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 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.

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 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

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

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 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 In Situ delayed mode product integrates the best available version of in situ oxygen, chlorophyll / fluorescence and nutrients data. The latest version of Copernicus delayed-mode BGC (bio-geo-chemical) product is also distributed from Copernicus Marine catalogue.

Ensemble simulations of the ecosystem model Apecosm (https://apecosm.org) forced by the IPSL-CM6-LR climate model with the climate change scenario SSP1-2.6. The output files contain yearly mean biomass density for 3 communities (epipelagic, mesopelagic migratory and mesopelagic redidents) and 100 size classes (ranging from 0.12cm to 1.96m) The model grid file is also provided. Units are in J/m2 and can be converted in kg/m2 by dividing by 4e6. These outputs are associated with the "Assessing the time of emergence of marine ecosystems from global to local scales using IPSL-CM6A-LR/APECOSM climate-to-fish ensemble simulations" paper from the Earth's Future "Past and Future of Marine Ecosystems" Special Collection.

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.