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  • 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.

  • The continuously updated version of Copernicus Argo floats realtime currents product is distributed from Copernicus Marine catalogue: - https://resources.marine.copernicus.eu/?option=com_csw&view=details&product_id=INSITU_GLO_UV_NRT_OBSERVATIONS_013_048 The Argo current product generated by Copernicus in situ TAC is derived from the original trajectory data from Argo GDAC (Global Data Assembly Center) available at: - Argo float data and metadata from Global Data Assembly Centre (Argo GDAC). SEANOE. https://doi.org/10.17882/42182 In 2021, the GDAC distributes data from more than 15,000 Argo floats. Deep ocean current is calculated from floats drift at parking depth, surface current is calculated from float surface drift. An Argo float drifts freely in the global ocean, performing regular observation cycles. An observation cycle usually spreads over 10 days :  - a surface descent to a parking depth (generally 1500 meters deep) - a 10-day drift at this parking depth - an ascent to the surface (vertical profile) - A short surface drift for data transmission The data transmitted at each cycle contain temperature, salinity observations (and additional biogeochemical parameters if applicable), positions (gps or argos), technical data. The ocean current product contains a NetCDF file for each Argo float. It is updated daily in real time by automated processes. For each cycle it contains the surface and deep current variables: - Date (time, time_qc) - Position  (latitude, longitude, position_qc) - Pressure (pres, pres_qc, representative_park_pressure for parking drift, 0 decibar for surface drift) - Current (ewct, ewct_qc, nsct, nsct_qc; the current vector is positioned and dated at the last position of the N-1 cycle) - Duration (days) of the current variable sampling (time_interval) - Grounded indicator - Positions and dates have a QC 1 (good data). Positions and dates that do not have a QC 1 are ignored. The positions are measured during the surface drift (Argos or GPS positioning). For the deep current of cycle N, we take the last good position of cycle N-1 and the first good position of cycle N. For the surface current of cycle N, we take the first and last good position of the N cycle.  

  • 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

  • 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 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.

  • C-RAID: Comprehensive Reprocessing of Drifting Buoy Data (1979-2018) The C-RAID (Copernicus - Reprocessing of Drifting Buoys) project delivers a comprehensive global reprocessing of historical drifting buoy data and metadata, providing climate-quality observations for marine and atmospheric research. Dataset Overview The C-RAID dataset encompasses metadata from 21 858 drifting buoys deployed between 1979 and 2018. Of these, 17 496 buoys have undergone complete reprocessing with scientific validation in delayed mode, including comparison against ERA5 reanalysis. Project Context Managed by the WMO DBCP Drifting Buoys Global Data Assembly Centre (GDAC) through Ifremer, Météo-France, and Ocean Sciences Division of Fisheries and Oceans Canada, C-RAID focuses on enhanced quality control and delivery of climate-quality drifting buoy data for the Marine Climate Data System (MCDS). Objectives - Complete reprocessing and clean-up of the historical drifting buoy data archive - Recovery and rescue of missing datasets - Reprocessing of Argos data with improved positioning using Kalman filter algorithms - Homogenization of quality control procedures across marine and atmospheric parameters Funding & Governance C-RAID was funded by the Copernicus Programme through the European Environment Agency (Contract # EEA/IDM/15/026/LOT1), supporting cross-cutting coordination activities for the in-situ component of Copernicus Services. Stakeholders & Partnerships The project is led by the DB-GDAC consortium (Ifremer, Météo-France) in collaboration with EUMETNET's E-SURFMAR programme, NOAA AOML, and JCOMMOPS. Key Achievements - Reprocessing of approximately 24 000 buoy-years of observations - Recovery of missing datasets and metadata through data rescue efforts - Implementation of homogeneous, rich metadata and data formats - Enhanced Argos location accuracy using Kalman filter reprocessing - Standardized quality control and validation procedures Data Access & FAIR Principles C-RAID provides FAIR (Findable, Accessible, Interoperable, Reusable) data access through: - Web-based data discovery portal for human users - API services for data discovery, subsetting, and download (machine-to-machine access) Target Users The dataset serves major operational and research programmes including: - Copernicus Climate Change Service (C3S) - Copernicus Marine Environment Monitoring Service (CMEMS) - iQuam (in-situ SST Quality Monitor) - ICOADS (International Comprehensive Ocean-Atmosphere Data Set) - GHRSST (Group for High Resolution Sea Surface Temperature) - ISPD (International Surface Pressure Databank) - ICDC (Integrated Climate Data Center)  

  • 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).

  • 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.

  • 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.