Calculation of the average annual sediment balance per stretch of coast for the past 10 years.

Phyto plankton Abundance: Identify the 3 most abundant phytoplankton species in the North Atlantic and calculate a timeseries of their abundance within the basin.

It's a study of MPA connectivity with assessment of : -size -shape -spacing between each MPA

'''DEFINITION''' The global annual chlorophyll anomaly is computed by subtracting a reference climatology (1997-2014) from the annual chlorophyll mean, on a pixel-by-pixel basis and in log10 space. Both the annual mean and the climatology are computed employing ESA Ocean Colour Climate Change Initiative (ESA OC-CCI, Sathyendranath et al., 2018a) global products (i.e. using the standard OC-CCI chlorophyll algorithms, OCI) as distributed by CMEMS. '''CONTEXT''' Phytoplankton – and chlorophyll concentration as a proxy for phytoplankton – respond rapidly to changes in their physical environment. Some of those changes are seasonal and are determined by light and nutrient availability (Racault et al., 2012). By comparing annual mean values to a climatology, we effectively remove the seasonal signal, while retaining information on potential events during the year. Chlorophyll anomalies can be correlated to climate indexes in particular regions, such as the ENSO index in the equatorial Pacific (Behrenfeld et al. 2006; Racault et al., 2012) and the IOD index in the Indian Ocean (Brewin et al., 2012). It is important to study chlorophyll anomalies in consonance with sea surface temperature and sea level anomalies, as increases in chlorophyll are generally consistent with decreases in SST and sea level anomalies, suggesting an increase in mixing and vertical nutrient transport (von Schuckmann et al., 2016). '''CMEMS KEY FINDINGS''' The average global chlorophyll anomaly 2019 is -0.02 log10(mg m-3), with a maximum value of 1.7 log10(mg m-3) and a minimum value of -3.2 log10(mg m-3). That is to say that, in average, the annual 2019 mean value is slightly lower (96%) than the 1997-2014 climatological value. The positive signals reported in 2016 and 2017 (Sathyendranath et al., 2018b) in the southern Pacific Ocean could still be observed in the 2019 map, while the significant negative anomalies in the tropical waters of the northern Pacific Ocean were also detected to a lesser extent. Areas showing a change of anomaly sign from 2019 include the southern coast of Japan (no anomaly to positive) and the tropical Atlantic (anomalies close to zero for 2019). A marked increase in chlorophyll concentration was observed during 2019 in the Great Australian Bight, while negative anomalies became stronger in the Guatemala Basin and the region south of the Gulf of Guinea and, with values of chlorophyll reaching as low as 30% of the climatological value (anomaly < -0.5 log10(mg m-3)). The persistent positive anomalies in the higher latitudes of the North Atlantic (> 40°) match the cooling observed in the 2018 and previous years SST anomaly maps.

This product attempt to follow up on the sea level rise per stretch of coast of the North Atlantic, over past 100 years as follows: • Characterization of absolute sea level trend at annual resolution, along the coasts of EU Member States (including Outermost Regions), Canada, Faroes, Greenland, Iceland, Mexico, Morocco, Norway and USA; The stretchs or coast are defined by the administrative regions of the Atlantic Coast: • from NUTS3** administrative division for EU countries (see Eurostat), and • from GADM*** administrative divisions for non-EU countries. ** Third level of Nomenclature of Territorial Units for Statistics *** Global Administrative Areas For absolute sea level trend for 100 years we extract the information from grided sea level reconstruction datasets (using a combination of satellite and tide gauges) and extrapolate it to the nearest strecth of coast. The product is Provided in tabular form and as a map layer.

The Oil Platform Leaks challenge attempts to determine the likely trajectory of the slick and to release rapid information on the oil movement and environmental and coastal impacts in the form of a bulletin broadcast 72 hours after the event. This bulletin indicates what information can be provided, evidencing the fitness for use of the current available marine datasets, as well as pointing out gaps in the current Emodnet data collection framework. The exercise relies on two tools operated by CLS: The OSCAR model (Oil Spill Contingency and Response, operated at CLS under license) made available by SINTEF and used to simulate the oil spill fate and weathering at water surface, in the water column and along shorelines. A QGIS system to display and cross the oil spill forecast with coastal data (information on environment and human activities). The declarative data given for the OSCAR simulation are: Date and time of oil spill, Location and depth of oil spill, Oil API number or oil type name, Oil spill amount or oil spill rate

This product attempt to follow up on the sea level rise per stretch of coast of the North Atlantic, over past 100 years as follows: • Characterization of absolute sea level trend at annual resolution, along the coasts of EU Member States (including Outermost Regions), Canada, Faroes, Greenland, Iceland, Mexico, Morocco, Norway and USA; The stretchs or coast are defined by the administrative regions of the Atlantic Coast: • from NUTS3** administrative division for EU countries (see Eurostat), and • from GADM*** administrative divisions for non-EU countries. ** Third level of Nomenclature of Territorial Units for Statistics *** Global Administrative Areas For absolute sea level trend for 100 years we extract the information from grided sea level reconstruction datasets (using a combination of satellite and tide gauges) and extrapolate it to the nearest strecth of coast. The product is Provided in tabular form and as a map layer.

Marché foncier en Poitou-Charentes

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 aim of the product is to represent areas where all forms of resource extraction are prohibited such as: • fishing • aggregate extraction • hydrocarbon offshore facilities • aids to navigation • habitation The product is specified through the same components as for the first product plus 2 additional ones: • Pipe lines and cables • Military activity