Mapping and classifying the seabed of the West Greenland continental shelf. Marine benthic habitats support a diversity of marine organisms that are both economically and intrinsically valuable. Our knowledge of the distribution of these habitats is largely incomplete, particularly in deeper water and at higher latitudes. The western continental shelf of Greenland is one example of a deep (more than 500 m) Arctic region with limited information available. This study uses an adaptation of the EUNIS seabed classification scheme to document benthic habitats in the region of the West Greenland shrimp trawl fishery from 60┬░N to 72┬░N in depths of 61ÔÇô725 m. More than 2000 images collected at 224 stations between 2011 and 2015 were grouped into 7 habitat classes. A classification model was developed using environmental proxies to make habitat predictions for the entire western shelf (200ÔÇô700 m below 72┬░N). The spatial distribution of habitats correlates with temperature and latitude. Muddy sediments appear in northern and colder areas whereas sandy and rocky areas dominate in the south. Southern regions are also warmer and have stronger currents. The Mud habitat is the most widespread, covering around a third of the study area. There is a general pattern that deep channels and basins are dominated by muddy sediments, many of which are fed by glacial sedimentation and outlets from fjords, while shallow banks and shelf have a mix of more complex habitats. This first habitat classification map of the West Greenland shelf will be a useful tool for researchers, management and conservationists.

Mapping and classifying the seabed of the West Greenland continental shelf. Marine benthic habitats support a diversity of marine organisms that are both economically and intrinsically valuable. Our knowledge of the distribution of these habitats is largely incomplete, particularly in deeper water and at higher latitudes. The western continental shelf of Greenland is one example of a deep (more than 500 m) Arctic region with limited information available. This study uses an adaptation of the EUNIS seabed classification scheme to document benthic habitats in the region of the West Greenland shrimp trawl fishery from 60┬░N to 72┬░N in depths of 61ÔÇô725 m. More than 2000 images collected at 224 stations between 2011 and 2015 were grouped into 7 habitat classes. A classification model was developed using environmental proxies to make habitat predictions for the entire western shelf (200ÔÇô700 m below 72┬░N). The spatial distribution of habitats correlates with temperature and latitude. Muddy sediments appear in northern and colder areas whereas sandy and rocky areas dominate in the south. Southern regions are also warmer and have stronger currents. The Mud habitat is the most widespread, covering around a third of the study area. There is a general pattern that deep channels and basins are dominated by muddy sediments, many of which are fed by glacial sedimentation and outlets from fjords, while shallow banks and shelf have a mix of more complex habitats. This first habitat classification map of the West Greenland shelf will be a useful tool for researchers, management and conservationists.

This dataset contains Amphipod distribution records and is based on literature from the years 1931 to 2018. The data were collected during a variety of cruises and sampling events while the majority was obtained during the Danish Ingolf expedition. Sampling events took place in the North Atlantic and Arctic waters which included the Artic Ocean, Barents Sea, Kara Sea, Labrador Sea, Buffin Bay and Greenland Sea. Amphipods were predominantly collected using dredges, epibenthic sledges and remotely operated vehicles but scuba divers and vehicle-free baited traps were also used. This way, over 1566 Amphipod samples were collected in total which include 45 families, 117 genera and 164 species.

This is the metadata covering the Sentinel-1 and Sentinel-2 Snow Phenology (SPS1S2) product. It is generated once a year over high-mountain areas at European scale, based on daily cumulative Gap-Filled Fractional Snow Cover (GFSC) products calculated from Sentinel-2 optical and Sentinel-1 radar data. This product describes the snow season in terms of temporality as it provides, for each pixel, the number of days with snow cover, as well as the first and the last day of the longest observed snow period. It has a spatial resolution of 60 m x 60 m, as does the input GFSC product. Each product is composed of separate files corresponding to the different layers of the product, and another metadata file." The product is also available in another projection as tiles aligned with the Pan-European High-Resolution Layers in the European grid (ETRS89 LAEA - EPSG: 3035) at 60 m x 60 m and 100 m x 100 m. SP S2+S2 is one of the products of the pan-European High-Resolution Water Snow & Ice portfolio (HR-WSI), which are provided at high spatial resolution from the Sentinel-2 and Sentinel-1 constellations data from September 1, 2016 onwards.

Moving 6-year analysis of dissolved oxygen concentration in the Arctic Ocean, for each season in the period 1965-2024. Every year of the time dimension corresponds to the 6-year centered average for each season. Winter: December-February, Spring: March-May, Summer: June-August, Autumn: September-November. Depth range (IODE standard depths): 0, 5, 10, 20, 30, 40, 50, 75, 100, 125, 150, 200, 250, 300, 400, ..., 1500, 1750, 2000, 2500m. Units: umol/l. Description of DIVA analysis: The computation was done with DIVAnd (Data-Interpolating Variational Analysis in n dimensions), version 2.7.13, using GEBCO 30sec topography for the spatial connectivity of water masses. The horizontal resolution of the produced DIVAnd maps grids is 0.125 degrees. Signal-to-noise ratio was fixed to 3.0, horizontal correlation length varying from 45 km near the coast to 150 km, and vertical correlation length varying between 25 and 1000 m. Logarithmic transformation is applied to the data prior to the analysis. Background field: analysis with signal-to-noise ratio = 20, horizontal correlation length 50-200 km, and vertical correlation length 25-1000 m.

Sentinel-2 is a constellation of two optical imaging satellites, which are a part of Copernicus - the European Union's Earth observation program.

Using new techniques to measure pan-Arctic sea ice thickness from the satellite radar altimeter Cryosat-2 during summer months

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 Arctic Oscillation (AO) is the dominant pattern of non-seasonal sea-level pressure (SLP) variations north of 20N, and it is characterized by SLP anomalies of one sign in the Arctic and anomalies of opposite sign centered about 37-45N. Additional information is available for the Arctic Oscillation (AO) and for the North Atlantic Oscillation (NAO), a close relative of the AO (http://jisao.washington.edu/ao/)

Jason-1 (Joint Altimetry Satellite Oceanography Network) Mission. Jason is the name of a joint CNES/NASA oceanography mission series with the objective to monitor global ocean circulation, discover the tie between the oceans and atmosphere, improve global climate predictions, and to monitor events such as El Nino conditions and ocean eddies. The oceanography mission series is considered a cornerstone of GCOS (Global Ocean Observing System), a concept advocated by WMO (World Meteorological Organization), IOC (Intergovernmental Oceanographic Commission of the UNESCO), UNEP (United Nations Environmental Program), and ICSU (International Council of Scientific Unions).