The GEBCO_2020 Grid was released in May 2020 and is the second global bathymetric product released by the General Bathymetric Chart of the Oceans (GEBCO) and has been developed through the Nippon Foundation-GEBCO Seabed 2030 Project. The GEBCO_2020 Grid provides global coverage of elevation data in meters on a 15 arc-second grid of 43200 rows x 86400 columns, giving 3,732,480,000 data points. Grid Development The GEBCO_2020 Grid is a continuous, global terrain model for ocean and land with a spatial resolution of 15 arc seconds. The grid uses as a ‘base’ Version 2 of the SRTM15+ data set (Tozer et al, 2019). This data set is a fusion of land topography with measured and estimated seafloor topography. It is augmented with the gridded bathymetric data sets developed by the four Seabed 2030 Regional Centers. The Regional Centers have compiled gridded bathymetric data sets, largely based on multibeam data, for their areas of responsibility. These regional grids were then provided to the Global Center. For areas outside of the polar regions (primarily south of 60°N and north of 50°S), these data sets are in the form of 'sparse grids', i.e. only grid cells that contain data were populated. For the polar regions, complete grids were provided due to the complexities of incorporating data held in polar coordinates. The compilation of the GEBCO_2020 Grid from these regional data grids was carried out at the Global Center, with the aim of producing a seamless global terrain model. In contrast to the development of the previous GEBCO grid, GEBCO_2019, the data sets provided as sparse grids by the Regional Centers were included on to the base grid without any blending, i.e. grid cells in the base grid were replaced with data from the sparse grids. This was with aim of avoiding creating edge effects, 'ridges and ripples', at the boundaries between the sparse grids and base grid during the blending process used previously. In addition, this allows a clear identification of the data source within the grid, with no cells being 'blended' values. Routines from Generic Mapping Tools (GMT) system were used to do the merging of the data sets. For the polar data sets, and the adjoining North Sea area, supplied in the form of complete grids these data sets were included using feather blending techniques from GlobalMapper software version 11.0, made available by Blue Marble Geographic. The GEBCO_2020 Grid includes data sets from a number of international and national data repositories and regional mapping initiatives. For information on the data sets included in the GEBCO_2020 Grid, please see the list of contributions included in this release of the grid (https://www.gebco.net/data_and_products/gridded_bathymetry_data/gebco_2020/#compilations).

Species distribution models (GAM, Maxent and Random Forest ensemble) predicting the distribution of Syringammina fragilissima fields assemblage in the North East Atlantic. This community is considered ecologically coherent according to the cluster analysis conducted by Parry et al. (2015) on image sample. Modelling its distribution complements existing work on their definition and offers a representation of the extent of the areas of the North East Atlantic where they can occur based on the best available knowledge. This work was performed at the University of Plymouth in 2021.

This raster dataset represents input of impulsive anthropogenic sound in Europe Seas. Impulsive sounds are typically brief with a rapid rise time, i.e. a great change in amplitude over a short period of time. The main anthropogenic sources of impulsive underwater noise are typically impact pile driving for inshore and offshore construction, seismic exploration with airguns, explosions and sonar systems. The dataset was created by combining pulse-block-days (PBD) data from the ICES Registry (for HELCOM and OSPAR areas) and ACCOMBAS (for the Mediterranean Sea), resampled using the EEA 10 km grid. The dataset does not include the Black Sea. The temporal reference of this dataset is the period 2014-2016. The cell values have been transformed into a logarithmic scale (log10). 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.

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.

Species distribution models (Maxent) predicting the distribution of two Vulnerable Marine Ecosystems (VME): the reef-forming Scleractinian coral Desmophyllum pertusum and the aggregations forming Hexactinellid sponge Pheronema carpenteri. Both of these species are VME indicator taxa and form habitat that enhance deep-sea diversity (Ross and Howell, 2013). Maps of the likely distribution of the habitat formed by these two species will enable efficient Marine Spatial planning to facilitate their conservation. This work was performed at the University of Plymouth in 2021. A GIS layer is provided for each species.

Classification of the seabed in the Atlantic Ocean into broad-scale benthic habitats employing a non-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. The numbers in the raster layer correspond to individual classes. Description of these classes is given in McQuaid, K.A. et al. (2023).

This dataset is the coastal zone land surface region from Europe, derived from the coastline towards inland, as a series of 10 consecutive buffers of 1km width each. The coastline is defined by the extent of the Corine Land Cover 2018 (raster 100m) version 20 accounting layer. In this version all Corine Land Cover pixels with a value of 523, corresponding to sea and oceans, were considered as non-land surface and thus were excluded from the buffer zone.