Businesses, policymakers, and local communities need to access reliable weather and climate information to safeguard human health, wellbeing, economic growth, and environmental sustainability. However, important changes in climate variability and extreme weather events are difficult to pinpoint and account for in existing modelling and forecasting tools. Moreover, many changes in the global climate are linked to the Arctic, where climate change is occurring rapidly, making weather and climate prediction a considerable challenge. Blue-Action evaluated the impact of Arctic warming on the northern hemisphere and developed new techniques to improve forecast accuracy at sub-seasonal to decadal scales. Blue-Action specifically worked to understand and simulate the linkages between the Arctic and the global climate system, and the Arctic’s role in generating weather patterns associated with hazardous conditions and climatic extremes. In doing so, Blue-Action aimed to improve the safety and wellbeing of people in the Arctic and across the Northern Hemisphere, reduce the risks associated with Arctic operations and resource exploitation, and support evidence-based decision-making by policymakers worldwide.

Description of the spatial layers atributes of sea surface temperature trend for the last 10, 50 and 100 years for the Mediterranean basin and for each NUTS3 region along the coast.

Output of the 2016 EUSeaMap broad-scale predictive model, produced by EMODnet Seabed Habitats and aggregated into the predominant habitats of the Marine Strategy Framework Directive. The extent of the mapped area includes the Mediterranean Sea, Black Sea, Baltic Sea, and areas of the North Eastern Atlantic extending from the Canary Islands in the south to Norway in the North. The map was produced using a "top-down" modelling approach using classified habitat descriptors to determine a final output habitat. Habitat descriptors differ per region but include: Biological zone Energy class Oxygen regime Salinity regime Seabed Substrate Riverine input Habitat descriptors (excepting Substrate) are calculated using underlying physical data and thresholds derived from statistical analyses or expert judgement on known conditions. The model is produced in Arc Model Builder (10.1). For more information on the modelling process please read the EMODnet Seabed Habitats The model was created using raster input layers with a cell size of 0.002dd (roughly 250 meters). The model includes the sublittoral zone only; due to the high variability of the littoral zone, a lack of detailed substrate data and the resolution of the model, it is difficult to predict littoral habitats at this scale.

Specification of the desirable and recommended products attributes for generating spatial layers of sea level trend for the last 50 and 100 years for the Mediterranean basin and for each NUTS3 region along the coast.

'''This product has been archived''' For operationnal and online products, please visit https://marine.copernicus.eu '''Short description''' The Operational Mercator global ocean analysis and forecast system at 1/12 degree is providing 10 days of 3D global ocean forecasts updated daily. The time series is aggregated in time in order to reach a two full year’s time series sliding window. This product includes daily and monthly mean files of temperature, salinity, currents, sea level, mixed layer depth and ice parameters from the top to the bottom over the global ocean. It also includes hourly mean surface fields for sea level height, temperature and currents. The global ocean output files are displayed with a 1/12 degree horizontal resolution with regular longitude/latitude equirectangular projection. 50 vertical levels are ranging from 0 to 5500 meters. This product also delivers a special dataset for surface current which also includes wave and tidal drift called SMOC (Surface merged Ocean Current). '''DOI (product) :''' https://doi.org/10.48670/moi-00016

Description of the attributes for the time-series annual average sea level for the last 50 and the last 100 yrs for the Mediterranean basin and for each NUTS region along the coast.

Description of attributes for time series of sea level trend for the last 10 yrs for the Mediterranean basin and for each NUTS3 region along the coast.

Confidence in the full output of the 2016 EUSeaMap broad-scale predictive model, produced by EMODnet Seabed Habitats. Values are on a range from 1 (low confidence) to 3 (high confidence). Confidence is calculated by amalgamating the confidence values of the underlying applicable habitat descriptors used to generate the habitat value in the area in question. Habitat descriptors differ per region but include: Biological zone Energy class Oxygen regime Salinity regime Seabed Substrate Riverine input Confidence in habitat descriptors are driven by the confidence in the source data used to determine the descriptor, and the confidence in the threshold/margin (areas closer to a boundary between two classes will have lower confidence). Confidence values are also available for each habitat descriptor and input data layer.

GO-SHIP, the Global Ocean Ship-Based Hydrographic Investigations Program, is conducting repeat hydrography with high accuracy high precision reference measurements of a variety of EOVs through the whole water column. A selection of continent-to-continent full depth sections are repeated at roughly decadal intervals. The data archive for CTD data and bottle data is currently at CCHDO, although the CTD data from European cruises are available at Seadatanet as well.

Level 2 sub-skin Sea Surface Temperature derived from AVHRR on Metop, global and provided in full-resolution swath (1 km at nadir), in GHRSST compliant netCDF format. The satellite input data has successively come from Metop-A, Metop-B and Metop-C level 1 data processed at EUMETSAT. SST is retrieved from AVHRR infrared channels (3.7, 10.8 and 12.0 µm) using a multispectral algorithm and a cloud mask. Atmospheric profiles of water vapor and temperature from a numerical weather prediction model, Sea Surface Temperature from an analysis, together with a radiative transfer model, are used to correct the multispectral algorithm for regional and seasonal biases due to changing atmospheric conditions. The quality of the products is monitored regularly by daily comparison of the satellite estimates against buoy measurements.The product format is compliant with the GHRSST Data Specification (GDS) version 2. Users are advised to use data only with quality levels 3,4 and 5.