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 ot the spatial layers attributes of sea level trend for the last 10 years for the Mediterranean basin and for each NUTS3 region along the coast.

Specification of the desirable and recommended product attributes for generating time series of sea level trend for the last 10 years for the Mediterranean basin for each NUTS3 region along the coast.

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.

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 temperature at mid-water and sea bottom for the last 10 yrs.

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.

'''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

'''This product has been archived''' For operationnal and online products, please visit https://marine.copernicus.eu '''Short description:''' The Operational Mercator Ocean biogeochemical global ocean analysis and forecast system at 1/4 degree is providing 10 days of 3D global ocean forecasts updated weekly. 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 biogeochemical parameters (chlorophyll, nitrate, phosphate, silicate, dissolved oxygen, dissolved iron, primary production, phytoplankton, PH, and surface partial pressure of carbon dioxyde) over the global ocean. The global ocean output files are displayed with a 1/4 degree horizontal resolution with regular longitude/latitude equirectangular projection. 50 vertical levels are ranging from 0 to 5700 meters. * NEMO version (v3.6_STABLE) * Forcings: GLOBAL_ANALYSIS_FORECAST_PHYS_001_024 at daily frequency. * Outputs mean fields are interpolated on a standard regular grid in NetCDF format. * Initial conditions: World Ocean Atlas 2013 for nitrate, phosphate, silicate and dissolved oxygen, GLODAPv2 for DIC and Alkalinity, and climatological model outputs for Iron and DOC * Quality/Accuracy/Calibration information: See the related QuID[http://marine.copernicus.eu/documents/QUID/CMEMS-GLO-QUID-001-028.pdf] '''DOI (product) :''' https://doi.org/10.48670/moi-00015

Moving 10-years analysis of Silicate 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 1963-1972 until 2005-2014 (winter) - from 1979-1988 until 2005-2014 (spring) - from 1990-1999 until 2005-2014 (summer) - from 1964-1973 until 2005-2014 (autumn) Observational data span from 1962 to 2014. Depth range (IODE standard depths): -3000.0, -2500.0, -2000.0, -1750, -1500.0, -1400.0, -1300.0, -1200.0, -1100.0, -1000.0, -900.0, -800.0, -700.0, -600.0, -500.0, -400.0, -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 consraint applied: no. Units: umol/l