Suitability index of a wind farm in the NWMed concerning the environmental resources, the natural barriers, human activities, MPA and fisheries.

Description ot the spatial layers attributes of sea level trend for the last 50 and 100 years for the Mediterranean basin and for each NUTS3 region along the coast.

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.

Moving 10-years analysis of Chlorophyll-a -1.0-ANA at Northeast Atlantic Ocean for each season: - winter: January-March, - spring: April-June, - summer: July-September, - autumn: October-December. Every year of the time dimension corresponds to the 10-year centred average of each season. Decades span from 1985-1994 until 2005-2014. Observational data span from 1970 to 2015. Depth range (IODE standard depths): -300.0, -250.0, -200.0, -150.0, -125.0, -100.0, -75.0, -50.0,-40.0, -30.0, -20.0, -10.0, -5.0, -0.0 Data Sources: observational data from SeaDataNet/EMODNet Chemistry Data Network. Description of DIVA analysis: Geostatistical data analysis by DIVA (Data-Interpolating Variational Analysis) tool. GEBCO 1min topography is used for the contouring preparation. Analyzed filed masked using relative error threshold 0.3 and 0.5 DIVA settings. Signal to noise ratio and correlation length were optimized and filtered vertically and a seasonally-averaged profile was used. Logarithmic transformation applied to the data prior to the analysis. Background field: the data mean value is subtracted from the data. Detrending of data: no, Advection constraint applied: no. Units: mg/m^3

Data from FerryBoxes on ships of opportunity going on permanent routes are stored inside this database (ferrydata.hzg.de). Parameters are temperature, salinity, chlorophyll-a fluorescence, oxygen and different others. The data model is transect oriented. A data portal to access and visualise the data is also provided.

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.

The main aim of this product was to define the suitability of offshore sites in the area between the borders of France-Spain-Italy for wind farm development. The adopted approach classifies wind speed data by their level of suitability, ranging from a grade 5 for exclusion zones, to a grade 1 for areas deemed appropriate for wind farm development. The quality indexes adopted were based on mean and variation statistical measures taking into consideration both the expected energy potential and the corresponding variability.

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.

The Drifting Buoys GDAC -Global Data Assembly Centre- is the repository of surface drifters data. Both NRT -Near Real Time- and DM -Delayed Mode- data are available on the GDAC. Drifters report generally trajectories, sea-surface temperatures, atmospheric pressures at sea-level, as well as sea-surface salinity or sub-surface temperature in the ocean top layer.

Présentation des entreprises, cartographie du risque et consignes en cas d'alerte pour les populations des communes de la Presqu'île d'Ambès. Plaquettes 4 ou 8 pages (avec cartographie)