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.

Specification of the desirable and recommended product attributes for generating time series of average annual sea-level rise for the last 50 and 100 yrs.

Cette donnée représente l'ensemble des ERP géolocalisés du Lot-et-Garonne. Le périmètre de production concerne les ERP de catégories 1, 2, 3, 4, et 5 avec local à sommeil soit 1069 ERP. Seuls les ERP de catégorie 5 sans local à sommeil ne sont pas classés. Tous les types d'ERP sont représentés sauf les ERP type CTS. Etant donné les changements fréquents dont les ERP sont sujets, la mise à jour de ces données ne peut être permanente.

Auteur(s): Cha Lucie , Analyse des paysages de méga évènements sur des sites internationaux. Historique de l'évolution de expositions géantes. Projet d'aménagement de la ville de Bordeaux qui a posé sa candidature pour l'Exposition universelle de 2025

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.

Cette donnée représente l'ensemble des ERP géolocalisés de la Gironde. Le périmètre de production concerne les ERP de type J,O,Uh et Rh, soit 1066.

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.

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)

GOSUD aims at assembling in-situ observations of the world ocean surface collected by a variety of ships and at distributing quality controlled datasets. At present time the variables considered by GOSUD are temperature and salinity. The GOSUD data are mostly collected using thermosalinographs (TSG) installed on research vessels, on commercial ships and in some cases on sailing exploration ships. GOSUD manages both near-real time (RT and NRT) data and delayed mode (DM-reprocessed) data. The GOSUD GDAC is hosted by the Coriolis data centre (France) and a back-up (permanent archived) is performed on a daily basis by NCEIS (NOAA's National Centers for Environmental Information).

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.