This data set contains the gridded hydrographic and transport data for the biennial Go-Ship A25 Greenland–Portugal OVIDE section from 2002 to 2012. The properties and transports are mapped on a 7km x 1m grid. Using a common grid facilitates the comparison between the different occupations of the line and the averaging. This data set was used in Daniault et al. (2016, Progress in Oceanography) to which the reader is referred for a description of the gridding method.

The OceanGliders initiative (formerly EGO) is a gathering of several teams of oceanographers, interested in developing the use of gliders for ocean observations. OceanGliders started in Europe with members from France, Germany, Italy, Norway, Spain, and the United Kingdom. The partners of OceanGliders have been funded by both European and national agencies to operate gliders for various purposes and at different sites. Coordinated actions are being set up for these sites in order to demonstrate the capabilities of a fleet of gliders for sampling the ocean, with a given scientific and/or operational objective. Gliders were developed since the 90’s to carry out in-situ observations of the upper 1km of the ocean, filling the gaps left by the existing observing systems. Gliders look like small autonomous robotic underwater vehicles which that uses an engine to change their buoyancy. While gliding from surface to about 1000 meters, gliders provide real-time physical and biogeochemical data along their transit.  They observe temperature, salinity, pressure, biogeochemical data or acoustic data. The OceanGliders GDAC handled at Ifremer/France aggregates the data and metadata from glider deployments provided by the DACs or PIs. The OceanGliders unique DOI publishes the quaterly snapshot of the whole GDAC content and preserves its successive quaterly versions (unique DOI for easy citability, preservation of quaterly versions for reproducibility).   The OceanGliders unique DOI references all individual glider deployment DOIs provided by the DACs or PIs, and with data in the GDAC. DACs or PIs may use the data processing chain published at http://doi.org/10.17882/45402 to generate glider NetCDF GDAC files.

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

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 Greenland-Portugal A25 OVIDE line is carried out biennially since 2002. The section is composed of 98 stations where hydrographic, biogeochemical and current measurements are carried out down to the bottom. OVIDE is a contribution to the international programs Go-Ship, IOCCP, and CLIVAR. This data set contains the final (adjusted) CTDO2 data. 

Satellite altimetry missions provide a quasi-global synoptic view of sea level over more than 25 years. The satellite altimetry constellation is used to build sea level maps and regional sea level indicators such as trends and accelerations. Estimating realistic uncertainties on these quantities is crucial to address some current climate science questions such as climate change detection and attribution or regional sea level budget closure for example. Previous studies have estimated the uncertainty for the global mean sea level (GMSL), but no uncertainty information is available at regional scales. In this study we estimate a regional satellite altimetry error budget and use it to derive maps of confidence intervals for local sea rise rates and accelerations. We analyze 27 years of satellite altimetry maps and derive the satellite altimetry error variance-covariance matrix at each grid point, prior to the estimation of confidence intervals on local trends and accelerations at the 90% confidence level using extended least squares estimators. Over 1993–2019, we find that the average local sea level trend uncertainty is 0.83 mm.yr-1 with local values ranging from 0.78 to 1.22 mm.yr-1. For accelerations, uncertainties range from 0.057 to 0.12 mm.yr-2, with a mean value of 0.063 mm.yr-2.   Change history: - 2020/07/08: initial dataset submission over 1993-2018 - 2020/10/21: 1993-2019 update and addition of error levels

The observations of campe glider on imedia deployment (Mediterranean Sea - Western basin) are distributed in 4 files: - EGO NetCDF time-series (data, metadata, derived sea water current) - NetCDF profiles extracted from the above time-series - Raw data - JSON metadata used by the decoder The following parameters are provided : - Practical salinity - Sea temperature in-situ ITS-90 scale - Electrical conductivity - Sea water pressure, equals 0 at sea-level

GOSUD aims at assembling in-situ observations of the world ocean surface collected by a variety of ships and at distributing quality controlled datasets.  At present time the variables considered by GOSUD are temperature and salinity. The GOSUD data are mostly collected using thermosalinographs (TSG) installed on research vessels, on commercial ships and in some cases on sailing exploration ships GOSUD manages both near-real time data and delayed mode (reprocessed) data.

Mesoscale eddy detection from 2000 to 2021 are computed using the AMEDA algorithm applied on AVISO L4 absolute dynamic topography at 1/8th degree. Eddy numbers correspond to tracks referenced in the DYNED atlas (https://doi.org/10.14768/2019130201.2). Detection is based on AVISO delyed-time product from 2000 to 2019 and on day+6 near-real-time altimetry from 2020 to 2021. Colocalisation is then made with available in situ profiles from Coriolis Ocean Dataset for Reanalysis (CORA) delayed-time data (113486 profiles) and Copernicus near-real-time profiles (43567).

This dataset contains OAC-P results from application to Argo data in the World Ocean : - the 2000-2015 climatology of OAC-P results mapped onto a 0.5x0.5 grid with mapping error estimates; - the 2000-2015 probability density function of the permanent pycnocline potential density referenced to the sea surface vs Brunt-Väisälä frequency squared.OAC-P is an "Objective Algorithm for the Characterization of the permanent Pycnocline" developed to characterize subtropical gyre stratification features with both observed and modeled potential density profiles. OAC-P estimates the following properties: - for the permanent pycnocline: depth, upper and lower thicknesses, Brunt-Väisälä frequency squared, potential density, temperature and salinity; - for the surface mode water overlying the permanent pycnocline: depth, Brunt-Väisälä frequency squared, potential density, temperature and salinity. Argo data were download from Coriolis Argo GDAC on February, 8th 2016. Only Argo data with QC=1, 2, 5 or 8 were used.