The upper ocean pycnocline (UOP) monthly climatology is based on the ISAS20 ARGO dataset containing Argo and Deep-Argo temperature and salinity profiles on the period 2002-2020. Regardless of the season, the UOP is defined as the shallowest significant stratification peak captured by the method described in Sérazin et al. (2022), whose detection threshold is proportional to the standard deviation of the stratification profile. The three main characteristics of the UOP are provided -- intensity, depth and thickness -- along with hydrographic variables at the upper and lower edges of the pycnocline, the Turner angle and density ratio at the depth of the UOP. A stratification index (SI) that evaluates the amount of buoyancy required to destratify the upper ocean down to a certain depth, is also included. When evaluated at the bottom of the UOP, this gives the upper ocean stratification index (UOSI) as discussed in Sérazin et al. (2022). Three mixed layer depth variables are also included in this dataset, including the one using the classic density threshold of 0.03 kg.m-3, along with the minimum of these MLD variables. Several statistics of the UOP characteristics and the associated quantities are available in 2°×2° bins for each month of the year, whose results were smoothed using a diffusive gaussian filter with a 500 km scale. UOP characteristics are also available for each profile, with all the profiles sorted in one file per month.

Monthly time series of Total Nitrogen [mg/l] from model data

Web portal providing wave energy forecast at the spatial resolution of 1/32°. Higher resolution forecasts (1/128°) are computed over ten sub-basins around the Italian coasts.

This dataset presents the resulting assessment grid (based on the EEA reference grid) with the classification of ecosystem health of the transitional, coastal and marine waters in the context of the Water Framework Directive (WFD) and the Marine Strategy Framework Directive (MSFD). This classification has been performed using the MESH+ (Marine EcoSystem Health) tool. The MESH+ tool builds on the EEA assessment tools developed and applied in the context of assessing the degree of contamination (CHASE+), eutrophication (HEAT+) and biodiversity (BEAT+) in Europe's seas (EEA, 2018a, 2019c; Vaughan et al., 2019). MESH+ makes use of the same data sets and threshold values used in these assessments but recombines these in a new framework that addresses 'ecosystem condition'. The overall area of interest used is based on the marine regions and subregions under the MSFD. Additionally, Norwegian (Barents Sea and Norwegian Sea) and Icelandic waters (’Iceland Sea’) have been added (see Surrounding seas of Europe). Note that within the North East Atlantic region only the subregions within EEZ boundaries (~200 nm) have been included. The spatial resolution of the assessment grid is 20 km x 20 km in coastal areas and 100 km x 100 km in offshore areas. This dataset underpins the findings and cartographic representations published in the report "Marine Messages II" (EEA, 2020): https://www.eea.europa.eu/publications/marine-messages-2

Annual time series of eel escapement, (2008-2011): • Time series of silver eel escapement biomass for rivers monitored by EU member state every 3 years since 2008, and as defined in their Eel Management Plans (EMPs) • Maps of silver eel escapement biomass per Eel Management Unit (EMU could be a river, basin district, a region or a whole

The impact of fishing on benthic habitats has previously been investigated however; a conclusive classification of potentially sensitive habitats per gear type does not exist. Currently only qualitative estimates of fishery impact using Broad-scale habitat maps are possible. Here a sensitivity matrix using both fishing pressure (fishing Intensity) and habitat sensitivity is employed to define habitat disturbance categories. The predominant fishing activities associated with physical abrasion of the seafloor area are from bottom contacting towed fishing gear. The swept area of the aforementioned gear in contact with the seabed is generally considered a function of gear width, vessel speed and fishing effort (ICES. 2015). The varying characteristics of fishing gear, their interaction with the sea floor and species being targeted; provide scope for differing interactions with subsurface (infaunal) and surface (epifaunal) dwelling communities. An evaluation of the abrasion pressure and habitat sensitivity split into surface and subsurface pressure allows greater insight to the ecological effects. Fishing intensity was calculated annually and based on the area of sea floor being swept (or swept area ratio SAR) by gear type. Calculations are based on SAR’s of gear types per area, per year. Fishing pressure ranks and habitat sensitivity ranks obtained from WGSFD working group (01 WGSFD - Report of the Working Group on Spatial Fisheries Data 2015) can be incorporated within a GIS environment to existing ICES fisheries data to provide habitat disturbance maps (fishing pressure maps+ habitat sensitivity maps) ICES. 2015. Report of the Working Group on Spatial Fisheries Data (WGSFD), 8–12 June 2015, ICES Headquarters, Copenhagen, Denmark. ICES CM 2015/SSGEPI:18. 150 pp.

The 4D Marine Heatwaves (MHW) atlas contains 4D (x, y, z, t) **daily temperature and marine heatwaves categories** for global region [82.875°S-89.875°N, 0.125°E-359.875°E], from 0 to 300m depth and a spatial resolution of 1/8°. It covers the period 1993-2022. The MHW atlas has been computed from the temperature 4D fields of the ARMOR3D global product delivered in the Copernicus Marine Service (MULTIOBS_GLO_PHY_TSUV_3D_MYNRT_015_012 - https://doi.org/10.48670/moi-00052 ). The MHW categories are derived from the Hobday’s method [Hobday et al.,2018]. Each MHW event is classified among four categories (moderate to extreme), identified in terms of multiples of the local difference between the 90th percentile and climatological values, and defined as moderate (1-2×, Category I), strong (2-3×, Category II), severe (3-4×, Category III), and extreme (>4×, Category IV). When the category is zero, this means that there is no MHW. The period 1993-2021 is used as a baseline for defining the climatology to be as close as possible to the 30-year period suggested by Hobday. This choice is motivated by the need of altimetry data to constrain the vertical temperature reconstruction, which is required for most ocean reanalyses as well. Additionally, ancillary data are provided together with the data. It consists of 4D daily **temperature climatology** and **90 percentiles of the temperature**. These fields have been used to compute the MHW categories. They are delivered over the same domain as the MHW atlas. ARMOR3D **temperature uncertainties** are also supplied as they can help users to select only the most reliable events in the database. This dataset was generated by CLS (Collecte Localisation satellite) and is distributed by Ifremer /CERSAT in the frame of the CAREHeat project (CAREHeat Website) funded by the European Space Agency (ESA).

The "EMODnet Digital Bathymetry (DTM) - 2016" 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 and Central Mediterranean Sea and Ionian Sea • Bay of Biscay, Iberian coast and North-East Atlantic • Adriatic Sea • Aegean - Levantine Sea (Eastern Mediterranean) • Azores - Madeira EEZ • Canary Islands • Baltic Sea • Black Sea • Norwegian – Icelandic seas The DTM is based upon more than 7700 bathymetric survey data sets and Composite DTMs that have been gathered from 27 data providers from 18 European countries and involving 169 data originators. The gathered survey data sets can be discovered and requested for access through the Common Data Index (CDI) data discovery and access service that also contains additional European survey data sets for global waters. The Composite DTMs can be discovered through the Sextant Catalogue service. Both discovery services make use of SeaDataNet standards and services and have been integrated in the EMODnet portal (https://emodnet.ec.europa.eu/en/bathymetry#bathymetry-services ). In addition, the EMODnet Map Viewer (https://emodnet.ec.europa.eu/geoviewer/ ) 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 1/8 * 1/8 arc minute of longitude and latitude (ca 230 * 230 meters) • option to view depth parameters of individual DTM cells and references to source data • option to download DTM in 16 tiles in different formats: EMO, EMO (without GEBCO data), ESRI ASCII, ESRI ASCII Mean Sea Level, XYZ, NetCDF (CF), RGB GeoTiff and SD • layer with a number of high resolution DTMs for coastal regions • layer with wrecks from the UKHO Wrecks database. The NetCDF (CF) DTM files are fit for use in a special 3D Viewer software package which is based on the existing open source NASA World Wind JSK application. It has been developed in the frame of the EU FP7 Geo-Seas project (another sibling of SeaDataNet for marine geological and geophysical data) and is freely available. The 3D viewer also supports the ingestion of WMS overlay maps. The SD files can also be used for 3D viewing by means of the freely available iView4De(Fledermaus) software. 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.

Daily and monthly surface wind analyses are determined as gridded wind products over global oceans, with regular spatial resolution of 0.25° in latitude and longitude. They are estimated from scatterometer wind retrievals (L2b data). According to the scatterometer sampling scheme, the objective method allowing the determination of regular in space surface wind fields uses remotely sensed observations as well as ECMWF analyses. The calculation of daily estimates uses ascending as well as descending available and valid retrievals. The objective method aims to provide daily-averaged gridded wind speed, zonal component, meridional component, wind stress and the corresponding components at global scale. The error associated to each parameter, related to the sampling impact and wind space and time variability, is provided too. Monthly wind analyses are calculated from daily estimates.