were harmonised and validated by '‘IFREMER / IDM / SISMER - Scientific Information Systems for the SEA’ in France. The dataset contains water (profiles), sediment (profiles and timeseries) and biota (timeseries). The temporal coverage is 1974–2018 for water measurements, 1966–2022 for sediment measurements and 1979–2023 for biota measurements. Regional datasets concerning contaminants are automatically harvested and the resulting collections are harmonised and validated using ODV Software and following a common methodology for all sea regions ( https://doi.org/10.6092/8b52e8d7-dc92-4305-9337-7634a5cae3f4 ). Parameter names are based on P01 vocabulary, which relates to BODC Parameter Usage Vocabulary and is available at: https://vocab.nerc.ac.uk/search_nvs/P01/ . The harmonised dataset can be downloaded as as an ODV spreadsheet, which is composed of a metadata header followed by tab separated values. This spreadsheet can be imported into ODV Software for visualisation (more information can be found at: https://www.seadatanet.org/Software/ODV ). In addition, the same dataset is offered also as a txt file in a long/vertical format, in which each P01 measurement is a record line. Additionally, there are a series of columns that split P01 terms into subcomponents (substance, CAS number, matrix...).This transposed format is more adapted to worksheet applications (e.g. LibreOffice Calc).