Specifications of the desirable and recommended product attributes for generating spatial layers of sea level trend for the last 10 years for the Mediterranean basin and for each NUTS3 region along the coast.

The objective of this tender is to examine the current data collection, observation and data assembly programmes in the Meditterranean Sea, identify gaps and to evaluate how they can be optimised.

Moving 10-years analysis of Phosphate 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 1963-1972 until 2005-2014 (spring) - from 1964-1973 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 constraint applied: no. Units: umol/l

VOS/SOOP tracks are usually repeated several times a year and inform about the marine sinks and sources of atmospheric carbon dioxide on a global bases and their variability. Data from this network has been made available to the scientific community and interested public via the Carbon Dioxide Information Analysis Centre (CDIAC) Oceans at the Department of Energy, USA, since the early 1990’s where PIs submitted and shared their data. In 2017, CDIAC Ocean will be named Ocean Carbon Data System (OCADS) and join NOAA’s National Centers for Environmental Information (NCEI). In 2007, the marine biogeochemistry community coordinated by the International Ocean Carbon Coordination Project (IOCCP), launched the Surface Ocean Carbon Dioxide ATlas (SOCAT) in order to uniformly quality control and format the data with detailed documentation. Underway carbon dioxide data from the VOS network are integrated in SOCAT.

The objective of this tender is to examine the current data collection, observation and data assembly programmes in the Meditterranean Sea, identify gaps and to evaluate how they can be optimised.

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.

Data from FerryBoxes on ships of opportunity going on permanent routes are stored inside this database (ferrydata.hzg.de). Parameters are temperature, salinity, chlorophyll-a fluorescence, oxygen and different others. The data model is transect oriented. A data portal to access and visualise the data is also provided.

Output of the 2016 EUSeaMap broad-scale predictive model, produced by EMODnet Seabed Habitats. The extent of the mapped area includes the Mediterranean Sea, Black Sea, Baltic Sea, and areas of the North Eastern Atlantic extending from the Canary Islands in the south to Norway in the North. The map was produced using a "top-down" modelling approach using classified habitat descriptors to determine a final output habitat. Habitat descriptors differ per region but include: Biological zone Energy class Oxygen regime Salinity regime Seabed Substrate Riverine input Habitat descriptors (excepting Substrate) are calculated using underlying physical data and thresholds derived from statistical analyses or expert judgement on known conditions. The model is produced in Arc Model Builder (10.1). For more information on the modelling process please read the EMODnet Seabed Habitats The model was created using raster input layers with a cell size of 0.002dd (roughly 250 meters). The model includes the sublittoral zone only; due to the high variability of the littoral zone, a lack of detailed substrate data and the resolution of the model, it is difficult to predict littoral habitats at this scale. The map follows the EUNIS 2007-11 classification system where it is appropriate.

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.

Moving 10-years analysis of Ammonium 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 1984-1993 until 2005-2014 (winter) - from 1980-1989 until 2005-2014 (spring) - from 1980-1989 until 2005-2014 (summer) - from 1980-1989 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 constraint applied: no. Units: umol/l