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.

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.  

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 dataset provides a World Ocean Atlas of Argo inferred statistics. The primary data are exclusively Argo profiles. The statistics are done using the whole time range covered by the Argo data, starting in July 1997. The atlas is provided with a 0.25° resolution in the horizontal and 63 depths from 0 m to 2,000 m in the vertical. The statistics include means of Conservative Temperature (CT), Absolute Salinity, compensated density, compressiblity factor and vertical isopycnal displacement (VID); standard deviations of CT, VID and the squared Brunt Vaisala frequency; skewness and kurtosis of VID; and Eddy Available Potential Energy (EAPE). The compensated density is the product of the in-situ density times the compressibility factor. It generalizes the virtual density used in Roullet et al. (2014). The compressibility factor is defined so as to remove the dependency with pressure of the in-situ density. The compensated density is used in the computation of the VID and the EAPE.

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.

These monthly gridded climatology were produced using MBT, XBT, Profiling floats, Gliders, and ship-based CTD data from different database and carried out in the Med. between 1969 and 2013. The Mixed Layer Depth (MLD) is calculated with a delta T= 0.1 C criterion relative to 10m reference level on individual profiles. The Depth of the Bottom of the Seasonal Thermocline (DBST) is calculated on individual profiles as the maximum value from a vector composed of two elements: 1) the depth of the temperature minimum in the upper 200m; 2) the MLD. This double criterion for the calculation of DBST is necessary in areas where the mixed layer exceed 200m depth. DBST is the integration depth used in the calculation of the upper-ocean Heat Storage Rate. For more details about the data and the methods used, see: Houpert et al. 2015, Seasonal cycle of the mixed layer, the seasonal thermocline and the upper-ocean heat storage rate in the Mediterranean Sea derived from observations, Progress in Oceanography, http://doi.org/10.1016/j.pocean.2014.11.004

This dataset is an aggregation of all availale in situ data from Coriolis and Copernicus in situ data centres, observed in the French DCSMM area. It contains 5167 NetCDF CF files from 1903 to 2017. Each file contains the observations of a specific platform (e.g. vessel, mooring site, sea level station). Observed parameters are temperature, salinity, pressure, oxygen, nitrate, chlorophyll (and other bio-geo-chemicals), current, wave, sea level, river flow.  

This dataset is composed by the climatological seasonal field of the Ocean Salinity Stratification as defined from the Brunt-Vaisala frequency limited to the upper 300 m depth. The details are given in Maes, C., and T. J. O’Kane (2014), Seasonal variations of the upper ocean salinity stratification in the Tropics, J. Geophys. Res. Oceans, 119, 1706–1722, doi:10.1002/2013JC009366.

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 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