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.

'''This product has been archived''' '''Short description:''' Arctic sea ice thickness from merged SMOS and Cryosat-2 (CS2) observations during freezing season between October and April. The SMOS mission provides L-band observations and the ice thickness-dependency of brightness temperature enables to estimate the sea-ice thickness for thin ice regimes. On the other hand, CS2 uses radar altimetry to measure the height of the ice surface above the water level, which can be converted into sea ice thickness assuming hydrostatic equilibrium. '''DOI (product) :''' https://doi.org/10.48670/moi-00125

The abundance of ichthyoplankton in samples from dedicated plankton surveys by Cefas with positional and sample data. Surveys took place off the Western Coast of the UK and Ireland between 1986 and 2004. Series of cruises undertaken to contribute to the estimation of the spawning stock biomass of the western mackerel and horse mackerel stocks by plankton survey. The triennial mackerel egg surveys were begun in 1977 to estimate the SSB of the western mackerel stock. Since 1986 the surveys have also been used to estimate the SSB of horse mackerel. Plankton sampling is undertaken to estimate the egg production and trawling is carried out to estimate the mean fecundity of the mature female fish. Various designs of Gulf VII type samplers have been used with various apertures of nosecones and 270 micron nets. Samplers are now standardised to the 53cm version, fitted with 20cm aperture nosecones. Analysis at Cefas involved separating all fish eggs and larvae from samples. Where possible all eggs were identified. Eggs lacking identifiable features were measured. Where >100 eggs were found, sub-sampling was undertaken. Eggs that were unmeasured were apportioned across the size distribution of measured eggs. All mackerel and horse mackerel eggs were staged.

French Zostera Marina et Zostera Noltei abundance data are collected during monitoring surveys on the English Channel / Bay of Biscay coasts. Protocols are impletmented in the Water Framework Directive. Data are transmitted in a Seadatanet format (CDI + ODV) to EMODnet Biology european database. 35 ODV files have been generated from period 01/01/2004 to 31/12/2021 for Z. Marina and from 01/01/2011 to 31/12/2021 for Z. Noltei.  

'''DEFINITION''' Variations of the Mediterranean Outflow Water at 1000 m depth are monitored through area-averaged salinity anomalies in specifically defined boxes. The salinity data are extracted from several CMEMS products and averaged in the corresponding monitoring domain: * IBI-MYP: IBI_MULTIYEAR_PHY_005_002 * IBI-NRT: IBI_ANALYSISFORECAST_PHYS_005_001 * GLO-MYP: GLOBAL_REANALYSIS_PHY_001_030 * CORA: INSITU_GLO_TS_REP_OBSERVATIONS_013_002_b * ARMOR: MULTIOBS_GLO_PHY_TSUV_3D_MYNRT_015_012 The anomalies of salinity have been computed relative to the monthly climatology obtained from IBI-MYP. Outcomes from diverse products are combined to deliver a unique multi-product result. Multi-year products (IBI-MYP, GLO,MYP, CORA, and ARMOR) are used to show an ensemble mean and the standard deviation of members in the covered period. The IBI-NRT short-range product is not included in the ensemble, but used to provide the deterministic analysis of salinity anomalies in the most recent year. '''CONTEXT''' The Mediterranean Outflow Water is a saline and warm water mass generated from the mixing processes of the North Atlantic Central Water and the Mediterranean waters overflowing the Gibraltar sill (Daniault et al., 1994). The resulting water mass is accumulated in an area west of the Iberian Peninsula (Daniault et al., 1994) and spreads into the North Atlantic following advective pathways (Holliday et al. 2003; Lozier and Stewart 2008, de Pascual-Collar et al., 2019). The importance of the heat and salt transport promoted by the Mediterranean Outflow Water flow has implications beyond the boundaries of the Iberia-Biscay-Ireland domain (Reid 1979, Paillet et al. 1998, van Aken 2000). For example, (i) it contributes substantially to the salinity of the Norwegian Current (Reid 1979), (ii) the mixing processes with the Labrador Sea Water promotes a salt transport into the inner North Atlantic (Talley and MacCartney, 1982; van Aken, 2000), and (iii) the deep anti-cyclonic Meddies developed in the African slope is a cause of the large-scale westward penetration of Mediterranean salt (Iorga and Lozier, 1999). Several studies have demonstrated that the core of Mediterranean Outflow Water is affected by inter-annual variability. This variability is mainly caused by a shift of the MOW dominant northward-westward pathways (Bozec et al. 2011), it is correlated with the North Atlantic Oscillation (Bozec et al. 2011) and leads to the displacement of the boundaries of the water core (de Pascual-Collar et al., 2019). The variability of the advective pathways of MOW is an oceanographic process that conditions the destination of the Mediterranean salt transport in the North Atlantic. Therefore, monitoring the Mediterranean Outflow Water variability becomes decisive to have a proper understanding of the climate system and its evolution (e.g. Bozec et al. 2011, Pascual-Collar et al. 2019). The CMEMS IBI-OMI_WMHE_mow product is aimed to monitor the inter-annual variability of the Mediterranean Outflow Water in the North Atlantic. The objective is the establishment of a long-term monitoring program to observe the variability and trends of the Mediterranean water mass in the IBI regional seas. To do that, the salinity anomaly is monitored in key areas selected to represent the main reservoir and the three main advective spreading pathways. More details and a full scientific evaluation can be found in the CMEMS Ocean State report Pascual et al., 2018 and de Pascual-Collar et al. 2019. '''CMEMS KEY FINDINGS''' The absence of long-term trends in the monitoring domain Reservoir (b) suggests the steadiness of water mass properties involved on the formation of Mediterranean Outflow Water. Results obtained in monitoring box North (c) present an alternance of periods with positive and negative anomalies. The last negative period started in 2016 reaching up to the present. Such negative events are linked to the decrease of the northward pathway of Mediterranean Outflow Water (Bozec et al., 2011), which appears to return to steady conditions in 2020 and 2021. Results for box West (d) reveal a cycle of negative (2015-2017) and positive (2017 up to the present) anomalies. The positive anomalies of salinity in this region are correlated with an increase of the westward transport of salinity into the inner North Atlantic (de Pascual-Collar et al., 2019), which appear to be maintained for years 2020-2021. Results in monitoring boxes North and West are consistent with independent studies (Bozec et al., 2011; and de Pascual-Collar et al., 2019), suggesting a westward displacement of Mediterranean Outflow Water and the consequent contraction of the northern boundary. Note: The key findings will be updated annually in November, in line with OMI evolutions. '''DOI (product):''' https://doi.org/10.48670/moi-00258

The Coastal Zones (CZ) LC/LU product for 2018 is providing a detailed Land Cover / Land Use (LC/ LU) dataset for areas along the coastline of the EEA38 countries and the United Kingdom, with reference year 2018 for the classification. This product monitors landscape dynamics in European coastal territory to an inland depth of 10 km with a total area of approximately 730,000 km², with all the relevant areas (estuaries, coastal lowlands, nature reserves). The production of the coastal zone layers was coordinated by the European Environment Agency (EEA) in the frame of the EU Copernicus programme, as part of the Copernicus Land Monitoring Service (CLMS) Local Component. The Coastal Zones product covers a buffer zone of coastline derived from EU-Hydro v1.1. Land Cover/Land Use (LC/LU) layer is extracted from Very High Resolution (VHR) satellite data and other available data. The class definitions follow the pre-defined nomenclature on the basis of Mapping and Assessment of Ecosystems and their Services (MAES) typology of ecosystems (Level 1 to Level 4) and CORINE Land Cover adapted to the specific characteristics of coastal zones. The classification provides 71 distinct thematic classes with a Minimum Mapping Unit (MMU) of 0.5 ha and a Minimum Mapping Width (MMW) of 10 m. The product is available for the 2012 and 2018 reference year including change mapping. This CZ dataset is distributed in vector format, in a single OGC GeoPackage SQLite file covering the area of interest.

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.