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 Southern Ocean plays a fundamental role in regulating the global climate. This ocean also contains a rich and highly productive ecosystem, potentially vulnerable to climate change. Very large national and international efforts are directed towards the modeling of physical oceanographic processes to predict the response of the Southern Ocean to global climate change and the role played by the large-scale ocean climate processes. However, these modeling efforts are greatly limited by the lack of in situ measurements, especially at high latitudes and during winter months. The standard data that are needed to study ocean circulation are vertical profiles of temperature and salinity, from which we can deduce the density of seawater. These are collected with CTD (Conductivity-Temperature-Depth) sensors that are usually deployed on research vessels or, more recently, on autonomous Argo profilers. The use of conventional research vessels to collect these data is very expensive, and does not guarantee access to areas where sea ice is found at the surface of the ocean during the winter months. A recent alternative is the use of autonomous Argo floats. However, this technology is not easy to use in glaciated areas. In this context, the collection of hydrographic profiles from CTDs mounted on marine mammals is very advantageous. The choice of species, gender or age can be done to selectively obtain data in particularly under-sampled areas such as under the sea ice or on continental shelves. Among marine mammals, elephant seals are particularly interesting. Indeed, they have the particularity to continuously dive to great depths (590 ± 200 m, with maxima around 2000 m) for long durations (average length of a dive 25 ± 15 min, maximum 80 min). A Conductivity-Temperature-Depth Satellite Relay Data Logger (CTD-SRDLs) has been developed in the early 2000s to sample temperature and salinity vertical profiles during marine mammal dives (Boehme et al. 2009, Fedak 2013). The CTD-SRDL is attached to the seal on land, then it records hydrographic profiles during its foraging trips, sending the data by satellite ARGOS whenever the seal goes back to the surface.While the principle intent of seal instrumentation was to improve understanding of seal foraging strategies (Biuw et al., 2007), it has also provided as a by-product a viable and cost-effective method of sampling hydrographic properties in many regions of the Southern Ocean (Charrassin et al., 2008; Roquet et al., 2013).

This dataset comprises two netcdf files. The first file contains the six global two-dimensional maps necessary to implement the tidal mixing parameterization presented in de Lavergne et al. (2020). Four power fields (E_wwi, E_sho, E_cri and E_hil) represent depth-integrated internal tide energy dissipation, with units of Watts per square meter. Each power field corresponds to a specific dissipative process and associated vertical structure of turbulence production. The two remaining fields, H_cri and H_bot, are decay heights (with units of meters) that enter the vertical structures of the E_cri and E_hil components, respectively. The second file contains three-dimensional fields of turbulence production (with units of Watts per kilogram) obtained by application of the parameterization to the WOCE global hydrographic climatology. The file includes the total turbulence production (epsilon_tid), its four components (epsilon_wwi, epsilon_sho, epsilon_cri, epsilon_hil), and the underlying hydrographic fields, as a function of longitude, latitude and depth. All maps have a horizontal resolution of 0.5º. Detailed documentation of the parameterization can be found in the following publication: de Lavergne, C., Vic, C., Madec, G., Roquet, F., Waterhouse, A.F., Whalen, C.B., Cuypers, Y., Bouruet-Aubertot, P., Ferron, B., Hibiya, T. A parameterization of local and remote tidal mixing. Journal of Advances in Modeling Earth Systems, 12, e2020MS002065 (2020). https://doi.org/10.1029/2020MS002065

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

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 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.

10 years of L-Band remote sensing Sea Surface Salinity (SSS) measurements have proven the capability of satellite SSS to resolve large scale to mesoscale SSS features in tropical to subtropical ocean. In mid to high latitude, L-Band measurements still suffer from large scale and time varying biases. Here, a simple method is proposed to mitigate the large scale and time varying biases. First, in order to estimate these biases, an Optimal Interpolation (OI) using a large correlation scale is used to map SMOS and SMAP L3 products and is compared to equivalent mapping of in situ observations. Then, a second mapping is performed on corrected SSS at scale of SMOS/SMAP resolution (~45 km). This procedure allows to correct and merge both products, and to increase signal to noise ratio of the absolute SSS estimates. Using thermodynamic equation of state (TEOS-10), the resulting L4 SSS product is combined with microwave satellite SST products to produce sea surface density and spiciness, useful to fully characterize the surface ocean water masses. The new L4 SSS products is validated against independent in situ measurements from low to high latitudes. The L4 products exhibits a significant improvement in mid-and high latitude in comparison to the existing SMOS and SMAP L3 products. However, in the Arctic Ocean, L-Band SSS retrieval issues such as sea ice contamination and low sensitivity in cold water are still challenging to improve L-Band SSS data.

C-RAID project is a global reprocessing of drifting buoys data and metadata. The C-RAID dataset contains the metadata of 20 000 drifting buoys, deployed between 1979 and 2018. The data of 16 965 drifting buoys have been fully reprocessed and scientifically checked (delayed mode including comparison with ERA5 reanalysis). Context: The WMO DBCP Drifting Buoys GDAC (Ifremer, Meteo-France and Ocean-Canada ) is dedicated to improved quality control and delivery of drifting buoy of “climate quality”  data for the Marine Climate Data System (MCDS). Goal: clean-up an entire data archive for the past buoys deployed & reprocess the argos data & improve argos position quality (reprocessed with Kalman filter) Lead: The C-RAID project is funded by Copernicus through a contract with the European Environment Agency. Contract # EEA/IDM/15/026/LOT1 (For Services supporting the European Environment Agency’s (EEA) implementation of cross-cutting activities for coordination of the in-situ component of the Copernicus Programme Services). Stakeholders: DB-GDAC, Météo-France, EUMETNET (with its E-SURFMAR program), but also builds on NOAA AOML and JCOMMOPS expertise Challenge: reprocess/recover 22,000 years of data and make them accessible For whom? Copernicus Climate Change Service, Copernicus Marine Environment Monitoring Service, iQuam, ICOADS, GHRSST, ISPD, and ICDC. C-RAID deliverables - An improved drifting buoy data record for years 1979-2018 - FAIR interfaces to drifting buoys data in Ifremer GDAC: Web data discovery for human users API data discovery/subsetting/download services (machine-to-machine data access) What do we mean by “Improved drifting buoy data record”: - Missing datasets and parts of datasets recovered (data rescue) - Homogeneous and rich metadata and data format - Improved Argos locations with Kalman filter algorithm - Homogeneous QC and assessment on marine and atmospheric data

Argo is a global array of 3,000 free-drifting profiling floats that measures the temperature and salinity of the upper 2000 m of the ocean. This allows, for the first time, continuous monitoring of the temperature, salinity, and velocity of the upper ocean, with all data being relayed and made publicly available within hours after collection. The array provides 100,000 temperature/salinity profiles and velocity measurements per year distributed over the global oceans at an average of 3-degree spacing. Some floats provide additional bio-geo parameters such as oxygen or chlorophyll. All data collected by Argo floats are publically available in near real-time via the Global Data Assembly Centers (GDACs) in Brest (France) and Monterey (California) after an automated quality control (QC), and in scientifically quality controlled form, delayed mode data, via the GDACs within six months of collection. The BGC-Argo Sprof snapshot is a subset of the global Argo data snapshot.  It is created to ease BGC-Argo data usage.  The content is the same if you are to download the global Argo data snapshot, and then select all the BGC-Argo Sprof files.  Please use the same DOI and citation as the global Argo data snapshot.