This visualization product displays the density of floating micro-litter per net normalized per m³ per year from specific protocols different from research and monitoring protocols. EMODnet Chemistry included the collection of marine litter in its 3rd phase. Before 2021, there was no coordinated effort at the regional or European scale for micro-litter. Given this situation, EMODnet Chemistry proposed to adopt the data gathering and data management approach as generally applied for marine data, i.e., populating metadata and data in the CDI Data Discovery and Access service using dedicated SeaDataNet data transport formats. EMODnet Chemistry is currently the official EU collector of micro-litter data from Marine Strategy Framework Directive (MSFD) National Monitoring activities (descriptor 10). A series of specific standard vocabularies or standard terms related to micro-litter have been added to SeaDataNet NVS (NERC Vocabulary Server) Common Vocabularies to describe the micro-litter. European micro-litter data are collected by the National Oceanographic Data Centres (NODCs). Micro-litter map products are generated from NODCs data after a test of the aggregated collection including data and data format checks and data harmonization. A filter is applied to represent only micro-litter sampled according to a very specific protocol such as the Volvo Ocean Race (VOR) or Oceaneye. Densities were calculated for each net using the following calculation: Density (number of particles per m³) = Micro-litter count / Sampling effort (m³) When the number of micro-litters was not filled, it was not possible to calculate the density. Percentiles 50, 75, 95 & 99 have been calculated taking into account data for all years. Warning: the absence of data on the map does not necessarily mean that they do not exist, but that no information has been entered in the National Oceanographic Data Centre (NODC) for this area.

'''DEFINITION''' Estimates of Ocean Heat Content (OHC) are obtained from integrated differences of the measured temperature and a climatology along a vertical profile in the ocean (von Schuckmann et al., 2018). 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). Additionally, the time series based on the method of von Schuckmann and Le Traon (2011) has been added. The regional OHC values are then averaged from 60°S-60°N aiming i) to obtain the mean OHC as expressed in Joules per meter square (J/m2) to monitor the large-scale variability and change. ii) to monitor the amount of energy in the form of heat stored in the ocean (i.e. the change of OHC in time), expressed in Watt per square meter (W/m2). Ocean heat content is one of the six Global Climate Indicators recommended by the World Meterological Organisation for Sustainable Development Goal 13 implementation (WMO, 2017). '''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 ocean shapes our perspectives for the future (von Schuckmann et al., 2020). Variations in OHC can induce changes in ocean stratification, currents, sea ice and ice shelfs (IPCC, 2019; 2021); they set time scales and dominate Earth system adjustments to climate variability and change (Hansen et al., 2011); they are a key player in ocean-atmosphere interactions and sea level change (WCRP, 2018) and they can impact marine ecosystems and human livelihoods (IPCC, 2019). '''CMEMS KEY FINDINGS''' Since the year 2005, the upper (0-700m) near-global (60°S-60°N) ocean warms at a rate of 0.6 ± 0.1 W/m2. Note: The key findings will be updated annually in November, in line with OMI evolutions. '''DOI (product):''' https://doi.org/10.48670/moi-00234

The PHYTOBS-Network dataset includes long-term time series on marine microphytoplankton, since 1987, along the whole French metropolitan coast. Microphytoplankton data cover microscopic taxonomic identifications and counts. The whole dataset is available, it includes 25 sampling locations. PHYTOBS-Network studies microphytoplankton diversity in the hydrological context along French coasts under gradients of anthropogenic pressures. PHYTOBS-Network allows to analyse the responses of phytoplankton communities to environmental changes, to assess the quality of the coastal environment through indicators, to define ecological niches, to detect variations in bloom phenology, and to support any scientific question by providing data. The PHYTOBS-Network provides the scientific community and stakeholders with validated and qualified data, in order to improve knowledge regarding biomass, abundance and composition of marine microphytoplankton in coastal and lagoon waters in their hydrological context. PHYTOBS-Network originates of two networks. The historical REPHY (French Observation and Monitoring program for Phytoplankton and Hydrology in coastal waters) supported by Ifremer since 1984 and the SOMLIT (Service d'observation en milieu littoral) supported by INSU-CNRS since 1995. The monitoring has started in 1987 on some sites and later in others. Hydrological data are provided by REPHY or SOMLIT network as a function of site locations.

'''DEFINITION''' Significant wave height (SWH), expressed in metres, is the average height of the highest third of waves. This OMI provides global maps of the seasonal mean and trend of significant wave height (SWH), as well as time series in three oceanic regions of the same variables and their trends from 2002 to 2020, calculated from the reprocessed global L4 SWH product (WAVE_GLO_PHY_SWH_L4_MY_014_007). The extreme SWH is defined as the 95th percentile of the daily maximum SWH for the selected period and region. The 95th percentile is the value below which 95% of the data points fall, indicating higher than normal wave heights. The mean and 95th percentile of SWH (in m) are calculated for two seasons of the year to take into account the seasonal variability of waves (January, February and March, and July, August and September). Trends have been obtained using linear regression and are expressed in cm/yr. For the time series, the uncertainty around the trend was obtained from the linear regression, while the uncertainty around the mean and 95th percentile was bootstrapped. For the maps, if the p-value obtained from the linear regression is less than 0.05, the trend is considered significant. '''CONTEXT''' Grasping the nature of global ocean surface waves, their variability, and their long-term interannual shifts is essential for climate research and diverse oceanic and coastal applications. The sixth IPCC Assessment Report underscores the significant role waves play in extreme sea level events (Mentaschi et al., 2017), flooding (Storlazzi et al., 2018), and coastal erosion (Barnard et al., 2017). Additionally, waves impact ocean circulation and mediate interactions between air and sea (Donelan et al., 1997) as well as sea-ice interactions (Thomas et al., 2019). Studying these long-term and interannual changes demands precise time series data spanning several decades. Until now, such records have been available only from global model reanalyses or localised in situ observations. While buoy data are valuable, they offer limited local insights and are especially scarce in the southern hemisphere. In contrast, altimeters deliver global, high-quality measurements of significant wave heights (SWH) (Gommenginger et al., 2002). The growing satellite record of SWH now facilitates more extensive global and long-term analyses. By using SWH data from a multi-mission altimetric product from 2002 to 2020, we can calculate global mean SWH and extreme SWH and evaluate their trends, regionally and globally. '''KEY FINDINGS''' From 2002 to 2020, positive trends in both Significant Wave Height (SWH) and extreme SWH are mostly found in the southern hemisphere (a, b). The 95th percentile of wave heights (q95), increases faster than the average values, indicating that extreme waves are growing more rapidly than average wave height (a, b). Extreme SWH’s global maps highlight heavily storms affected regions, including the western North Pacific, the North Atlantic and the eastern tropical Pacific (a). In the North Atlantic, SWH has increased in summertime (July August September) but decreased in winter. Specifically, the 95th percentile SWH trend is decreasing by 2.1 ± 3.3 cm/year, while the mean SWH shows a decrease of 2.2 ± 1.76 cm/year. In the south of Australia, during boreal winter, the 95th percentile SWH is increasing at 2.6 ± 1.5 cm/year (c), with the mean SWH increasing by 0.5 ± 0.66 cm/year (d). Finally, in the Antarctic Circumpolar Current, also in boreal winter, the 95th percentile SWH trend is 3.2 ± 2.14 cm/year (c) and the mean SWH trend is 1.7 ± 0.84 cm/year (d). These patterns highlight the complex and region-specific nature of wave height trends. Further discussion is available in A. Laloue et al. (2024). '''DOI (product):''' https://doi.org/10.48670/mds-00352

210Pb, 226Ra and 137Cs were measured by non-destructive gamma spectrometry on marine sediment cores, collected during RIKEAU 2002 cruise on board r/v Thalia, on the shelf of the Bay of Biscay

The Arcachon bay is a meso- / macro-tidal (0.8 to 4.6 m), semi-enclosed lagoon of 180 km² located on the South-western coast of France. Three main water masses are described in this bay: (i) the external neritic waters (ENW) directly influenced by the adjacent oceanic waters, (ii) the intermediate neritic waters (ItNW) and (iii) the inner neritic waters (InNW) more influenced by the continental inputs. The watershed of the Arcachon bay, mainly covered by forests, has an area of 3500 km² and the bay is considered as poorly anthropised. It hosts the largest Zostera noltei seagrass meadow in western Europe and is an important site for oyster farming and Manilla clam production. Since 1997, Arcachon Bay waters are monitored for hydrological and bio-geochemical parameters by the “Environnements et Paléoenvironnements Océaniques et Continentaux” (EPOC) Research Unit of the University of Bordeaux-CNRS, first in one single station (Eyrac), then on 2 complementary sites since 2005 (Bouee13 and Comprian). The monitoring is carried out within the national framework of the “SOMLIT” (“Service d’Observation en Milieu Littoral”) which is a French multi-site monitoring network initiated in the mid-1990s. SOMLIT is based on a joint strategy for 19 sites belonging to 12 ecosystems that are distributed over the three maritime facades of mainland France, i.e. the English Channel, the Atlantic Ocean and the Mediterranean Sea. Sampling of surface water samples is performed fortnightly at high tide for a group of 15 parameters (temperature, salinity, dissolved oxygen, pH, nitrate, nitrite, ammonium, phosphate, silicate, suspended matter, chlorophyll a, concentrations and isotopic ratios of particulate organic carbon and nitrogen) and 8 flow cytometry biological variables of pico- and nanoplankton. Vertical profiles of multiparametric probes concerning 4 parameters (temperature, salinity, fluorescence, PAR) are also performed. Given the significant diversity of coastal ecosystems where SOMLIT’s stations are located, strict and joint guidelines with regards to sampling strategy, measurement methods and data qualification and storage are paramount in order to make FAIR data available to users. The whole data acquisition strategy is carried out within the framework of the SOMLIT quality system formalized in 2006-2007 by referring to the ISO 17025: 2017 standard “General requirements for the competence of testing and calibration laboratories”. Unified sampling and analysis protocols are based on recognized disciplinary standards and on the expertise of the research teams. The scientific objectives of SOMLIT are 1) to characterize the multi-decadal evolution of coastal ecosystems; 2) to determine the climatic and anthropogenic forcings and 3) to make data and logistical support available for research activities and other observation activities. SOMLIT is therefore a research tool providing large datasets that also serve as logistical support for related research actions (from seasonal to long-term studies). Two additional national networks operate at the same SOMLIT sites: “COAST-HF” network performs high-frequency measurements (automated in situ measurements every 10 to 20 minutes) and “PHYTOBS-network” provides microphytoplankton biodiversity data. SOMLIT, COAST-HF and PHYTOBS are elementary networks of the Research Infrastructure “Infrastructure Littorale et Côtière” (ILICO) and are National Observation Services (SNO) of the Institut National des Sciences de l'Univers (INSU).

The SOMLIT-Antioche observation station, located at 5 nautical miles from Chef de Baie harbor (La Rochelle) is part of the French monitoring network SOMLIT (https://www.somlit.fr/), accredited by the INSU-CNRS as a national Earth Science Observatory (Service National d’Observation : SNO), which comprises 12 observation stations distributed throughout France in coastal locations. It aims to detect long-term changes  of these ecosystems under both natural and anthropogenic forcings. SOMLIT is part of the national research infrastructure for coastal ocean observation ILICO (https://www.ir-ilico.fr/?PagePrincipale&lang=en). The SOMLIT-Antioche station (46.0842 °N, 1.30833 °W) is located in the north-eastern part of the Bay of Biscay, halfway between the islands of Ré and Oléron, at the centre of what is commonly known as the Pertuis Charentais area, which correspond to a semi-enclosed shallow basin and includes four islands (Ré, Oléron, Aix and Madame) and three Pertuis (i.e., detroit) (Breton, Antioche and Maumusson). This 40m-deep site, with muddy to sandy marine bottoms, is submitted to a macro-tidal regime and is largely open to the prevailing westerly swells. It remains under a dominant oceanic/neritic influence, even though its winter/spring hydrological context is influenced by the diluted plumes of the Charente, Gironde and Loire rivers, but not by those of too small estuaries (Lay, Seudre and Sèvre Niortaise). SOMLIT-Antioche hydrological monitoring has been carried out by the LIENSs/OASU laboratory on a fortnightly basis since June 2011. Surface water samples are collected  at high-tide during intermediate tides (70 ± 10 in SHOM units) on board the research  vessel ‘L’Estran’ owned by La Rochelle University. Samples are analyzed for more than 16 core parameters: temperature, salinity, dissolved oxygen, pH, ammonia, nitrates, nitrites, phosphates, silicates, suspended matter, particulate organic carbone, particulate organic nitrogen, chlorophyll, delta15N, delta13C; pico- and nano- plankton. Measurements are carried out in accordance with the ISO/IEC 17025:2017 standard. Simultaneous monitoring of the micro-phytoplankton community (since 2013, SNO PHYTOBS: https://www.phytobs.fr/en) and monitoring of prokaryotic communities (Bacteria and Archaea) are also carried out on a monthly basis. Since 2019, seasonal observations of benthic invertebrate communities (SNO BenthObs : https://www.benthobs.fr/) have also been carried out. This monitoring is complementary to that carried out at hydrological stations in the pre-existing REPHY and DCE networks, some of which are located near marine farming areas (oyster and mussel farms).

Rapid changes in ocean circulation and climate have been observed in marine-sediment and ice cores over the last glacial period and deglaciation, highlighting the non-linear character of the climate system and underlining the possibility of rapid climate shifts in response to anthropogenic greenhouse gas forcing. To date, these rapid changes in climate and ocean circulation are still not fully explained. One obstacle hindering progress in our understanding of the interactions between past ocean circulation and climate changes is the difficulty of accurately dating marine cores. Here, we present a set of 92 marine sediment cores from the Atlantic Ocean for which we have established age-depth models that are consistent with the Greenland GICC05 ice core chronology, and computed the associated dating uncertainties, using a new deposition modeling technique. This is the first set of consistently dated marine sediment cores enabling paleoclimate scientists to evaluate leads/lags between circulation and climate changes over vast regions of the Atlantic Ocean. Moreover, this data set is of direct use in paleoclimate modeling studies.

The Mediterranean Sea is a natural laboratory to address questions about the formation and evolution of continental margins and the relationship between surface and deep processes. Different regional to local events have influenced the Neogene stratigraphic evolution of the Valencia and Menorca basins. The evaporites deposited during the Messinian Salinity Crisis (MSC) strongly impact its sedimentary and geomorphological evolution. Here we present a compilation of the main regional seismic stratigraphic markers from the continental platform to the deep sea. We provide in xyz format (z in second twt) the original picking files, (not interpolated) and interpolated grid of: i) the top of the Mesozoic formation, the base of the Neogene formations including the early Miocene volcanic features, ii) the top Burdigalian, Langhian, and Serravallian seismic horizons, iii) the seismic horizons related to the Messinian Salinity Crisis, iv) the Pliocene and Pleistocene seismic horizons v) the depth of the Seafloor. The available reflection seismic dataset results from the compilation and processing of vintage seismic profiles of previous works and from the Instituto Geologico y Minero de Espana (IGME). This compilation is currently the first available in literature and provides a useful contribution to the scientific community working on sedimentary, tectonics and geodynamics within the Western Mediterranean basins.

This visualization product displays fishing related items density per trawl. EMODnet Chemistry included the collection of marine litter in its 3rd phase. Since the beginning of 2018, data of seafloor litter collected by international fish-trawl surveys have been gathered and processed in the EMODnet Chemistry Marine Litter Database (MLDB). The harmonization of all the data has been the most challenging task considering the heterogeneity of the data sources, sampling protocols (OSPAR and MEDITS protocols) and reference lists used on a European scale. Moreover, within the same protocol, different gear types are deployed during bottom trawl surveys. In cases where the wingspread and/or the number of items were/was unknown, it was not possible to use the data because these fields are needed to calculate the density. Data collected before 2011 are concerned by this filter. When the distance reported in the data was null, it was calculated from: - the ground speed and the haul duration using the following formula: Distance (km) = Haul duration (h) * Ground speed (km/h); - the trawl coordinates if the ground speed and the haul duration were not filled in. The swept area was calculated from the wingspread (which depends on the fishing gear type) and the distance trawled: Swept area (km²) = Distance (km) * Wingspread (km) Densities were calculated on each trawl using the following computation: Density of fishing related items (number of items per km²) = ∑Number of fishing related items / Swept area (km²) Percentiles 50, 75, 95 & 99 were calculated taking into account data for all years. The list of selected items for this product is attached to this metadata. Information on data processing and calculation is detailed in the attached methodology document. Warning: the absence of data on the map does not necessarily mean that they do not exist, but that no information has been entered in the Marine Litter Database for this area.