This visualization product displays beaches locations where the Marine Strategy Framework Directive (MSFD) monitoring protocol has been applied to collate data on macrolitter (> 2.5 cm). Reference lists associated with these protocols have been indicated with different colors in the map. EMODnet Chemistry included the collection of marine litter in its 3rd phase. Since the beginning of 2018, data of beach litter 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 and reference lists used on a European scale. Preliminary processings were necessary to harmonize all the data: - Exclusion of OSPAR 1000 protocol: in order to follow the approach of OSPAR that it is not including these data anymore in the monitoring; - Selection of MSFD surveys only (exclusion of other monitoring, cleaning and research operations); - Exclusion of beaches without coordinates; - Some categories & some litter types like organic litter, small fragments (paraffin and wax; items > 2.5cm) and pollutants have been removed. This list was created using EU Marine Beach Litter Baselines, the European Threshold Value for Macro Litter on Coastlines and the Joint list of litter categories for marine macro-litter monitoring from JRC (these three documents are attached to this metadata). More information is available in the attached documents. 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.

ROCCH, the French Chemical Contaminant Monitoring Network, regularly provides data for assessing the chemical quality of French coastal waters. Concentrations of trace metals and organic compounds are measured in integrative matrices (bivalves and sediments). Surface sediment samples are collected from 200 to 250 monitoring stations in the English Channel, the Bay of Biscay and Mediterranean lagoons every six years. Results concerning approximately 140 historical and emerging chemical substances (metals, PAHs, PCBs, PBDEs, PFAS …) are submitted to international databases of the Regional Sea Convention (OSPAR for the North East Atlantic and the Barcelona Convention for the Mediterranean) and disseminated to public stakeholders. During the ROCCHSED campaign in spring 2022, three sediment cores, each forty to fifty centimetres long, were collected from three different sites in the Bay of Biscay. Horizons of one to two centimetres in length were dated, sieved and freeze-dried for chemical analysis. The concentrations of metals, PAHs and PCBs were determined in horizons aged from over 150 years to the present in order to define the reference concentration of natural levels and describe the temporal profile of contamination.

'''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

This visualization product displays the cigarette related items abundance of marine macro-litter (> 2.5cm) per beach per year from Marine Strategy Framework Directive (MSFD) monitoring surveys without UNEP-MARLIN data. EMODnet Chemistry included the collection of marine litter in its 3rd phase. Since the beginning of 2018, data of beach litter 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 and reference lists used on a European scale. Preliminary processings were necessary to harmonize all the data: - Exclusion of OSPAR 1000 protocol: in order to follow the approach of OSPAR that it is not including these data anymore in the monitoring; - Selection of MSFD surveys only (exclusion of other monitoring, cleaning and research operations); - Exclusion of beaches without coordinates; - Selection of cigarette related items only. The list of selected items is attached to this metadata. This list was created using EU Marine Beach Litter Baselines, the European Threshold Value for Macro Litter on Coastlines and the Joint list of litter categories for marine macro-litter monitoring from JRC (these three documents are attached to this metadata); - Exclusion of surveys referring to the UNEP-MARLIN list: the UNEP-MARLIN protocol differs from the other types of monitoring in that cigarette butts are surveyed in a 10m square. To avoid comparing abundances from very different protocols, the choice has been made to distinguish in two maps the cigarette related items results associated with the UNEP-MARLIN list from the others; - Normalization of survey lengths to 100m & 1 survey / year: in some case, the survey length was not exactly 100m, so in order to be able to compare the abundance of litter from different beaches a normalization is applied using this formula: Number of cigarette related items of the survey (normalized by 100 m) = Number of cigarette related items of the survey x (100 / survey length) Then, this normalized number of cigarette related items is summed to obtain the total normalized number of cigarette related items for each survey. Finally, the median abundance of cigarette related items for each beach and year is calculated from these normalized abundances of cigarette related items per survey. Sometimes the survey length was null or equal to 0. Assuming that the MSFD protocol has been applied, the length has been set at 100m in these cases. Percentiles 50, 75, 95 & 99 have been calculated taking into account cigarette related items from MSFD monitoring data (excluding UNEP-MARLIN protocol) for all years. More information is available in the attached documents. 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.

This visualization product displays the single use plastics (SUP) related items abundance of marine macro-litter (> 2.5cm) per beach per year from non-MSFD monitoring surveys, research & cleaning operations. EMODnet Chemistry included the collection of marine litter in its 3rd phase. Since the beginning of 2018, data of beach litter 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 and reference lists used on a European scale. Preliminary processing were necessary to harmonize all the data: - Exclusion of OSPAR 1000 protocol: in order to follow the approach of OSPAR that it is not including these data anymore in the monitoring; - Selection of surveys from non-MSFD monitoring, cleaning and research operations; - Exclusion of beaches without coordinates; - Selection of SUP related items only. The list of selected items is attached to this metadata. This list was created using EU Marine Beach Litter Baselines, the European Threshold Value for Macro Litter on Coastlines and the Joint list of litter categories for marine macro-litter monitoring from JRC (these three documents are attached to this metadata). The selection was adapted to the Joint list of litter categories SUP identification and therefore contains some differences with the selection made for previously published versions of this product; - Exclusion of surveys without associated length; - Normalization of survey lengths to 100m & 1 survey / year: in some case, the survey length was not 100m, so in order to be able to compare the abundance of litter from different beaches a normalization is applied using this formula: Number of SUP related items of the survey (normalized by 100 m) = Number of SUP related items of the survey x (100 / survey length) Then, this normalized number of SUP related items is summed to obtain the total normalized number of SUP related items for each survey. Finally, the median abundance of SUP related items for each beach and year is calculated from these normalized abundances of SUP related items per survey. Percentiles 50, 75, 95 & 99 have been calculated taking into account SUP related items from other sources data for all years. More information is available in the attached documents. 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.

'''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

A world deep displacement dataset comprising more than 1600 000 Argo floats deep displacements, has been produced from the global Argo float database (GDAC). ANDRO dataset was completed over the period 2000-2009, then was partially but yearly updated since 2010. ANDRO actual contents and format is described in the user guide, which must be carefully read before using ANDRO (ANDRO format is also described in Ollitrault M. et al (2013)). One important feature of ANDRO is that the pressures measured during float drifts at depth, and suitably averaged are preserved in ANDRO (see Figure 2). To reach this goal, it was necessary to reprocess most of the Argo raw data, because of the many different decoding versions (roughly 100) not always applied by the DACs to the displacement data because they were mainly interested in the p,t,S profiles. The result of our work was the production of comprehensive files, named DEP (for déplacements in French), containing all the possibly retrievable float data. For detailed information and status of the last released ANDRO product, please visit the dedicated Argo France web page: https://www.umr-lops.fr/SNO-Argo/Products/ANDRO-Argo-floats-displacements-Atlas

This visualization product displays nets locations (start positions) where specific protocols have been applied to collate data on microlitter. Mesh size used with these protocols have been indicated with different colors in the map. 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. 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.

This set of data documents the radiocarbon dates (n=19) obtained thanks to the accelerator mass spectrometry method (AMS) at the LMC14/ARTEMIS French national facility on the cores (Multicorer, Kullenberg) retrieved from the West-Gironde mud patch (WGMP) during the JERICObent-7 cruise (10-15 July 2019; NR Côtes de la Manche, https://doi.org/10.17600/18001022). The WGMP registers very high sedimentation rates since the last 600 years (≥ 0.3 cm/yr) and is thus of great interest for palaeoceanographic investigations. At present, this depocenter marks the mid-shelf of the temperate Bay of Biscay off major French rivers from the Aquitaine basin. The fine mud deposits of the WGMP are of 3 to 4 meters thick and lie on palimpsest levels rich in gravels and shells. They cover a V-shaped structure, oriented SW-NE, which is attributed to the incision(s) of a paleovalley in the Cenozoic substrate, mainly linked to the paleo-Gironde routing changes during past glacials/interglacials, and its potential past convergences with the paleo-rivers of the Antioche perthuis (Seudre, Charente paleovalleys?) at that times. Detailed information on each sample is presented with the 14C results obtained by the Artemis AMS facility at LMC14 laboratory (Dumoulin et al. 2017- https://doi.org/10.1017/RDC.2016.116, Beck et al. 2024- https://doi.org/10.1017/RDC.2023.23). Raw ages are indicated together with calibration calculations using the last two versions of the Calib software (http://calib.org/, Calib 7 and 8) to show the dispersion of ages linked to the updating of calibration curves (Marine13, Intcal13, Marine20, Intcal 20). The calibrated ages finally retained for publications (used in the related Seanoe document - https://doi.org/10.17882/104237 - and published in Eynaud et al., 2025 for the ST3c core, https://doi.org/10.1016/j.gloplacha.2025.105039) are those obtained with the last Calib 8.1 version. Raw 14C ages were calibrated and converted to calendar ages using the IntCal20 calibration curve with a reservoir age correction of 400 years deduced from Radionuclide analyses (137Cs and 210Pb) at the top of the studied cores (see Schmidt, 2025, https://www.seanoe.org/data/00968/107979/). 

Web Map Service for Emodnet Chemistry