Temporal series (annual mean values) and Long term Average (LTA) of water discharge for each river mouth where in situ data is available. Different sources can be mixed if any.

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

The SeaDataNet aggregated datasets over the Atlantic Ocean are regional ODV historical collections of all temperature and salinity measurements contained within SeaDataNet database and covering 3 European sea basins: North Arctic Ocean, North Sea, North Atlantic Ocean. Two versions have been published during SeaDataNet 2 and they represent a snapshot of the SeaDataNet database content at two different times: • V1.1 January 2014 • V2 March 2015 Each of them is the result of the Quality Check Strategy (QCS) implemented during SeaDataNet 2 that contributed to highly improve the quality of temperature and salinity data. The QCS is made by four main phases: 1. data harvesting from the central CDI 2. file and parameter aggregation 3. quality check analysis at regional level 4. analysis and correction of data anomalies. The aggregated datasets have been prepared and quality checked using ODV software.

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

Le plan cadastral est le découpage du territoire français en unités de surfaces permettant le calcul de certains impôts (notamment la taxe foncière, la taxe d'habitation et la cotisation foncière des entreprises). La consultation du cadastre peut se faire en ligne sur https://cadastre.gouv.fr. Chaque commune est subdivisée en sections, elles-mêmes subdivisées en feuilles (ou planches). Une feuille cadastrale comporte des parcelles, qui peuvent supporter des bâtiments, ainsi que de nombreux autres objets d'habillage ou de gestion. --- Etat de la disponibilité de la donnée : - Data.gouv : donnée téléchargeable au format EDIGEO L93 (formats EDIGEO Zone CC et DXF à venir)et mise à jour trimestriellement.Elle est anonymisée.

Potentialités agronomiques par culture (blé, haricot, maïs, orge, tabac et tournesol).

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

This data product selects sample areas of digital bathymetry, chosen for their relevance to marine activities and data sources alternative to GEBCO. The approach for building the digital map of water depth is to use GEBCO as a baseline and look at a set of sample areas where GEBCO could be improved upon. Sample areas have also been selected to be representative of each continent bordering the Atlantic and expected future requirements. Data sources include GEBCO, EMODNET, USGS and CHS.

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)°

The eleven collected wild strains of T. lutea were compared phenotypically, in particular with regard to their pigment and lipid profiles. The genome of each T. lutea strain was also sequenced to investigate the genetic structure and genome organisation of this species. Collected data were summarized in a genome browser to provide easy-to-use support for the scientific community (https://genomes-catalog.ifremer.fr). This provides an important resource- to understand, exploit and predict the biodiversity of this species.