2017
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Calculation of the average annual sediment balance per stretch of coast for the past 50 years for all coastal zones bordering the North Atlantic Ocean. For this scale of study, this has been interpreted in terms of shoreline advance / retreat in mm/year. Required data sources are therefore national or international datasets giving this parameter directly. It is also possible to utilise more aggregated data sources, but annual values would then be approximated from them. The main challenge in producing this product lies with obtaining datasets which include this data from multiple countries and potentially multiple languages, since this data is usually produced as a result of comparatively small scale studies.
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Localisation et description des sentiers de randonnées (GR, PDIPR, itinérance à pied, chemin local,sans classement). Localisation et description des tronçons (accessibilité/nature du sol/état...). Bornes/mats (description/état/historique des interventions...) Mobiliers (description/état/historique des interventions...)
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Maps of seasonal p90 (percentile 90) of Chla on the North Atlantic basin for the past ten years (2005-2014) using the Global Copernicus chla level 4 (L4) products (resolution of 4 km). Method as Gohin Francis, Saulquin Bertrand, Bryere Philippe (2010) Atlas de la Température, de la concentration en Chlorophylle et de la Turbidité de surface du plateau continental français et de ses abords de l’Ouest européen. Ifremer. http://archimer.ifremer.fr/doc/00057/16840/
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ERA5 is a climate reanalysis dataset, covering the period 1979 to present. ERA5 is being developed through the Copernicus Climate Change Service (C3S). Extracted data available here are one hourly at a regular grid lat,lon 0.25*0.25
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The Global Sea Level Observing System (GLOSS) was established by the Intergovernmental Oceanographic Commission (IOC) of UNESCO in 1985 to establish a well-designed, high-quality in situ sea level observing network to support a broad research and operational user base. Various tide gauge networks have contributed to GLOSS, each with a different focus and each changing over time as research priorities evolve. The main component is the GLOSS Core Network (GCN), a global set of ~300 tide gauges that serves as the backbone of the global in situ sea level network. GCN gauges were allocated to each island or group of islands at intervals not closer than 500 km, and along continental coasts at intervals generally not less than 1000 km. Preference was given to islands in order to maximise exposure to the open ocean. Established in 1933, the Permanent Service for Mean Sea Level (PSMSL) is responsible for the collection, publication, analysis and interpretation of sea level data from the global network of tide gauges, including the GLOSS Core Network.
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The in-situ TAC integrates and quality control in a homogeneous manner in situ data from outside Copernicus Marine Environment Monitoring Service (CMEMS) data providers to fit the needs of internal and external users. It provides access to integrated datasets of core parameters for initialization, forcing, assimilation and validation of ocean numerical models which are used for forecasting, analysis and re-analysis of ocean physical and biogeochemical conditions. The in-situ TAC comprises a global in-situ centre and 6 regional in-situ centres (one for each EuroGOOS ROOSs). The focus of the CMEMS in-situ TAC is on parameters that are presently necessary for Copernicus Monitoring and Forecasting Centres namely temperature, salinity, sea level, current, waves, chlorophyll / fluorescence, oxygen and nutrients. The initial focus has been on observations from autonomous observatories at sea (e.g. floats, buoys, gliders, ferrybox, drifters, and ships of opportunity). The second objective was to integrate products over the past 25 to 50 years for re-analysis purposes... Gathering data from outsider organisations requires strong mutual agreements. Integrating data into ONE data base requires strong format standard definition and quality control procedures. The complexity of handling in situ observation depends not only on the wide range of sensors that have been used to acquire them but, in addition to that, the different operational behaviour of the platforms (i.e vessels allow on board human supervision, while the supervision of others should be put off until recovering or message/ping reception)°
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The Joint WMO-IOC Technical Commission for Oceanography and Marine Meteorology Observing Programmes Support Centre, provides technical coordination at international level for the sustained elements of the Global Ocean Observing System. The Centre monitors in real-time the status of the observing networks and provides a toolbox to evaluate their performance and optimize their implementation and data flow. Currently OceanOPS monitors the Argo profiling floats, the DBCP surface drifters, coastal and tropical moorings, ice buoys, tsunami buoys, the OceanSITES moorings time-series, the GO-SHIP hydrographic reference lines, the SOT mat/ocean ship based observations and the GLOSS sea level tide gauges. A number of other observing systems are being added gradually, including ocean gliders, polar systems, marine mammals and potentially HF radars.
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Combined product of Water body phosphate based on DIVA 4D 10-year analysis on five regions : Northeast Atlantic Ocean, North Sea, Baltic Sea, Black Sea, Mediterranean Sea. The boundaries and overlapping zones between these five regions were filtered to avoid any unrealistic spatial discontinuities. This combined water body phosphate product is masked using the relative error threshold 0.5. Units: umol/l
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Cartographie des écluses à poissons actuellement encore en place sur l'île de Ré
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We took inspiration from a “Matrix of marine activities” (appropriate for each IUCN management category) extracted from IUCN paper, to achieve the first objective by computing 1 product comprising the following 12 components: Product ATLANTIC_CH02_Product_1 / MPA Atlantic network classified in IUCN classification • Traditional fishing area • Sustainable fishing area (industrial) • Leisure fishing area • Leisure activity area (diving, surfing, tourist beaches) • Shipping area (shipping trajectory, aids navigation) • Scientific activity area • Renewable energy generation facility area (ocean energy facilities, wind farms) • Aquaculture area (finfish production, shellfish production) • Shipping infrastructure area (harbours, dredging area...) • Waste discharge area • Mining area (aggregate extraction, hydrocarbon extraction) • Habitation area (urban area) Each geographic information required for the components was compiled into a layer in grid format. These grids were intersected with the MPAs layer to assign each MPA a IUCN category according to the conditional matrix illustrated below : If the MPA area contains : Habitation area (urban area) The IUCN category is :V If the MPA area contains : Mining area (aggregate extraction, hydrocarbon extraction) The IUCN category is V If the MPA area contains : Waste discharge area The IUCN category is : V If the MPA area contains : Shipping infrastructure area (harbours, dredging area...) The IUCN category is IV If the MPA area contains : Aquaculture area (finfish production, shellfish production) The IUCN category is IV If the MPA area contains : Renewable energy generation facility area (ocean energy facilities, wind farms) The IUCN category is IV If the MPA area contains : Leisure fishing area The IUCN category is IV If the MPA area contains : Sustainable fishing area (industrial) The IUCN category is IV If the MPA area contains : Shipping area (shipping trajectory, aids navigation) The IUCN category is II If the MPA area contains : Leisure activity area (diving, surfing, tourist beaches) The IUCN category is Ib If the MPA area contains : Traditional fishing area The IUCN category is Ib If the MPA area contains : Scientific activity area The IUCN category is Ia
Catalogue PIGMA