The North Atlantic and Arctic Isopoda dataset contains three parts: 1. Distribution records collected from literature; 2. Distribution records of specimens collected by the BIOICE project (Benthic Invertebrates of Icelandic waters 1992-2004); 3. Distribution records of specimens collected by the IceAGE project (Icelandic marine animals: Genetics and Ecology, since 2011). This dataset contains distribution data regarding the 3nd group, isopods occurrences sampled during the IceAGE project

The "EMODnet Digital Bathymetry (DTM)- 2022" 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 21937 bathymetric survey data sets and Composite DTMs that have been gathered from 64 data providers from 28 countries riparian to European seas and beyond. Also Satellite Derived Bathymetry data products have been included fro Landsat 8 and Sentinel satellite images. Areas not covered by observations are completed by integrating GEBCO 2022 and IBCAO V4. 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 December 2022 contained > 41.000survey data sets from European data providers 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 1/16 * 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: ESRI ASCII, XYZ, EMODnet CSV, NetCDF (CF), 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.

As part of the STeP project (STorfjorden Polynya multidisciplinary study), two moorings, M1 and M2, were deployed in Storfjorden (Svalbard) on July 14, 2016 from the French R/V L’Atalante and were recovered one year later, on September 28, 2017, from the French R/V Pourquoi-Pas?. The two moorings, deployed a few hundred meters apart at 78°N and 20°E at a depth of 100m, documented the formation of dense Brine-enriched Shelf Water (BSW).  The moorings included both physical oceanography (PO) and biogeochemistry sensors. The present dataset is composed of PO data only: the 3 components of the currents, backscatter, salinity, temperature and dissolved oxygen. PO sensors on M1, spanning the whole water column, included 6 Seabird SBE37 microcat (CTD),  15 RBR solo (T), and 1 RBR duet (TD) for hydrography, while currents were monitored with a RDI WH 300kHz upward looking ADCP and 1 Nortek Aquadopp underneath. PO sensors on the shorter M2 mooring included 1 Seabird SBE63 (CTD-O2), 1 RBR solo (T) and 1 RBR duo (TD). Data have been calibrated and validated and the different steps of this processing are discussed in the technical report provided with the dataset. Two netcdf4 files are provided for M1: one for hydrography (STEP2016_M1_hydrography.nc), the other one (STEP2016_M1_current.nc)  for currents and backscatter. Only one netcdf4 files (STEP2016_M2_hydrography.nc) is provided for the shorter M2. Temperature and salinity data from SBE sensors have been interpolated on a common time grid with a 20’ time step. Likewise temperature data from RBR are provided on a 30” time grid. A merged SBE-RBR dataset has also been built for increased vertical resolution, providing temperature every 20’. ADCP data are provided on a 100’ time grid. The user is referred to the technical report provided with the dataset for further information on the different fields. Important Note: This submission has been initially submitted to SEA scieNtific Open data Edition (SEANOE) publication service and received the recorded DOI. The metadata elements have been further processed (refined) in EMODnet Ingestion Service in order to conform with the Data Submission Service specifications.

Running 6-year analysis of Water body phosphate in the Baltic Sea. Four seasons (March-May, June-August, September-November, December-February). Every year of the time dimension corresponds to a 6-year centred average. Periods span between 1975-2021. Analyses for depths (m) (HELCOM standard depths): 0, 5, 10, 15, 20, 30, 40, 50, 60, 70, 80, 90, 100, 125, 150, 175, 200, 225, 250, 275, 300. Data Sources: observational data from SeaDataNet/EMODnet Chemistry Data Network. Description of DIVA analysis: Geostatistical data analysis by DIVAnd (Data-Interpolating Variational Analysis in n dimensions) tool. GEBCO_08 Grid (30 arc-seconds) topography is used for the contouring preparation. Files contain analysed fields, error fields and combined field with the deepest value for each grid point selected. Also pre-masked fields using relative error threshold 0.3 and 0.5 are included. In the analyses the horizontal correlation length is fixed to 80 km and decreasing towards the coastline, the vertical correlation length is varying with depth. Signal to noise ratio is fixed to 1.0. Background fields were created using data for the given time period and season. Log transformation was used in the analyses. No detrending, advection constraints or weighting are applied. Unit is umol/l.

This dataset presents monthly gridded sea ice and ocean parameters for the Arctic derived from the European Space Agency's satellite CryoSat-2. Parameters include sea ice freeboard, sea ice thickness, sea ice surface roughness, mean sea surface height, sea level anomaly, and geostrophic circulation. Data are provided as monthly grids with a resolution of 25 km, mapped onto the NSIDC EASE2-Grid, covering the Arctic region north of 50 degrees latitude, for all winter months (Oct-Apr) between 2010 and 2018. CryoSat-2 Level 1b Baseline C observed waveforms have been retracked using a numerical model for the SAR altimeter backscattered echo from snow-covered sea ice presented in Landy et al. (2019), which offers a sophisticated physically-based treatment of the effect of ice surface roughness on retracked ice and ocean elevations. Methods for optimizing echo model fits to observed CryoSat-2 waveforms, retracking waveforms, classifying returns, deriving sea ice freeboard, and converting to thickness are detailed in Landy et al. (In Review). This dataset contains derived sea ice thicknesses from two processing chains, the first using the conventional snow depth and density climatology from Warren et al. (1999) and the second using reanalysis and model-based snow data from SnowModel (Stroeve et al., In Review). Sea surface height and ocean topography grids were derived from only those CryoSat-2 samples classified as leads. Both the random and systematic uncertainties relevant for each parameter have been carefully estimated and are provided in the data files. NetCDF files contain detailed descriptions of each derived parameter. Funding was provided by ESA Living Planet Fellowship Arctic-SummIT grant ESA/4000125582/18/I-NS and NERC Project PRE-MELT grant NE/T000546/1.

Generated by inverting DTU15 Gravity field (generated from Cryosat Data) and combining with existing bathymetries

ClONO2 - This is a stratospheric reservoir species for chlorine and nitrogen, two of the catalysts in the breakdown of ozone. It reacts with HCl at low temperatures on the surfaces of polar stratospheric clouds (PSCs over Antarctica and possibly in the stratosphere over the Arctic). That normally slow reaction heterogeneously produces molecular chlorine and nitric acid. The former outgases from the PSC surface and is quickly photolyzed by 450 nm or shorter wavelength light to form chlorine radicals which rapidly catalyze the breakdown of ozone (see chlorine monoxide). [Science; v 238; pages 1258-1260; 1987.] [Science; v 258; pages 1342-1345; 1992.]

1 km Greenland, daily, with cloud mask, geotiff at https://github.com/AdrienWehrle/SICE/tree/master/masks

Albedo is the ratio of the radiation (radiant energy or luminous energy) reflected by a surface to that incident on it. Snow and cloud surfaces have a high albedo, because most of the energy of the visible solar spectrum is reflected. Vegetation and ocean surfaces have low albedo, because they absorb a large fraction of the energy. Clouds are the chief cause of variations in the Earth's albedo.The land surface albedo is the ratio of the radiant flux reflected from Earth's surface to the incident flux. It is a key forcing parameter controlling the partitioning of radiative energy between the atmospheric and surface. In the case of vegetation, a reference surface is typically defined at or near the top of the canopy and must be specified explicitly. Surface albedo depends on natural variations, highly variable in space and time as a result of terrestrial properties changes, and with illumination conditions and human activities and is a sensitive indicator of environmental vulnerability.

The Share of Built-Up Change Classified (SBCC) 2018-2021 layer is part of the High Resolution Layer (HRL) Imperviousness and provides categorical information on the change of built-up per pixel between the reference years 2018 and 2021 as derived from a re-classification of the Share of Built-Up Change (IMDC) 2021–2018 layer. The production of the HRL Imperviousness is coordinated by EEA in the frame of Copernicus, the Earth observation component of the European Union’s Space programme. The product is a raster dataset with 100-meter grid spacing (spatial resolution) that covers the 38 Eionet member and cooperating countries as well as the United Kingdom (i.e. EEA38+UK). It is distributed as 100 x 100 km tiles that are fully conformant with the EEA reference grid.