This product displays for Nickel, positions with values counts that have been measured per matrix and are present in EMODnet regional contaminants aggregated datasets, v2022. The product displays positions for all available years.

This product displays for Mercury, positions with percentages of all available data values per group of animals that are present in EMODnet regional contaminants aggregated datasets, v2024. The product displays positions for all available years.

Wave forecasting models allow the representation of sea states based on a spectral resolution at the global scale or at the scale of ocean basins. This code calculates the evolution of the sea state by decomposing it into a wave spectrum that propagates in different directions and with different periods. During the propagation, the wave energy is increased or decreased by the effects of wind, breaking waves and energy exchanges between the different components. The wave forecasts available on data.shom.fr are calculated with 2 different types of models: MFWAM for the offshore domain (resolution from 0.5° to 0.1°) and Wavewatch III ® (WW3) for the coastal domain (resolution from 2' to 200m). MFWAM is a sea state forecasting model (wind wave and swell) derived from the third generation WAM code (WAMDI Group, 1988). Wavewatch III ® (WW3) is developed in a collaboration between the United States Weather Service (NOAA/NCEP), Shom, the University of Darmstadt in Germany, and other partners. The forecasts published on data.shom.fr are issued from the parameterization carried out and optimized by the Shom and Météo-France within the framework of the Homonim project (national coastal flood/wave/storm warning system).

This product displays for Nickel, positions with values counts that have been measured per matrix for each year and are present in EMODnet regional contaminants aggregated datasets, v2024. The product displays positions for every available year.

Moving 10-years analysis of phosphates at Mediterranean Sea for each season : - winter (January-March), - spring (April-June), - summer (July-September), - autumn (October-December). Every year of the time dimension corresponds to the 10-year centered average of each season. Decades span from 1960-1969 until 2004-2013. Observational data span from 1960 to 2013. Depth range (IODE standard depths): -1500.0, -1400.0, -1300.0, -1200.0, -1100.0, -1000.0, -900.0, -800.0, -700.0, -600.0, -500.0, -400.0, -300.0, -250.0, -200.0, -150.0, -125.0, -100.0, -75.0, -50.0, -30.0, -20.0, -10.0, -5.0, -0.0. Data Sources: observational data from SeaDataNet/EMODNet Chemistry Data Network. Description of DIVA analysis: Geostatistical data analysis by DIVA (Data-Interpolating Variational Analysis) tool. Profiles were interpolated at standard depths using weighted parabolic interpolation algorithm (Reiniger and Ross, 1968). GEBCO 1min topography is used for the contouring preparation. Analyzed filed masked using relative error threshold 0.3 and 0.5. DIVA settings: A constant value for signal-to-noise ratio was used equal to 3. Correlation length was optimized and filtered vertically and a seasonally-averaged profile was used. Logarithmic transformation applied to the data prior to the analysis. Background field: the data mean value is subtracted from the data. Detrending of data: no. Advection constraint applied: no. Originators of Italian data sets-List of contributors • Brunetti Fabio (OGS) • Cardin Vanessa, Bensi Manuel doi:10.6092/36728450-4296-4e6a-967d-d5b6da55f306 • Cardin Vanessa, Bensi Manuel, Ursella Laura, Siena Giuseppe doi:10.6092/f8e6d18e-f877-4aa5-a983-a03b06ccb987 • Cataletto Bruno (OGS) • Cinzia Comici Cinzia (OGS) • Civitarese Giuseppe (OGS) • DeVittor Cinzia (OGS) • Giani Michele (OGS) • Kovacevic Vedrana (OGS) • Mosetti Renzo (OGS) • Solidoro C.,Beran A.,Cataletto B.,Celussi M.,Cibic T.,Comici C.,Del Negro P.,De Vittor C.,Minocci M.,Monti M.,Fabbro C.,Falconi C.,Franzo A.,Libralato S.,Lipizer M.,Negussanti J.S.,Russel H.,Valli G., doi:10.6092/e5518899-b914-43b0-8139-023718aa63f5 • Celio Massimo (ARPA FVG) • Malaguti Antonella (ENEA) • Fonda Umani Serena (UNITS) • Bignami Francesco (ISAC/CNR) • Boldrini Alfredo (ISMAR/CNR) • Marini Mauro (ISMAR/CNR) • Miserocchi Stefano (ISMAR/CNR) • Zaccone Renata (IAMC/CNR) • Lavezza, R., Dubroca, L. F. C., Ludicone, D., Kress, N., Herut, B., Civitarese, G., Cruzado, A., Lefèvre, D., Souvermezoglou, E., Yilmaz, A., Tugrul, S., and Ribera d’Alcala, M.: Compilation of quality controlled nutrient profiles from the Mediterranean Sea, doi:10.1594/PANGAEA.771907, 2011. Units: umol/l

This product displays for Cadmium, positions with values counts that have been measured per matrix for each year and are present in EMODnet regional contaminants aggregated datasets, v2024. The product displays positions for every available year.

The Shom uses a 2D barotropic version of the HYCOM code (https://hycom.org/) to compute water level /surge forecasts (astronomical tides and meteorological surges) for the Atlantic, Mediterranean, Antilles-Guyane and Indian Ocean domains. The configurations use curvilinear grid with resolutions of several km offshore and ranging from 1.5km to around 500m on the french mainland coasts and the Antilles-Guyana coast. A downscaling by nesting allows a resolution of 800m to 200m over the Indian domain. These models have been adapted by the Shom to be operable in coastal areas by taking into account, in particular, the tide and high resolution bathymetry in these areas (from 100m for DTMs of facade to 20m for coastal DTMs) using Litto3D surveys by airborne LIDAR. The models are operated by Météo-France and the Shom in the framework of the HOMONIM project for the coastal flood/wave warning system.

Understanding the dynamics of species interactions for food (prey-predator, competition for resources) and the functioning of trophic networks (dependence on trophic pathways, food chain flows, etc.) has become a thriving ecological research field in recent decades. This empirical knowledge is then used to develop population and ecosystem modelling approaches to support ecosystem-based management. The TrophicCS data set offers spatialized trophic information on a large spatial scale (the entire Celtic Sea continental shelf and upper slope) for a wide range of species. It combines ingested prey (gut content analysis) and a more integrated indicator of food sources (stable isotope analysis). A total of 1337 samples of large epifaunal invertebrates (bivalve mollusks and decapod crustaceans), zooplankton, fish and cephalopods, corresponding to 114 species, were collected and analyzed for stable isotope analysis of their carbon and nitrogen content. Sample size varied between taxa (from 1 to 52), with an average of 11.72 individuals sampled per species, and water depths ranged from 57 to 516 m. The gut contents of 1026 fish belonging to ten commercially important species: black anglerfish (Lophius budegassa), white anglerfish (Lophius piscatorius), blue whiting (Micromesistius poutassou), cod (Gadus morhua), haddock (Melanogrammus aeglefinus), hake (Merluccius merluccius), megrim (Lepidorhombus whiffiagonis), plaice (Pleuronectes platessa), sole (Solea solea) and whiting (Merlangius merlangus) were analyzed. The stomach content data set contains the occurrence of prey in stomach, identified to the lowest taxonomic level possible. To consider potential ontogenetic diet changes, a large size range was sampled. The TrophicCS data set was used to improve understanding of trophic relationships and ecosystem functioning in the Celtic Sea. When you use the data in your publication, we request that you cite this data paper. If you use the present data set (TrophicCS) for the majority of the data analyzed in your study, you may wish to consider inviting at least one author of the core team of this data paper to become a collaborator /coauthor of your paper.