The European Union’s Copernicus-funded TRUSTED project (Towards Fiducial Reference Measurements of Sea-Surface Temperature by European Drifters) has deployed over 100 state of the art drifting buoys for improved validation of Sea Surface Temperature (SST) from the Sentinel-3 Sea and Land Surface Temperature Radiometers (SLSTR). These buoys are manufactured by NKE. The TRUSTED drifting buoys data and metadata are distributed in qualtity control NetCDF files, as a subset of DBCP drifting buoys GDAC (Global Data Assembly Centre). Coriolis DAC  (Data Assembly Centre) routinely collects, decodes, quality controls, preserves and distributes data and metadata as NetCDF-CF files. The TRUSTED buoys have specific features managed by Coriolis DAC python data processing chain: a high resolution temperature sensor in addition to the classic drifting buoy temperature sensor. The high sampling and high resolution observations are distributed in specific variables TEMP_HR, TEMP_HR_SPOT, TEMP_HR_XX (XX is the percentile sample).  

The acoustic tomography approach provides an indirect measure of the temperature of an ocean volume. The technique provides an integrated measure of temperature along the sound propagation paths. The variety of paths between a transmitter and a receiver, as well as the large number of instruments deliver information on the variability of the thermal content of the insonified volume.

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 )

French Zostera Marina et Zostera Noltei abundance data are collected during monitoring surveys on the English Channel / Bay of Biscay coasts. Protocols are impletmented in the Water Framework Directive. Data are transmitted in a Seadatanet format (CDI + ODV) to EMODnet Biology european database. 35 ODV files have been generated from period 01/01/2004 to 31/12/2021 for Z. Marina and from 01/01/2011 to 31/12/2021 for Z. Noltei.  

The network was initiated by IFREMER from 1993 to 2009 (under the acronym REMORA) to study the rearing performance of the Pacific oyster Crassostrea gigas at a national scale. To do so, the network monitored annually the mortality and growth of standardized batches of 18-month-old oysters. Starting in 1995, the monitoring of the rearing performance of 6-month-old oyster spat was integrated into this network. These sentinel batches were distributed simultaneously each year on 43 sites and were monitored quarterly. These sites were distributed over the main French oyster farming areas and allowed a national coverage of the multiannual evolution of oyster farming performances. Most of the sites were located on the foreshore at comparable levels of immersion. Field studies were carried out by the "Laboratoires Environnement Ressources" (LER) for the sites included in their geographical area of investigation. Following the increase in spat mortality in 2008, the network evolved in 2009 (under the acronym RESCO). From this date, the network selected 13 sites among the 43 sites previously monitored in order to increase the frequency of visits (twice a month) and the number of sentinel batches. More precisely, sentinel batches of oysters corresponding to different origins (wild or hatchery, diploid or triploid) and to two rearing age classes (spat or 18-month-old adults) were selected. The monitoring of environmental variables (temperature, salinity) associated with the 13 sites was also implemented. The actions of the network have thus contributed to disentangle the biotic and abiotic parameters involved in mortality phenomena, taking into account the different compartments (environment / host / infectious agents) likely to interact with the evolution of oyster rearing performance. Finally, since 2015, the network has merged the RESCO and VELYGER networks to adopt the acronym ECOSCOPA. The general objective of this current network is to analyze the causes of spatio-temporal variability of the main life traits (Larval stage - Recruitment - Reproduction - Growth - Survival - Cytogenetic abnormalities) of the cupped oyster in France and to follow their evolution on the long term in the context of climate change. To do this, the network proposes a regular spatio-temporal monitoring of the major proxies of the life cycle of the oyster, organized in three major thematic groups: (1) proxies related to growth, physiological tolerance and survival of experimental sentinel populations over 3 age classes: (2) proxies related to reproduction, larval phase and recruitment of the species throughout its natural range in France, and: (3) proxies related to environmental parameters essential to the species (weather conditions, temperature, salinity, pH, turbidity, chlorophyll a and phytoplankton) at daily or sub-hourly frequencies. Working in a geographical network associating several laboratories, ECOSCOPA provide these monitoring within 8 sites selected among the previous ones to ensure the continuity of the data acquisition. Today, these 8 sites are considered as ecosystems of common interest, contrasted, namely : - The Thau lagoon - The Arcachon basin - The Marennes Oléron basin - The Bourgneuf Bay - The bay of Vilaine - The bay of Brest - The bay of Mont Saint Michel - The bay of Veys The ECOSCOPA network is therefore one of the relevant monitoring tools on a national scale, allowing to objectively measure through different proxies the general state of health of cultivated and wild oyster populations, and this for the different sensitive phases of their life cycle. This network aims at allowing a better evaluation, on the long term, of the biological risks incurred by the sector but also by the ecosystems, in particular under the increasing constraint of climatic and anthropic changes. Figure : Sites monitored by the ECOSCOPA network  

Inorganic carbon and alkalinity measurements (in micromoles/kg) from Brazilian cruises in the Western Tropical Atlantic.

Survival was recorded at the endpoint for all batches of each group (2n-control, 2n-wild, 2n-commercial, 2nR, 3nR and 3n-commercial). Similarly, initial and final yield were recorded, corresponding to the total weight of the live oysters at deployment and at the endpoint. Finally, shell length and total weight for individually recorded at reception and at the endpoint.

LOCEAN has been in charge of collecting sea water for the analysis of water isotopes on a series of cruises or ships of opportunity mostly in the equatorial Atlantic, in the North Atlantic, in the southern Indian Ocean, in the southern Seas, Nordic Seas, and in the Arctic. The LOCEAN data set of the oxygen and hydrogen isotope (δ18O and δD) of marine water covers the period 1998 to 2019, but the effort is ongoing. Most data prior to 2010 (only δ18O) were analyzed using isotope ratio mass spectrometry (Isoprime IRMS) coupled with a Multiprep system (dual inlet method), whereas most data since 2010 (and a few earlier data) were obtained by cavity ring down spectrometry (CRDS) on a Picarro CRDS L2130-I, or less commonly on a Picarro CRDS L2120-I. Occasionally, some data were also run by Marion Benetti on an Isoprime IRMS coupled to a GasBench (dual inlet method) at the university of Iceland (Reykjavik). On the LOCEAN Picarro CRDS, most samples were initially analyzed after distillation, but since 2016, they have often been analyzed using a wire mesh to limit the spreading of sea salt in the vaporizer. Some of the samples on the CRDS were analyzed more than once on different days, when repeatability for the same sample was not sufficient or the daily run presented a too large drift. Accuracy is best when samples are distilled, and for δD are better on the Picarro CRDS L2130-I than on the Picarro CRDS L2120-I. Usually, we found that the reproducibility of the δ18O measurements is within ± 0.05 ‰ and of the δD measurements within ± 0.30 ‰, which should be considered an upper estimate of the error on the measurement on a Picarro CRDS. The water samples were kept in darkened glass bottles (20 to 50 ml) with special caps, and were often (but not always) taped afterwards. Once brought back in Paris, the samples were often stored in a cold room (with temperature close to 4°C), in particular if they were not analyzed within the next three months. There is however the possibility that some samples have breathed during storage. We found it happening on a number of samples, more commonly when they were stored for more than 5 years before being analyzed. We also used during one cruise bottles with not well-sealed caps (M/V Nuka Arctica in April 2019), which were analyzed within 3 months, but for which close to one third of the samples had breathed. We have retained those analyses, but added a flag ‘3’ meaning probably bad, at least on d-excess (outside of regions where sea ice forms or melts, for the analyses done on the Picarro CRDS, excessive evaporation is usually found with a d-excess criterium (which tends to be too low); for the IRMS analyses, it is mostly based when excessive scatter is found in the S- δ18O scatter plots or between successive data, in which case some outliers were flagged at ‘3’). In some cases when breathing happened, we found that d-excess can be used to produce a corrected estimate of δ18O and δD (Benetti et al., 2016). When this method was used a flag ‘1’ is added, indicating ‘probably good’ data, and should be thought as not as accurate as the data with no ‘correction’, which are flagged ‘2’ or ‘0’. We have adjusted data to be on an absolute fresh-water scale based on the study of Benetti et al. (2017), and on further tests with the different wire meshes used more recently. We have also checked the consistency of the runs in time, as there could have been changes in the internal standards used. On the Isoprime IRMS, it was mostly done using different batches of ‘Eau de Paris’ (EDP), whereas on the Picarro CRDS, we used three internal standards kept in metal tanks with a slight overpressure of dry air). The internal standards have been calibrated using VSMOW and GISP, and were also sent to other laboratories to evaluate whether they had drifted since the date of creation (as individual sub-standards have typically stored for more than 5-years). These comparisons are still not fully statisfactory to evaluate possible drifts in the sub-standards. Individual files correspond to regional subsets of the whole dataset. The file names are based on two letters for the region (see below) followed by –Wisotopes and a version number (-V0, …): example SO-Wisotopes-V0; the highest version number corresponds to the latest update of the regional data set. The region two letters are the followings: - SO: Southern Ocean including cruise station and surface data mostly from 2017 in the Weddell Sea (WAPITI Cruise JR160004, DOI:10.17882/54012), as well as in the southern Ocean south of 20°S - SI: OISO cruise station and surface data in the southern Indian Ocean (since 1998) (DOI:10.18142/228) - EA: 20°N-20°S cruise station and surface data (since 2005), in particular in the equatorial Atlantic from French PIRATA (DOI:10.18142/14) and EGEE cruises (DOI:10.18142/95) - NA: 20°N-72°N station and surface data, mostly in the North Atlantic from Oceanographic cruises as well as from ships of opportunity (this includes in particular OVIDE cruise data since 2002 (DOI:10.17882/46448),  CATARINA, BOCATS1 and BOCATS2 (PID2019-104279GB-C21/AEI/10.13039/501100011033) cruises funded by the Spanish Research Agency, RREX2017 2017 cruise data (DOI:10.17600/17001400), SURATLANT data set since 2011 (DOI:10.17882/54517), Nuka Arctica and Tukuma Arctica data since 2012, STRASSE (DOI:10.17600/12040060) and MIDAS cruise data in 2012-2013, as well as surface data from various ships of opportunity since 2012) - NS: Nordic Sea data from cruises in 2002-2018 - AS: Arctic Ocean north of 72°N, in particular from two Tara cruises (in 2006-2008 and 2013) and expeditions since 2020 - PM: miscellaneous data in tropical Pacific, Indian Ocean, Mediterranean Sea and Black Sea In some regions, such as in the Indian Ocean, it is valuable to combine different subsets to have the full data distribution. The files are in csv format reported, and starting with version V1, it is reported as: - Cruise name, station id, bottle number, day, month, year, hour, minute, latitude, longitude, pressure (db), temperature (°C), it, salinity (pss-78), is, dissolved oxygen (micromol/kg), io2, δ18O, iO, d D, iD, d-excess, id, method type - Temperature is an in situ temperature - Salinity is a practical salinity it, is, io2, iO, iD, id are quality indices equal to: - 0 no quality check (but presumably good data) - 1 probably good data - 2 good data - 3 probably bad data - 4 certainly bad data - 9 missing data (and the missing data are reported with an unlikely missing value) The method type is 1 for IRMS measurements, 2 for CRDS measurement of a saline water sample, 3 for CRDS measurement of a distilled water sample.

The data file present detailed individual congener/compound concentrations  for a large variety of hydrophobic organic contaminants including polychlorinated biphenyls (PCBs), organochlorine pesticides (OCPs), legacy and alternative brominated flame retardants (BFRs) and per- and polyfluoroalkyl substances (PFASs) in meso- and bathypelagic organisms collected in the Bay of Biscay, northeast Atlantic, in October 2017. The studied species include 3 crustacean species (Pasiphaea sivado, Sergia robusta, Ephyrina figueirai) and 11 fish species (Xenodermichthys copei, Searsia koefoedi, Myctophum punctatum, Notoscopelus kroeyeri, Lampanyctus crocodilus, Argyropelecus olfersii, Arctozenus risso, Stomias boa, Serrivomer beanii, Chauliodus sloani, Aphanopus carbo). The organisms were collected at night during one single trawling using a 25 m vertical opening pelagic trawl in the deep scattering layer (ca 800 m depth in the water column; 1330 m bottom floor). This dataset was used in the article entitled "A large diversity of organohalogen contaminants reach the meso- and bathypelagic organisms in the Bay of Biscay (northeast Atlantic)" published in Marine Pollution Bulletin.

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.