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'''DEFINITION''' The temporal evolution of thermosteric sea level in an ocean layer (here: 0-700m) is obtained from an integration of temperature driven ocean density variations, which are subtracted from a reference climatology (here 1993-2014) to obtain the fluctuations from an average field. The regional thermosteric sea level values from 1993 to close to real time 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''' The global mean sea level is reflecting changes in the Earth’s climate system in response to natural and anthropogenic forcing factors such as ocean warming, land ice mass loss and changes in water storage in continental river basins (IPCC, 2019). Thermosteric sea-level variations result from temperature related density changes in sea water associated with volume expansion and contraction (Storto et al., 2018). Global thermosteric sea level rise caused by ocean warming is known as one of the major drivers of contemporary global mean sea level rise (WCRP, 2018). '''CMEMS KEY FINDINGS''' Since the year 1993 the upper (0-700m) near-global (60°S-60°N) thermosteric sea level rises at a rate of 1.5±0.1 mm/year.
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Moving 6-year analysis and visualization of Water body silicate in the North Sea. Four seasons (December-February, March-May, June-August, September-November). Data Sources: observational data from SeaDataNet/EMODnet Chemistry Data Network. Description of DIVA analysis: Geostatistical data analysis by DIVAnd (Data-Interpolating Variational Analysis) tool, version 2.7.12. results were subjected to the minfield option in DIVAnd to avoid negative/underestimated values in the interpolated results; error threshold masks L1 (0.3) and L2 (0.5) are included as well as the unmasked field. The depth dimension allows visualizing the gridded field at various depths.
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'''DEFINITION''' Ocean heat content (OHC) is defined here as the deviation from a reference period (1993-2014) and is closely proportional to the average temperature change from z1 = 0 m to z2 = 700 m depth: OHC=∫_(z_1)^(z_2)ρ_0 c_p (T_yr-T_clim )dz [1] with a reference density of = 1030 kgm-3 and a specific heat capacity of cp = 3980 J kg-1 °C-1 (e.g. von Schuckmann et al., 2009). Time series of annual mean values area averaged ocean heat content is provided for the Mediterranean Sea (30°N, 46°N; 6°W, 36°E) and is evaluated for topography deeper than 300m. '''CONTEXT''' Knowing how much and where heat energy is stored and released in the ocean is essential for understanding the contemporary Earth system state, variability and change, as the oceans shape our perspectives for the future. The quality evaluation of MEDSEA_OMI_OHC_area_averaged_anomalies is based on the “multi-product” approach as introduced in the second issue of the Ocean State Report (von Schuckmann et al., 2018), and following the MyOcean’s experience (Masina et al., 2017). Six global products and a regional (Mediterranean Sea) product have been used to build an ensemble mean, and its associated ensemble spread. The reference products are: • The Mediterranean Sea Reanalysis at 1/24 degree horizontal resolution (MEDSEA_MULTIYEAR_PHY_006_004, DOI: https://doi.org/10.25423/CMCC/MEDSEA_MULTIYEAR_PHY_006_004_E3R1, Escudier et al., 2020) • Four global reanalyses at 1/4 degree horizontal resolution (GLOBAL_MULTIYEAR_PHY_ENS_001_031): GLORYS, C-GLORS, ORAS5, FOAM • Two observation based products: CORA (INSITU_GLO_PHY_TS_OA_MY_013_052) and ARMOR3D (MULTIOBS_GLO_PHY_TSUV_3D_MYNRT_015_012). Details on the products are delivered in the PUM and QUID of this OMI. '''CMEMS KEY FINDINGS''' The ensemble mean ocean heat content anomaly time series over the Mediterranean Sea shows a continuous increase in the period 1993-2022 at rate of 1.38±0.08 W/m2 in the upper 700m. After 2005 the rate has clearly increased with respect the previous decade, in agreement with Iona et al. (2018). '''DOI (product):''' https://doi.org/10.48670/moi-00261
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IREMARE (Marine Renewable Energie Resource Information) is a project funded by ADEME (Agency for the Environment and Energy Control, French Public Institution), convention n°1505C0027. It is dedicated to the production and dissemination of high level information about Marine Renewable Energy (MRE) resource. The information produced during IREMARE project covers the western coast of France (Atlantic, English Channel and North Sea) and can be used for national down to local scale studies. IREMARE-MED (Informations sur la Ressource pour les Energies MArines REnouvelables en MEDiterranée/Marine Renewable Energie Resource Information in the Mediterranean) is a project funded by ADEME (Agence de l'Environnement et de la Maitrise de l'Energie/Agency for the Environment and Energy Control, French Public Institution), convention n°1705C0016. It is dedicated to the production and dissemination of high level information about Marine Renewable Energy (MRE) resource. The data comes from the HOMERE database (Boudiere et al. 2013) for the zone Atlantic, Channel and North Sea and from the ANEMOC-2 dataset (Tiberi-Wadier et al. 2016) for the Mediterranean Sea.
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Auteur(s): Sanderre Alain, Desmoulins Christian , Projet thérapeutique étudié en fonction de l'architecture
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The raster dataset represents the risk of collision of whales with vessels in Europe Seas. The most vulnerable species from ship strikes are cetaceans and turtles, since they go to the surface to breathe. On the other hand, their migration routes can overlap with shipping lanes. The collisions can produce the death or injury of the animals, and are an important threat for the conservation of these species. The dataset has been prepared in the context of the development of the first European Maritime Transport Environmental Report (EMSA-EEA report, 2021: https://www.eea.europa.eu/publications/maritime-transport).
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This dataset contains the pictures used for morphometric measurements, as well as the elemental compositon and production rates data, of planktonic Rhizaria. Specimens were collected in the bay of Villefranche-sur-Mer in May 2019 and during the P2107 cruise in the California Current in July-August 2021. Analyses of the data can be found at https://github.com/MnnLgt/Elemental_composition_Rhizaria.
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This map presents all layers corresponding to "Repair and maintenance of ships and boats" activities in the Atlantic area. For more information about this NACE code : https://ec.europa.eu/eurostat/ramon/nomenclatures/index.cfm?TargetUrl=DSP_NOM_DTL_VIEW&StrNom=NACE_REV2&StrLanguageCode=EN&IntPcKey=18496334&IntKey=18506474&StrLayoutCode=HIERARCHIC&IntCurrentPage=1 Indicators collected are : Business indicators per country Number of persons employed and number of employees in full time equivalent units per NUTS 3 unit of the Atlantic Area
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'''Short description:''' The NWSHELF_ANALYSISFORECAST_BGC_004_002 is produced by a coupled hydrodynamic-biogeochemical model, implemented over the North East Atlantic and Shelf Seas at about 7 km of horizontal resolution and 24 vertical levels. The product is daily, providing 7-day forecast of the main biogeochemical variables. Products are provided as daily and monthly means. '''DOI (product) :''' https://doi.org/10.48670/moi-00056
Catalogue PIGMA