Maps of seasonal p90 (percentile 90) of Chla on the North Atlantic basin for the past ten years (2005-2014) using the Global Copernicus chla level 4 (L4) products (resolution of 4 km). Method as Gohin Francis, Saulquin Bertrand, Bryere Philippe (2010) Atlas de la Température, de la concentration en Chlorophylle et de la Turbidité de surface du plateau continental français et de ses abords de l’Ouest européen. Ifremer. http://archimer.ifremer.fr/doc/00057/16840/

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 raster dataset represents the intensity of species disturbance due to human presence along European coastlines. The dataset was created by combining the coastal urbanisation layer derived from Corine Land Cover 2012 (with the percentage of urbanised coastline per EEA 10 km grid cell) and the population density layer based on EUROSTAT NUTS 2016 data (with the population density in the NUTS 3 region corresponding to the coastal EEA 10 km grid cell). The dataset does not cover southern and western Mediterranean Sea, northern Black Sea and northernmost Atlantic Ocean. The dataset was prepared for 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.

The data set aims to contribute to a better biological characterization of European marine ecosystems. As such it represents probabilities of EUNIS (EUropean Nature Information System) habitat presence at Level 3 for marine habitats including information on sea ice coverage (this corresponds to EUNIS level 2 for terrestrial habitats). The map combines spatially explicit data on marine bathymetry and sea-bed with non-spatially referenced habitat information of the EUNIS classification. The objective of the data set produced by EEA and its Topic Centre ETC/ULS is to improve the biological description of marine based ecosystem types and their spatial distribution. The work supports Target 2 Action 5 of the implementation of the EU Biodiversity Strategy to 2020, established to achieve the Aichi targets of the Convention of Biological Diversity (CBD). It further addresses the MAES process (Mapping and Assessing of Ecosystems and their Services). The data set represents 2 classes of the MAES classification level 3, namely “Marine inlets and transitional waters” and “Marine”. The dataset comprises the following information: • Sea region (1 – Arctic, 2 – Atlantic, 3 – Baltic, 4 – Mediterranean, 5 – Black Sea) • Sea zone (1 – Littoral, 2 – Infralittoral, 3 – Circalittoral, 4 – Offshore circalittoral, 5 – Upper bathyal, 6 – Lower bathyal, 7 – Abyssal,8 - Coastal Lagoons, 9 - Coastal Lagoons) • Substrate (0 – undetermined substrate, 1 – rock and biogenic, 3 – coarse sediment, 4 – mixed sediment, 5 – sand, 6 – mud) • Sea ice coverage (0 – no sea ice presence, 1 – seasonal sea ice presence, 2 – perennial sea ice presence)

Classification of the Atlantic Ocean seabed into broad-scale benthic habitats employing a hierarchical top-down clustering approach aimed at informing Marine Spatial Planning. This work was performed at the University of Plymouth in 2021 with data provided by a wide group of partners representing the nations surrounding the Atlantic Ocean. It classifies continuous environmental data into discrete classes that can be compared to observed biogeographical patterns at various scales. It has 3 levels of classification. For ease of use, a layer is provided for each level. Level 1 has 4 classes. Level 2 has 15 classes nested within level 1. Layers indices are 2 digits (1[level1 class index]1[level 2 class index]). Level 3 has 157 classes nested within level 2 and class names have 4 digits (1digit[level1 class index]1[level 2 class index]2[level 3 class index]). Note that the classification was performed for the whole world and thus it has more classes than in the presented layer.

ERA5 is the fifth generation ECMWF reanalysis for the global climate and weather for the past 4 to 7 decades. Currently data is available from 1950, split into Climate Data Store entries for 1950-1978 (preliminary back extension) and from 1979 onwards (final release plus timely updates, this page). ERA5 replaces the ERA-Interim reanalysis. Reanalysis combines model data with observations from across the world into a globally complete and consistent dataset using the laws of physics. This principle, called data assimilation, is based on the method used by numerical weather prediction centres, where every so many hours (12 hours at ECMWF) a previous forecast is combined with newly available observations in an optimal way to produce a new best estimate of the state of the atmosphere, called analysis, from which an updated, improved forecast is issued. Reanalysis works in the same way, but at reduced resolution to allow for the provision of a dataset spanning back several decades. Reanalysis does not have the constraint of issuing timely forecasts, so there is more time to collect observations, and when going further back in time, to allow for the ingestion of improved versions of the original observations, which all benefit the quality of the reanalysis product. ERA5 provides hourly estimates for a large number of atmospheric, ocean-wave and land-surface quantities. An uncertainty estimate is sampled by an underlying 10-member ensemble at three-hourly intervals. Ensemble mean and spread have been pre-computed for convenience. Such uncertainty estimates are closely related to the information content of the available observing system which has evolved considerably over time. They also indicate flow-dependent sensitive areas. To facilitate many climate applications, monthly-mean averages have been pre-calculated too, though monthly means are not available for the ensemble mean and spread. ERA5 is updated daily with a latency of about 5 days (monthly means are available around the 6th of each month). In case that serious flaws are detected in this early release (called ERA5T), this data could be different from the final release 2 to 3 months later. So far this has not been the case and when this does occur users will be notified. The data set presented here is a regridded subset of the full ERA5 data set on native resolution. It is online on spinning disk, which should ensure fast and easy access. It should satisfy the requirements for most common applications. An overview of all ERA5 datasets can be found in this article. Information on access to ERA5 data on native resolution is provided in these guidelines. Data has been regridded to a regular lat-lon grid of 0.25 degrees for the reanalysis and 0.5 degrees for the uncertainty estimate (0.5 and 1 degree respectively for ocean waves). There are four main sub sets: hourly and monthly products, both on pressure levels (upper air fields) and single levels (atmospheric, ocean-wave and land surface quantities). The present entry is "ERA5 monthly mean data on single levels from 1979 to present".

The raster dataset represents the risk of collision of whales with vessels in Europe Seas. The most vulnerable species from ship strikes are cetaceans and turtles, since they go to the surface to breathe. On the other hand, their migration routes can overlap with shipping lanes. The collisions can produce the death or injury of the animals, and are an important threat for the conservation of these species. The dataset has been prepared in the context of the development of the first European Maritime Transport Environmental Report (EMSA-EEA report, 2021: https://www.eea.europa.eu/publications/maritime-transport).