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oceans

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  • SeaDataNet Temperature and Salinity historical data collection contains all open access temperature and salinity in situ data retrieved from SeaDataNet infrastructure at the end of 2013. The data span between -9.25 and 37 degrees of longitude, thus including an Atlantic box and Marmara Sea, and cover the time period 1900-2012. Data have been quality checked using ODV software. Quality Flags of anomalous data have been revised using basic QC procedures. For data access please register at http://www.marine-id.org The dataset format is ODV binary collections. You can read, analyse and export from the ODV application provided by Alfred Wegener institute at http://odv.awi.de/

  • This product displays for Fluoranthene, positions with values counts that have been measured per matrix and are present in EMODnet regional contaminants aggregated datasets, v2024. The product displays positions for all available years.

  • The coastal heights data combines two datasets: the land-sea mask of the gridded EMODnet bathymetry and the height of high-water (HAT) relative to chart datum (LAT) as computed with the GTSM tide model. Near the coast a diffusion scheme is applied to make the heights consistent with the land-sea mask. Finally, only grid cells that are classified as sea, but neighbor a land cell are selected. The main assumption in this approach is that the height of the topography near the coastline is close to the high-water mark. The main purpose of this dataset is to improve extrapolation towards the coast. In many areas around Europe there is a (small) gap between the point closest to the coast for which a survey is available and the coastline. In this way interpolation from coarser background data is avoided.

  • This dataset provides detections of fronts derived from high resolution remote sensing SST observations by SEVIRI L3C from OSISAF over Western Europe region. The data are available through HTTP and FTP; access to the data is free and open. In order to be informed about changes and to help us keep track of data usage, we encourage users to register at: https://forms.ifremer.fr/lops-siam/access-to-esa-world-ocean-circulation-project-data/ This dataset was generated by OceanDataLab and is distributed by Ifremer / CERSAT in the frame of the World Ocean Circulation (WOC) project funded by the European Space Agency (ESA).

  • '''DEFINITION''' The temporal evolution of thermosteric sea level in an ocean layer is obtained from an integration of temperature driven ocean density variations, which are subtracted from a reference climatology to obtain the fluctuations from an average field. The products used include three global reanalyses: GLORYS, C-GLORS, ORAS5 (GLOBAL_MULTIYEAR_PHY_ENS_001_031) and two in situ based reprocessed products: CORA5.2 (INSITU_GLO_PHY_TS_OA_MY_013_052) , ARMOR-3D (MULTIOBS_GLO_PHY_TSUV_3D_MYNRT_015_012). The regional thermosteric sea level values are then averaged from 60°S-60°N aiming to monitor interannual to long term global sea level variations caused by temperature driven ocean volume changes through thermal expansion as expressed in meters (m). '''CONTEXT''' Most of the interannual variability and trends in regional sea level is caused by changes in steric sea level. At mid and low latitudes, the steric sea level signal is essentially due to temperature changes, i.e. the thermosteric effect (Stammer et al., 2013, Meyssignac et al., 2016). Salinity changes play only a local role. Regional trends of thermosteric sea level can be significantly larger compared to their globally averaged versions (Storto et al., 2018). Except for shallow shelf sea and high latitudes (> 60° latitude), regional thermosteric sea level variations are mostly related to ocean circulation changes, in particular in the tropics where the sea level variations and trends are the most intense over the last two decades. '''CMEMS KEY FINDINGS''' Significant (i.e. when the signal exceeds the noise) regional trends for the period 2005-2023 from the Copernicus Marine Service multi-ensemble approach show a thermosteric sea level rise at rates ranging from the global mean average up to more than 8 mm/year. There are specific regions where a negative trend is observed above noise at rates up to about -5 mm/year such as in the subpolar North Atlantic, or the western tropical Pacific. These areas are characterized by strong year-to-year variability (Dubois et al., 2018; Capotondi et al., 2020). Note: The key findings will be updated annually in November, in line with OMI evolutions. '''DOI (product):''' https://doi.org/10.48670/moi-00241

  • Since 2004, the Service facility SNAPO-CO2 (Service National d’Analyse des Paramètres Océaniques du CO2) housed by the LOCEAN laboratory (Paris, France) has been in charge for the analysis of Total Alkalinity (AT) and Total dissolved inorganic carbon (CT) of seawater samples on a series of cruises or ships of opportunity conducted in different regions in the frame of French and International projects. Following the first synthesis (Metzl et al, 2024, https://doi.org/10.17882/95414), 24700 new data have been quality controlled and the second version includes more than 67000 observations over 1993-2023. Sampling was performed either from CTD-Rosette casts (Niskin bottles) or collected from the ship’s seawater supply (intake at about 5m depth). After completion of each cruise, discrete samples were returned back at LOCEAN laboratory and stored in a dark room at 4 °C before analysis generally within 2-3 months after sampling (sometimes within a week). AT and CT were analyzed simultaneously by potentiometric titration using a closed cell (Edmond, 1970). Certified Reference Materials (CRMs) provided by Pr. A. Dickson (Scripps Institution of Oceanography, San Diego, USA) were used to calibrate the measurements. The same instrumentation was used for underway measurements during OISO cruises (https://campagnes.flotteoceanographique.fr/series/228/) and MINERVE cruises (https://doi.org/10.18142/128) and new AT-CT data for 2002-2021 in the Indian Ocean and Southern Ocean added in this synthesis. The second dataset is organized in one file with the format: Cruise name, Ship name, day, month, year, hour, minute, second, latitude, longitude, depth, AT (µmol/kg), Flag-AT, CT (µmol/kg), Flag-CT, Temperature (°C), Flag-Temp, Salinity (PSU), Flag-Salinity, nsample/cruise, sampling method, Version number, nsample on file.