The development of the ecosystem approach and models for the management of ocean marine resources requires easy access to standard validated datasets of historical catch data for the main exploited species. They are used to measure the impact of biomass removal by fisheries and to evaluate the models skills, while the use of standard dataset facilitates models inter-comparison. North Atlantic albacore tuna is exploited all year round by longline and in summer and autumn by surface fisheries and fishery statistics compiled by the International Commission for the Conservation of Atlantic Tunas (ICCAT). Catch and effort with geographical coordinates at monthly spatial resolution of 1° or 5° squares were extracted for this species with a careful definition of fisheries and data screening. In total, thirteen fisheries were defined for the period 1956-2010, with fishing gears longline, troll, mid-water trawl and bait fishing. However, the spatialized catch effort data available in ICCAT database represent a fraction of the entire total catch. Length frequencies of catch were also extracted according to the definition of fisheries above for the period 1956-2010 with a quarterly temporal resolution and spatial resolutions varying from 1°x 1° to 10°x 20°. The resolution used to measure the fish also varies with size-bins of 1, 2 or 5 cm (Fork Length). The screening of data allowed detecting inconsistencies with a relatively large number of samples larger than 150 cm while all studies on the growth of albacore suggest that fish rarely grow up over 130 cm. Therefore, a threshold value of 130 cm has been arbitrarily fixed and all length frequency data above this value removed from the original data set.

Excel file containing CPR data from Standard Areas B4,C3,C4,D3,D4,D5,E4,F4 for the plankton Calanus finmarchicus and helgolandicus, total traverse (small) copepods, total large copepods, Phytoplankton Colour Index and Cnidaria (presence denoted by a 1, absence by a zero). All taxa are from 1980, except Cnidaria which are from 2011. Dataset is in the format of sample level data, with each row being a discrete sample, with a sample being 3m3 filtered seawater, and 10nm of tow. For each row, a sample has the following information, starting at column a: Standard area of sample, sample id, latitude (decimal degrees) of sample mid point, longitude (decimal degrees) of sample midpoint, sample midpoint date and local time, year of sample, month of sample, then plankton abundance values (or PCI index or cnidaria presence/absence). All taxa have been looked for during the period this dataset spans, so zero values represent true absence.

This is a compilation of OSPAR habitat point data for the northeast Atlantic submitted by OSPAR contracting parties. The compilation is coordinated by the UK's Joint Nature Conservation Committee, working with a representative from each of the OSPAR coastal contracting parties. This public dataset does not contain records relating to sensitive species (e.g. Ostrea edulis) in specific areas, or where data are restricted from public release by the owner's use limitations. This version (v2020) was published in July 2021.

This dataset containing traits of marine fish is based on fish taxa observed during international scientific bottom-trawl surveys regularly conducted in the Northeast Atlantic, Northwest Atlantic and the Northeast Pacific. These scientific surveys target primarily demersal (bottom-dwelling) fish species, but pelagic species are also regularly recorded. The overarching aim of this dataset was to collect information on ecological traits for as many fish taxa as possible and to find area-specific trait values to account for intraspecific variation in traits, especially for widely distributed species. We collected traits for species, genera and families. The majority of trait values were sourced from FishBase (Froese and Pauly, 2019), and have been supplemented with values from the primary literature.

NOAA High-resolution Blended Analysis of Daily SST and Ice. Data is from Sep 1981 and is on a 1/4 deg global grid.

Intermediate Assessment 2017 - Seabed Litter - Litter is widespread on the seafloor across the area assessed, with plastic being the predominant material encountered. In the areas assessed, higher amounts of litter are found in the Eastern Bay of Biscay, Southern Celtic Seas and English Channel relative to the north of the Greater North Sea and Celtic Seas.

All statistics of UNCTAD are harmonized and integrated into UNCTADstat- free to use dissemination platform. It gives access to basic and derived indicators built upon common rules, harmonized environment and clear methodology supported by powerful data browsing system. The statistical series are regularly updated and classified into easy-to-navigate themes. UNCTADstat offers ready-to-use analytical groupings, with a unique coverage for countries and products and a particular focus on developing and transition economies. This approach ensures data consistency across multiple data series, and enables users to harness its full potential by mixing and matching data from various domains. The navigation browser allows table or graphic presentations, easy selection and reorganization of data, personalized functionalities and several straightforward extraction options.

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 abundance of ichthyoplankton in samples from dedicated plankton surveys by Cefas with positional and sample data. Surveys took place off the Western Coast of the UK and Ireland between 1986 and 2004. Series of cruises undertaken to contribute to the estimation of the spawning stock biomass of the western mackerel and horse mackerel stocks by plankton survey. The triennial mackerel egg surveys were begun in 1977 to estimate the SSB of the western mackerel stock. Since 1986 the surveys have also been used to estimate the SSB of horse mackerel. Plankton sampling is undertaken to estimate the egg production and trawling is carried out to estimate the mean fecundity of the mature female fish. Various designs of Gulf VII type samplers have been used with various apertures of nosecones and 270 micron nets. Samplers are now standardised to the 53cm version, fitted with 20cm aperture nosecones. Analysis at Cefas involved separating all fish eggs and larvae from samples. Where possible all eggs were identified. Eggs lacking identifiable features were measured. Where >100 eggs were found, sub-sampling was undertaken. Eggs that were unmeasured were apportioned across the size distribution of measured eggs. All mackerel and horse mackerel eggs were staged.

JRA55-do is a surface dataset for driving ocean-sea ice models and used in phase 2 of OMIP (OMIP-2). JRA55-do corrects the atmospheric reanalysis product JRA-55 (Kobayashi et al., 2015) using satellite and other atmospheric reanalysis products. The merits of JRA55-do are the high horizontal resolution (~55 km) and temporal interval (3 h). An assessment by Tsujino et al. (2020) implies that JRA55-do can suitably replace the current CORE/OMIP-1 dataset. This reanalysis of atmospheric variables is provided by the Japanese Meteorological Agency starting in the year 1958 and will be used to drive the coupled NEMO-ERSEM model in the hindcast configuration.