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2017

523 record(s)
 
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From 1 - 10 / 523
  • Temporal series (annual mean values) and Long Term Average (LTA) of sediment load for each river mouth where in situ data is available. Different sources can be mixed if any.

  • The EEA coastline dataset is created for detailed analysis with a Minimum Mapping Unit of e.g. 1:100000, for geographical Europe. The coastline is a hybrid product obtained from satellite imagery from two projects: 1) EUHYDRO (Pan-European hydrographic and drainage database) [https://land.copernicus.eu/pan-european/satellite-derived-products/eu-hydro/view] and 2) GSHHG (A Global Self-consistent, Hierarchical, High-resolution Geography Database) [http://www.soest.hawaii.edu/pwessel/gshhg/]. The defining criteria was altitude level = 0 from EUDEM [https://land.copernicus.eu/pan-european/satellite-derived-products/eu-dem/view]. Outside the coverage of the EUDEM, the coastline from GSHHG was used without modifications. A few manual amendments to the dataset were necessary to meet requirements from EU Nature Directives, Water Framework Directive and Marine Strategy Framework Directive. In 2015, several corrections were made in the Kalogeroi Islands (coordinates 38.169, 25.287) and two other Greek little islets (coordinates 36.766264, 23.604318), as well as in the peninsula of Porkkala (around coordinates 59.99, 24.42). In this revision (v3, 2017), 2 big lagoons have been removed from Baltic region, because, according to HELCOM, are freshwater lagoons. This dataset is a polygon usable as a water-land mask.

  • 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/

  • The Surface Ocean CO₂ Atlas (SOCAT) is a synthesis activity for quality-controlled, surface ocean fCO₂ (fugacity of carbon dioxide) observations by the international marine carbon research community (>100 contributors). SOCAT data is publicly available, discoverable and citable. SOCAT enables quantification of the ocean carbon sink and ocean acidification and evaluation of ocean biogeochemical models. SOCAT represents a milestone in biogeochemical and climate research and in informing policy. SOCAT data are released in versions. Each succeeding version contains new data sets as well as updates of older ones. The first version of SOCAT was released in 2011, the second and third version followed biennially. Automation allowed annual public releases since version 4. The latest SOCAT version (version 5) has 21.5 million observations from 1957 to 2017 for the global oceans and coastal seas. SOCAT contains data from the VOS, OceanSites network and mooring, buoy data in general as well as calibrated sensor data.

  • Temporal series (annual mean values) with error of estimation and Long Term Average (LTA) with error of estimation of total nitrogen load for each river mouth where in situ data is available. Different sources can be mixed if any.

  • 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.

  • Temporal series (annual mean values) of temperature for each river mouth.Temporal series (annual mean values) of temperature for each river mouth.

  • The analysis was performed per season using DIVA software tool (Data-Interpolating Variational Analysis). The analyses products are stored as NetCDF CF files and made available as WMS layers for easy browsing and adding. Every step of the time dimension corresponds to a 6-year moving average from 1983 to 2016. The depth dimension spans from surface to 1000 m, with 21 vertical levels. The boundaries and overlapping zones between these regions were filtered to avoid any unrealistic spatial discontinuities. This combined water body dissolved oxygen concentration product is masked using the relative error threshold 0.5. Units: µmol/l Created by 'University of Liège, GeoHydrodynamics and Environment Research (ULiège-GHER)'. The data used as input for DIVA have been extracted from the EMODnet Chemistry Download Service: https://emodnet-chemistry.maris.nl/search Intermediate regional data products: Mediterranean Sea - DIVA 4D 6-year analysis of Water body silicate 1965/2016 v2018, Arctic Ocean - DIVA 4D 6-year analysis of Water body silicate 1980/2017 v2018, North Sea - DIVA 4D 6-year analysis of Water body silicate 1980/2017 v2018, Black Sea - DIVA 4D 6-year analysis of Water body silicate 1990/2016 v2018, North East Atlantic Ocean - DIVA 4D 6-year analysis of Water body silicate 1971/2017 v2018

  • The three digital maps provided in this product aim to assess the degree of Offshore windfarm siting suitability existing over a geographical area with a focal point where waters of France and Spain meet in Biscay Bay on 500 m depth. The maps display respectively the spatial distribution of the average and lowest windfarm siting suitability scores along with the average wind speed distribution over a time period of 10 years. They are part of a process set up to assess the fit for use quality of the currently available datasets to support a preliminary selection of potential offshore sites for wind energy development. To build these maps, GIS tools were applied to several key spatial datasets from the 5 data type domains considered in the project: Air, Marine Water, Riverbed/Seabed, Biota/Biology and Human Activities, collated during the initial stages of the project. Initially, each selected dataset was formatted and clipped to the study area extent and spatially classified according to suitability scores, to define raster layers with the variables depicting levels of current anthropogenic and environmental spatial occupation of activities, seabed depth and slope, distances to shoreline, shipping intensity, mean significant wave height, and substrate type. These pre-processed layers were employed as inputs for applying a spatial multi-criteria model using a wind farming suitability classification based on a discrete 5 grades index, ranging from Very Low up to Very High suitability. In adition to suitability maps, an average wind speed spatial distribution map for a 10 years period, at 10 m height, was obtained over the study area from the raster processing of a wind speed time series of monthly means available from daily wind analysis data. The characteristics of the datasets used in this exercise underwent an appropriateness evaluation procedure based on a comparison between their measured quality and those specified for the product. The study area, located in the Biscay Golf includes a coastal zone of Spain and France. Consequently, some zones are subject to constraints to offshore windfarm implementation due to environmental protection, visual impacts and seafoor attributes. Data gaps exist with an emphasis on fishing activity and distribution of essential habitats and species. All the spatial information made available in these maps and from the subsequent appropriateness analysis of the datasets, contributes to a clearer overview of the amount of public-access baseline knowledge currently existing for the North Atlantic basin area.

  • Nature de l'occupation du sol par commune et en m².