Annual time series of eel recruitement, (2005-2014) • Time series of glass and yellow eel for those rivers used in the annual ICES advice to the EU • Location, data availability and long term annual (LTA) eel recruiment per river mouth

List of fish stocks referenced for the year 2018. The repository includes 477 stocks. Each stock is identified by a unique key in accordance with the ICES codification in use. Each record contains a stock identifier, a species or group of species identifier according to the ASFIS/FAO classification, the English stock name, the Latin name of the species, the assessment area according to the FAO codification of fishing sectors. When the stock assessment area groups a series of sectors, the first and last sectors in the series are separated by a dash.

North Atlantic basin average at Pentadal (5-year) resolution time-series of the ocean heat storage (upper 700m) and kinetic energy. Use gridded information to calculate the local heat storage and average kinetic energy as a 5 year average and then calculate the basin average.

Map at 1 degree resolution of 50-year linear trend in sea water temperature at 3 levels: surface, 500m, bottom.

The impact of fishing on benthic habitats has previously been investigated however; a conclusive classification of potentially sensitive habitats per gear type does not exist. Currently only qualitative estimates of fishery impact using Broad-scale habitat maps are possible. Here a sensitivity matrix using both fishing pressure (fishing Intensity) and habitat sensitivity is employed to define habitat disturbance categories. The predominant fishing activities associated with physical abrasion of the seafloor area are from bottom contacting towed fishing gear. The swept area of the aforementioned gear in contact with the seabed is generally considered a function of gear width, vessel speed and fishing effort (ICES. 2015). The varying characteristics of fishing gear, their interaction with the sea floor and species being targeted; provide scope for differing interactions with subsurface (infaunal) and surface (epifaunal) dwelling communities. An evaluation of the abrasion pressure and habitat sensitivity split into surface and subsurface pressure allows greater insight to the ecological effects. Fishing intensity was calculated annually and based on the area of sea floor being swept (or swept area ratio SAR) by gear type. Calculations are based on SAR’s of gear types per area, per year. Fishing pressure ranks and habitat sensitivity ranks obtained from WGSFD working group (01 WGSFD - Report of the Working Group on Spatial Fisheries Data 2015) can be incorporated within a GIS environment to existing ICES fisheries data to provide habitat disturbance maps (fishing pressure maps+ habitat sensitivity maps) ICES. 2015. Report of the Working Group on Spatial Fisheries Data (WGSFD), 8–12 June 2015, ICES Headquarters, Copenhagen, Denmark. ICES CM 2015/SSGEPI:18. 150 pp.

'''This product has been archived''' '''DEFINITION''' Estimates of Ocean Heat Content (OHC) are obtained from integrated differences of the measured temperature and a climatology along a vertical profile in the ocean (von Schuckmann et al., 2018). The regional OHC values are then averaged from 60°S-60°N aiming i) to obtain the mean OHC as expressed in Joules per meter square (J/m2) to monitor the large-scale variability and change. ii) to monitor the amount of energy in the form of heat stored in the ocean (i.e. the change of OHC in time), expressed in Watt per square meter (W/m2). Ocean heat content is one of the six Global Climate Indicators recommended by the World Meterological Organisation for Sustainable Development Goal 13 implementation (WMO, 2017). '''CONTEXT''' Knowing how much and where heat energy is stored and released in the ocean is essential for understanding the contemporary Earth system state, variability and change, as the ocean shapes our perspectives for the future (von Schuckmann et al., 2020). Variations in OHC can induce changes in ocean stratification, currents, sea ice and ice shelfs (IPCC, 2019; 2021); they set time scales and dominate Earth system adjustments to climate variability and change (Hansen et al., 2011); they are a key player in ocean-atmosphere interactions and sea level change (WCRP, 2018) and they can impact marine ecosystems and human livelihoods (IPCC, 2019). '''CMEMS KEY FINDINGS''' Since the year 2005, the near-surface (0-300m) near-global (60°S-60°N) ocean warms at a rate of 0.4 ± 0.1 W/m2. Note: The key findings will be updated annually in November, in line with OMI evolutions. '''DOI (product):''' https://doi.org/10.48670/moi-00233

Map at 1 degree resolution of 50-year linear trend in sea water temperature at 3 levels: surface, 500m, bottom.

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.

'''This product has been archived'''                For operationnal and online products, please visit https://marine.copernicus.eu '''DEFINITION''' The indicator of the Kuroshio extension phase variations is based on the standardized high frequency altimeter Eddy Kinetic Energy (EKE) averaged in the area 142-149°E and 32-37°N and computed from the DUACS (https://duacs.cls.fr) delayed-time (reprocessed version DT-2021, CMEMS SEALEVEL_GLO_PHY_L4_MY_008_047) and near real-time (CMEMS SEALEVEL_GLO_PHY_L4_NRT_OBSERVATIONS_008_046) altimeter sea level gridded products. The change in the reprocessed version (previously DT-2018) and the extension of the mean value of the EKE (now 27 years, previously 20 years) induce some slight changes not impacting the general variability of the Kuroshio extension (correlation coefficient of 0.988 for the total period, 0.994 for the delayed time period only). '''CONTEXT''' The long-term mean and trends alone do not give a complete view of the likely changes in position of unstable western boundary current extensions (Kelly et al., 2010). The Kuroshio Extension is an eastward-flowing current in the subtropical western North Pacific after the Kuroshio separates from the coast of Japan at 35°N, 140°E. Being the extension of a wind-driven western boundary current, the Kuroshio Extension is characterized by a strong variability and is rich in large-amplitude meanders and energetic eddies (Niiler et al., 2003; Qiu, 2003, 2002). The Kuroshio Extension region has the largest sea surface height variability on sub-annual and decadal time scales in the extratropical North Pacific Ocean (Jayne et al., 2009; Qiu and Chen, 2010, 2005). Prediction and monitoring of the path of the Kuroshio are of huge importance for local economies as the position of the Kuroshio extension strongly determines the regions where phytoplankton and hence fish are located. '''CMEMS KEY FINDINGS''' The different states of the Kuroshio extension phase have been presented and validated by Bessières et al. (2013) and further reported by Drévillon et al. (2018) in the Copernicus Ocean State Report #2. Two rather different states of the Kuroshio extension are observed: an ‘elongated state’ (also called ‘strong state’) corresponding to a narrow strong steady jet, and a ‘contracted state’ (also called ‘weak state’) in which the jet is weaker and more unsteady, spreading on a wider latitudinal band. When the Kuroshio Extension jet is in a contracted (elongated) state, the upstream Kuroshio Extension path tends to become more (less) variable and regional eddy kinetic energy level tends to be higher (lower). In between these two opposite phases, the Kuroshio extension jet has many intermediate states of transition and presents either progressively weakening or strengthening trends. In 2018, the indicator reveals an elongated state followed by a weakening neutral phase since then. '''DOI (product):''' https://doi.org/10.48670/moi-00222

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.