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

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

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

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

Map the occurrence of ice at 1-degree resolution over different periods of the last century (1915-2014, 1965-2014, 2005-2014, 2009-2014). For each entire period (100, 50, 10, 5 years) find and map all cells of the 1 degree grid that experience ice conditions in at least 1 month.

One product and 3 components were developed in order to fulfill the third objectif ATLANTIC_CH02_Product_5 / Distribution of ocean monitoring systems to assess climate change existing into the MPA network • Physical parameter monitoring • Chemical parameter monitoring • Biological parameter monitoring The aim of the product is the identification of ocean monitoring systems to assess climate change in MPAs.

'''DEFINITION''' Heat transport across lines are obtained by integrating the heat fluxes along some selected sections and from top to bottom of the ocean. The values are computed from models’ daily output. The mean value over a reference period (1993-2014) and over the last full year are provided for the ensemble product and the individual reanalysis, as well as the standard deviation for the ensemble product over the reference period (1993-2014). The values are given in PetaWatt (PW). '''CONTEXT''' The ocean transports heat and mass by vertical overturning and horizontal circulation, and is one of the fundamental dynamic components of the Earth’s energy budget (IPCC, 2013). There are spatial asymmetries in the energy budget resulting from the Earth’s orientation to the sun and the meridional variation in absorbed radiation which support a transfer of energy from the tropics towards the poles. However, there are spatial variations in the loss of heat by the ocean through sensible and latent heat fluxes, as well as differences in ocean basin geometry and current systems. These complexities support a pattern of oceanic heat transport that is not strictly from lower to high latitudes. Moreover, it is not stationary and we are only beginning to unravel its variability. '''CMEMS KEY FINDINGS''' The mean transports estimated by the ensemble global reanalysis are comparable to estimates based on observations; the uncertainties on these integrated quantities are still large in all the available products. Note: The key findings will be updated annually in November, in line with OMI evolutions. '''DOI (product):''' https://doi.org/10.48670/moi-00245

This raster dataset presents the number of different hydrographical pressures per grid cell along the European coastlines. Hydrographical pressures are human activities that cause changes in hydrological conditions, i.e. changes to freshwater input, salinity, seawater flows, waves, currents, and temperature. Examples of such activities include riverine or coastal dams, offshore infrastructure, and outflows from power plants. The layer has been created using the Water Framework Directive (WFD) reported data on hydrographical pressures joined with the water body polygon features for the reference year 2016. The dataset was then rasterized into the EEA 10 km grid, and the cell values assigned with the number of different hydrographical pressures in the area covered by the cell. This dataset has been prepared for the calculation of the combined effect index, produced for the ETC/ICM Report 4/2019 "Multiple pressures and their combined effects in Europe's seas" available on: https://www.eionet.europa.eu/etcs/etc-icm/etc-icm-report-4-2019-multiple-pressures-and-their-combined-effects-in-europes-seas-1.

Particuliers bénéficiant du portage de repas à domicile

'''This product has been archived''' '''DEFINITION''' The linear change of zonal mean subsurface temperature over the period 1993-2019 at each grid point (in depth and latitude) is evaluated to obtain a global mean depth-latitude plot of subsurface temperature trend, expressed in °C. The linear change is computed using the slope of the linear regression at each grid point scaled by the number of time steps (27 years, 1993-2019). A multi-product approach is used, meaning that the linear change is first computed for 5 different zonal mean temperature estimates. The average linear change is then computed, as well as the standard deviation between the five linear change computations. The evaluation method relies in the study of the consistency in between the 5 different estimates, which provides a qualitative estimate of the robustness of the indicator. See Mulet et al. (2018) for more details. '''CONTEXT''' Large-scale temperature variations in the upper layers are mainly related to the heat exchange with the atmosphere and surrounding oceanic regions, while the deeper ocean temperature in the main thermocline and below varies due to many dynamical forcing mechanisms (Bindoff et al., 2019). Together with ocean acidification and deoxygenation (IPCC, 2019), ocean warming can lead to dramatic changes in ecosystem assemblages, biodiversity, population extinctions, coral bleaching and infectious disease, change in behavior (including reproduction), as well as redistribution of habitat (e.g. Gattuso et al., 2015, Molinos et al., 2016, Ramirez et al., 2017). Ocean warming also intensifies tropical cyclones (Hoegh-Guldberg et al., 2018; Trenberth et al., 2018; Sun et al., 2017). '''CMEMS KEY FINDINGS''' The results show an overall ocean warming of the upper global ocean over the period 1993-2019, particularly in the upper 300m depth. In some areas, this warming signal reaches down to about 800m depth such as for example in the Southern Ocean south of 40°S. In other areas, the signal-to-noise ratio in the deeper ocean layers is less than two, i.e. the different products used for the ensemble mean show weak agreement. However, interannual-to-decadal fluctuations are superposed on the warming signal, and can interfere with the warming trend. For example, in the subpolar North Atlantic decadal variations such as the so called ‘cold event’ prevail (Dubois et al., 2018; Gourrion et al., 2018), and the cumulative trend over a quarter of a decade does not exceed twice the noise level below about 100m depth. Note: The key findings will be updated annually in November, in line with OMI evolutions. '''DOI (product):''' https://doi.org/10.48670/moi-00244