The gyre index constructed here from satellite altimetry is related to core aspects of the North Atlantic subpolar gyre, meridional overturning circulation, hydrographic properties in the Atlantic inflows toward the Arctic, and in marine ecosystems in the northeast Atlantic Ocean. The data series spans the period January 1993 to September 2018. Data description: Monthly gyre index from January 1993 until September 2018. The data is provided in one comma separated value (csv) file with the following entries on each row: year, month, index value. The index is normalized, i.e. it has a zero mean and unit standard deviation. Positive (negative) gyre index reflects stronger (weaker) than average surface circulation of the North Atlantic subpolar gyre.

The Commission for the Conservation Southern Bluefin Tuna collects a variety of data types from its Members and Cooperating Non-Members, including total catch, catch and effort data, and catch at size data. Catch, size and trade information is also collected through the Commission's Catch Documentation Scheme, Japanese import statistics, and other monitoring programs. Annual catches provided on this page are reported on a calendar year basis. CCSBT Members use quota years (not calendar years) for managing catching limits, but quota years differ between Members, so calendar years are used to provide catches on a common timescale. Relevant subsets and summaries of these data are provided below. All figures are subject to change as improved data or estimates become available. In particular, reviews of SBT data in 2006 indicated that southern bluefin tuna catches may have been substantially under-reported over the previous 10-20 years and the data presented here do not include estimates for this unreported catch. Also, data for the last reported year of catch (2020) are preliminary and are subject to revision. Any latitudes and longitudes presented in these summaries represent the north western corner of the relevant grid, which is a 5*5 grid unless otherwise specified. Other information on Members and Cooperating Non-Members fishing activities appears in the reports of the Extended Scientific Committee, Compliance Committee and Extended Commission.

The RAM Legacy Stock Assessment Database is a compilation of stock assessment results for commercially exploited marine populations from around the world. The RAM Legacy Stock Assessment Database is grateful to the many stock assessment scientists whose work this database is based upon and the many collaborators who recorded the assessment model results for inclusion in the RAM Legacy Stock Assessment Database. Since 2011 the RAM Legacy Data base has been hosted and managed at the University of Washington with financial assistance from a consortium of Seattle-based seafood companies and organizations, and from the Walton Family Foundation. Initial development of the database from 2006-2010 was supported by the Census of Marine Life, Canadian Foundation for Innovation, NCEAS, NSERC, the Smith Conservation Research Fellowship, New Jersey Sea Grant, and the National Science Foundation.

This is the FAO Fishery and Aquaculture Reference Data repository: Codes and reference data for fishing gear, species, currencies, commodities, countries and others.

We assembled a dataset of 14C-based productivity measurements to understand the critical variables required for accurate assessment of daily depth-integrated phytoplankton carbon fixation (PP(PPeu)u) from measurements of sea surface pigment concentrations (Csat)(Csat). From this dataset, we developed a light-dependent, depth-resolved model for carbon fixation (VGPM) that partitions environmental factors affecting primary production into those that influence the relative vertical distribution of primary production (Pz)z) and those that control the optimal assimilation efficiency of the productivity profile (P(PBopt). The VGPM accounted for 79% of the observed variability in Pz and 86% of the variability in PPeu by using measured values of PBopt. Our results indicate that the accuracy of productivity algorithms in estimating PPeu is dependent primarily upon the ability to accurately represent variability in Pbopt. We developed a temperature-dependent Pbopt model that was used in conjunction with monthly climatological images of Csat sea surface temperature, and cloud-corrected estimates of surface irradiance to calculate a global annual phytoplankton carbon fixation (PPannu) rate of 43.5 Pg C yr‒1. The geographical distribution of PPannu was distinctly different than results from previous models. Our results illustrate the importance of focusing Pbopt model development on temporal and spatial, rather than the vertical, variability.

Several climate indices, regarding Atlantic Basin: - North Atlantic Oscillation - Southern Oscillation Index - Bivariate ENSO Timeseries - Tropical Northern Atlantic Index - Tropical Southern Atlantic Index - Oceanic Niño Index - Multivariate ENSO Index (MEI V2) - North Tropical Atlantic SST Index - ENSO precipitation index - Northeast Brazil Rainfall Anomaly - Solar Flux (10.7cm) - Global Mean Lan/Ocean Temperature

World Ocean Atlas 2018 (WOA18) is a set of objectively analyzed (one degree grid and quarter degree grid) climatological fields of in situ temperature, salinity, dissolved oxygen, Apparent Oxygen Utilization (AOU), percent oxygen saturation, phosphate, silicate, and nitrate at standard depth levels for annual, seasonal, and monthly compositing periods for the World Ocean. Quarter degree fields are for temperature and salinity only. It also includes associated statistical fields of observed oceanographic profile data interpolated to standard depth levels on quarter degree, one degree, and five degree grids. Temperature and salinity fields are available for six decades (1955-1964, 1965-1974, 1975-1984, 1985-1994, 1995-2004, and 2005-2017) an average of all decades representing the period 1955-2017, as well as a thirty year "climate normal" period 1981-2010. Oxygen fields (as well as AOU and percent oxygen saturation) are available using all quality controlled data 1960-2017, nutrient fields using all quality controlled data from the entire sampling period 1878-2017. This accession is a product generated by the National Centers for Environmental Information's (NCEI) Ocean Climate Laboratory Team. The analyses are derived from the NCEI World Ocean Database 2018.

This dataset comprises the global frequency, classification and distribution of marine heat waves (MHWs) from 1996-2020, in Chauhan et al. 2023 (https://doi.org/10.3389/fmars.2023.1177571). The classification was done based on their attributes and using different baselines. Daily SST values were extracted from the NOAA-OISST v2 high-resolution (0.25°) dataset from 1982-2020. MHWs were detected using the method presented by Hobday et al. 2016 (https://doi.org/10.1016/j.pocean.2015.12.014), and by using the 95th percentile of the accumulated temperature distribution to flag the extreme events. A shifting baseline of 8-year rolling period was selected between the years 1982-1996, since this period shows relatively stable maximum values of temperature across different ocean regions. The shifting baseline aims to account for the decadal changes of westerly winds, temperatures and ocean gyres circulations. The classification was done using the KMeans clustering algorithm to identify the relevant features of MHWs and classify them into separate groups based on feature similarities. This algorithm takes MHW features, namely duration, maximum intensity, rate onset and rate decline, as input vectors and applies clustering in the 4-dimensional feature space where each data point represents an MHW event. Note that all the MHWs features are standardized because unequal variances can put more weight on variables with smaller variances. This record comprehends the geospatial datasets of: Average number of MHW days per year (i.e., the sum of all MHW days divided by the total number of years, 1996-2020). Average cumulative intensity per year (i.e., the sum of cumulative intensity divided by the total number of years, 1996-2020). Total number of MHW events across the different periods averaged on the total number of years (1989-2020). The period 1982-1988 was only used as an initial baseline without calculating MHWs. Spatial distribution of three MHW categories: moderate MHWs, abrupt and Intense MHWs and extreme MHWs; displaying the total number of MHW days normalized by the number of years considered (i.e., 1989-2020). Distribution of Extreme MHWs across the different periods (A) 1989-1996, (B) 1997-2004, (C) 2005-2012, (D) 2013-2020. The relative frequency (γ) is a ratio of extreme MHWs in a specific period and all extreme MHWs in the same cluster for all periods.

'''Short description''' The biogeochemical hindcast for global ocean is produced at Mercator-Ocean (Toulouse. France). It provides 3D biogeochemical fields since year 1993 at 1/4 degree and on 75 vertical levels. It uses PISCES biogeochemical model (available on the NEMO modelling platform). No data assimilation in this product. * Latest NEMO version (v3.6_STABLE) * Forcings: FREEGLORYS2V4 ocean physics produced at Mercator-Ocean and ERA-Interim atmosphere produced at ECMWF at a daily frequency * Outputs: Daily (chlorophyll. nitrate. phosphate. silicate. dissolved oxygen. primary production) and monthly (chlorophyll. nitrate. phosphate. silicate. dissolved oxygen. primary production. iron. phytoplankton in carbon) 3D mean fields interpolated on a standard regular grid in NetCDF format. The simulation is performed once and for all. * Initial conditions: World Ocean Atlas 2013 for nitrate. phosphate. silicate and dissolved oxygen. GLODAPv2 for DIC and Alkalinity. and climatological model outputs for Iron and DOC * Quality/Accuracy/Calibration information: See the related QuID '''DOI (product):''' https://doi.org/10.48670/moi-00019

'''Short description:''' The GLORYS12V1 product is the CMEMS global ocean eddy-resolving (1/12° horizontal resolution, 50 vertical levels) reanalysis covering the altimetry (1993 onward). It is based largely on the current real-time global forecasting CMEMS system. The model component is the NEMO platform driven at surface by ECMWF ERA-Interim then ERA5 reanalyses for recent years. Observations are assimilated by means of a reduced-order Kalman filter. Along track altimeter data (Sea Level Anomaly), Satellite Sea Surface Temperature, Sea Ice Concentration and In situ Temperature and Salinity vertical Profiles are jointly assimilated. Moreover, a 3D-VAR scheme provides a correction for the slowly-evolving large-scale biases in temperature and salinity. This product includes daily and monthly mean files for temperature, salinity, currents, sea level, mixed layer depth and ice parameters from the top to the bottom. The global ocean output files are displayed on a standard regular grid at 1/12° (approximatively 8 km) and on 50 standard levels. '''DOI (product) :''' https://doi.org/10.48670/moi-00021