This dataset contains the dynamical outputs of a global ocean simulation coupling dynamics and biogeochemistry at ¼° over the year 2019. The simulation has been performed using the coupled circulation/ecosystem model NEMO/PISCES (https://www.nemo-ocean.eu/), which is here enhanced to perform an ensemble simulation with explicit simulation of modeling uncertainties in the physics and in the biogeochemistry. This dataset is one of the 40 members of the ensemble simulation. This study was part of the Horizon Europe project SEAMLESS (https://seamlessproject.org/Home.html), with the general objective of improving the analysis and forecast of ecosystem indicators.   See Popov et al. (https://os.copernicus.org/articles/20/155/2024/) for more details on the study.

The Coriolis Ocean Dataset for Reanalysis for the Ireland-Biscay-Iberia region (hereafter CORA-IBI) product is a regional dataset of in situ temperature and salinity measurements. The latest version of the product covers the period 1950-2014. The CORA-IBI observations comes from many different sources collected by Coriolis data centre in collaboration with the In Situ Thematic Centre of the Copernicus Marine Service (CMEMS INSTAC).  The observations integrated in the CORA-IBI product have been acquired both by autonomous platforms (Argo profilers, fixed moorings, gliders, drifters, sea mammals, fishery observing system from the RECOPESCA program), research or opportunity vessels ( CTDs, XBTs, ferrybox).  This CORA-IBI product has been controlled using an objective analysis (statistical tests) method and a visual quality control (QC). This QC procedure has been developed with the main objective to improve the quality of the dataset to the level required by the climate application and the physical ocean re-analysis activities. It provides T and S individual profiles on their original level with QC flags. The reference level of measurements is immersion (in meters) or pressure (in decibars). It is a subset on the IBI (Iberia-Bay-of-Biscay Ireland) of the CMEMS product referenced hereafter. The main new features of this regional product compared with previous global CORA products are the incorporation of coastal profiles from fishery observing system (RECOPESCA programme) in the Bay of Biscay and the English Channel as well as the use of an historical dataset collected by the Service hydrographique de la Marine (SHOM).

The DBCP – Data Buoy Cooperation Panel - is an international program coordinating the use of autonomous data buoys to observe atmospheric and oceanographic conditions, over ocean areas where few other measurements are taken. DBCP coordinates the global array of 1 600 active drifting buoys (August 2020) and historical observation from 14 000 drifting buoys. Data and metadata collected by drifting buoys are publically available in near real-time via the Global Data Assembly Centers (GDACs) in Coriolis-Ifremer (France) and MEDS (Canada) after an automated quality control (QC). In long term, scientifically quality controlled delayed mode data will be distributed on the GDACs. Disclaimer: the DB-GDAC is under construction. It is currently (January 2020) aggregating data from the Coriolis DAC (E-Surfmar, Canada). Additional DACs are considered. An interim provision from GTS real-time data to GDAC may be provided from Coriolis DAC.  

This dataset provides a global Look-Up Table (LUT) of physiological ratios for the real-time adjustment of chlorophyll-a fluorescence measured by biogeochemical Argo (BGC-Argo) profiling floats. The physiological ratios aim to account for the global variability in the relationship between fluorescence and chlorophyll-a concentration, as influenced by phytoplankton physiology. The LUT was developed using two different gap-filled observational Argo-based products (SOCA machine learning-based methodology ; Sauzède et al., 2016; Sauzède et al., 2024). The first product provides gap-filled chlorophyll-a data derived from fluorescence corrected for dark signal and non-photochemical quenching (NPQ) following Schmechtig et al. (2023), while the second product provides chlorophyll-a concentrations derived from light attenuation. The latter is based on the downward irradiance at 490 nm (ED490) derived from the SOCA-light method (Renosh et al., 2023). From this, the diffuse attenuation coefficient (KD490) is computed, which is subsequently used to estimate the chlorophyll-a concentration through the bio-optical relationships described by Morel et al. (2007). These two products, based on fluorescence and radiometry, enable the derivation of spatially varying correction factors, or physiological ratios. These ratios provide a validated grounded framework for adjusting real-time fluorescence observations from OneArgo floats into chlorophyll-a concentrations. The LUT is distributed in NetCDF format and is provided on a regular 1°×1° latitude–longitude grid covering the global ocean. Each grid cell contains the temporal mean, averaged over the water column (from the surface to 1.5 times the euphotic depth), of the physiological ratio. The file also includes metadata describing variable definitions, units, and other relevant information. Variables included: - physiological_ratio — fluorescence-to-radiometry-based chlorophyll correction factor (dimensionless) - physiological_ratio_sd — temporal standard deviation (over the twelve months) of the fluorescence-to-radiometry-based chlorophyll correction factor (dimensionless) - lat, lon — spatial coordinates (degrees north/east) - Global attributes — dataset description, reference citation, and contact information

The glider operations in the MOOSE network started to be deployed regularly in 2010 in the North Western Mediterranean Sea, thanks to the setup of national glider facilities at DT-INSU/Ifremer (http://www.dt.insu.cnrs.fr/gliders/gliders.php) and with the support of the European project FP7-PERSEUS. Two endurance lines are operated: MooseT00 (Nice-Calvi; Ligurian Sea) and MooseT02 (Marseille-Menorca; Gulf of Lion). The all dataset here corresponds to raw data in the EGO format.

This delayed mode product designed for reanalysis purposes integrates the best available version of in situ data for ocean surface currents and current vertical profiles. It concerns three delayed time datasets dedicated to near-surface currents measurements coming from three platforms (Lagrangian surface drifters, High Frequency radars and Argo floats) and velocity profiles within the water column coming from the Acoustic Doppler Current Profiler (ADCP, vessel mounted only). The latest version of Copernicus surface and sub-surface water velocity product is also distributed from Copernicus Marine catalogue.

A quantitative understanding of the integrated ocean heat content depends on our ability to determine how heat is distributed in the ocean and what are the associated coherent patterns. This dataset contains the results of the Maze et al., 2017 (Prog. Oce.) study demonstrating how this can be achieved using unsupervised classification of Argo temperature profiles. The dataset contains: - A netcdf file with classification~results (labels and probabilities) and coordinates (lat/lon/time) of 100,684 Argo temperature profiles in North Atlantic. - A netcdf file with a Profile Classification Model (PCM) that can be used to classify new temperature profiles from observations or numerical models. The classification method used is a Gaussian Mixture Model that decomposes the Probability Density Function of the dataset into a weighted sum of Gaussian modes. North Atlantic Argo temperature profiles between 0 and 1400m depth were interpolated onto a regular 5m grid, then compressed using Principal Component Analysis and finally classified using a Gaussian Mixture Model. To use the netcdf PCM file to classify new data, you can checkout our PCM Matlab and Python toolbox here: https://github.com/obidam/pcm

This product contains observations and gridded files from two up-to-date carbon and biogeochemistry community data products: Surface Ocean Carbon ATlas SOCATv2023 and GLobal Ocean Data Analysis Project GLODAPv2.2023. The SOCATv2023-OBS dataset contains >25 million observations of fugacity of CO2 of the surface global ocean from 1957 to early 2023. The quality control procedures are described in Bakker et al. (2016). These observations form the basis of the gridded products included in SOCATv2023-GRIDDED: monthly, yearly and decadal averages of fCO2 over a 1x1 degree grid over the global ocean, and a 0.25x0.25 degree, monthly average for the coastal ocean. GLODAPv2.2023-OBS contains >1 million observations from individual seawater samples of temperature, salinity, oxygen, nutrients, dissolved inorganic carbon, total alkalinity and pH from 1972 to 2021. These data were subjected to an extensive quality control and bias correction described in Olsen et al. (2020). GLODAPv2-GRIDDED contains global climatologies for temperature, salinity, oxygen, nitrate, phosphate, silicate, dissolved inorganic carbon, total alkalinity and pH over a 1x1 degree horizontal grid and 33 standard depths using the observations from the previous major iteration of GLODAP, GLODAPv2. SOCAT and GLODAP are based on community, largely volunteer efforts, and the data providers will appreciate that those who use the data cite the corresponding articles (see References below) in order to support future sustainability of the data products.

Observations of Sea surface temperature and salinity are now obtained from voluntary sailing ships using medium or small size sensors. They complement the networks installed on research vessels or commercial ships. The delayed mode dataset proposed here is upgraded annually as a contribution to GOSUD (http://www.gosud.org )

This data set provides a monthly time series of the upper limb of the Meridional Overturning Circulation (MOC) intensity at the A25 Greenland-Portugal OVIDE line from 1993 to 2015. The MOC was derived by combining AVISO altimetry with ISAS temperature and salinity data. The reader is referred to Mercier et al. (2015, Progress in Oceanography) for a full description of the method.