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.

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.

Ensemble simulations of the ecosystem model Apecosm (https://apecosm.org) forced by the IPSL-CM6-LR climate model with the climate change scenario SSP5-8.5. 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 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

The In Situ delayed mode product designed for reanalysis purposes integrates the best available version of in situ data for ocean surface currents. The data are collected from the Surface Drifter Data Assembly Centre (SD-DAC at NOAA AOML). All surface drifters data have been processed to check for drogue loss. Drogued and undrogued drifting buoy surface ocean currents are provided with a drogue presence flag as well as a wind slippage correction for undrogued buoys. Altimeter and wind data have been used to extract the direct wind slippage from the total drifting buoy velocities. This product is designed to be assimilated into or for validation purposes of operational models operated by ocean forecasting centers for reanalysis purposes or for research community. These users need data aggregated and quality controlled in a reliable and documented manner.

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.

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 )

The upper ocean pycnocline (UOP) monthly climatology is based on the ISAS20 ARGO dataset containing Argo and Deep-Argo temperature and salinity profiles on the period 2002-2020. Regardless of the season, the UOP is defined as the shallowest significant stratification peak captured by the method described in Sérazin et al. (2022), whose detection threshold is proportional to the standard deviation of the stratification profile. The three main characteristics of the UOP are provided -- intensity, depth and thickness -- along with hydrographic variables at the upper and lower edges of the pycnocline, the Turner angle and density ratio at the depth of the UOP. A stratification index (SI) that evaluates the amount of buoyancy required to destratify the upper ocean down to a certain depth, is also included. When evaluated at the bottom of the UOP, this gives the upper ocean stratification index (UOSI) as discussed in Sérazin et al. (2022). Three mixed layer depth variables are also included in this dataset, including the one using the classic density threshold of 0.03 kg.m-3, along with the minimum of these MLD variables. Several statistics of the UOP characteristics and the associated quantities are available in 2°×2° bins for each month of the year, whose results were smoothed using a diffusive gaussian filter with a 500 km scale. UOP characteristics are also available for each profile, with all the profiles sorted in one file per month.

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).