Global wave hindcast (1961-2020) at 1° resolution using CMIP6 wind and sea-ice forcings for ALL (historical), GHG (historical greenhouse-gas-only), AER (historical Anthropogenic-aerosol-only), NAT (historical natural only) scenario.

WGS for Iatlantic projet ( ) for assessing past and present connectivity

Serveur wms du projet CHARM III

In order to better characterize the genetic diversity of Cetaceans and especially the common Dolphin from the Bay of Biscay, sequences from the mitochondrial Cytochrome B region were obtained from water samples acquired close to groups of dolphins.

The GEBCO_2022 Grid is a global continuous terrain model for ocean and land with a spatial resolution of 15 arc seconds. In regions outside of the Arctic Ocean area, the grid uses as a base Version 2.4 of the SRTM15_plus data set (Tozer, B. et al, 2019). This data set is a fusion of land topography with measured and estimated seafloor topography. Included on top of this base grid are gridded bathymetric data sets developed by the four Regional Centers of The Nippon Foundation-GEBCO Seabed 2030 Project. The GEBCO_2022 Grid represents all data within the 2022 compilation. The compilation of the GEBCO_2022 Grid was carried out at the Seabed 2030 Global Center, hosted at the National Oceanography Centre, UK, with the aim of producing a seamless global terrain model. Outside of Polar regions, the Regional Centers provide their data sets as sparse grids i.e. only grid cells that contain data are populated. These data sets were included on to the base using a remove-restore blending procedure. This is a two-stage process of computing the difference between the new data and the base grid and then gridding the difference and adding the difference back to the existing base grid. The aim is to achieve a smooth transition between the new and base data sets with the minimum of perturbation of the existing base data set. The data sets supplied in the form of complete grids (primarily areas north of 60N and south of 50S) were included using feather blending techniques from GlobalMapper software. The GEBCO_2022 Grid has been developed through the Nippon Foundation-GEBCO Seabed 2030 Project. This is a collaborative project between the Nippon Foundation of Japan and the General Bathymetric Chart of the Oceans (GEBCO). It aims to bring together all available bathymetric data to produce the definitive map of the world ocean floor by 2030 and make it available to all. Funded by the Nippon Foundation, the four Seabed 2030 Regional Centers include the Southern Ocean - hosted at the Alfred Wegener Institute, Germany; South and West Pacific Ocean - hosted at the National Institute of Water and Atmospheric Research, New Zealand; Atlantic and Indian Oceans - hosted at the Lamont-Doherty Earth Observatory, Columbia University, USA; Arctic and North Pacific Oceans - hosted at Stockholm University, Sweden and the Center for Coastal and Ocean Mapping at the University of New Hampshire, USA.

The SWISCA Level 2S (L2S) product provides along-track colocation of SWIM wave measuring instrument onto SCAT scatterometer grid, over the global ocean. SWIM and SCAT are both instruments onboard CFOSAT. CFOSAT (Chinese French Ocean SATellite) is a french-chinese mission launched in 2018, whose aim is to provide wind (SCAT instrument) and wave (SWIM instrument) measurements over the sea surface. The SWISCA L2S product is broken down into three different subproducts: - L2A containing the sigma0 of both SWIM and SCAT - L2B containing the wave parameters measured by SWIM and wind vectors measured by SCAT - AUX containing additional ancillary fields such as sea ice concentration (from CERSAT/SSMI), ocean currents (from CMEMS/GlobCurrent), SST and Wind (from ECMWF), rain rate (from IMERG), and WaveWatch3 wave spectra. All SWIM and ancillary observations are resampled onto SCAT scatterometer's geometry (wind vector cells, WVC). The SWISCA level 2S product is generated in delayed mode, a few days after acquisition. It is intended to foster cross analysis of SWIM and SCAT observations, and their combination to improve the retrieval of both wind and wave parameters. The SWISCA L2S product is generated and distributed by Ifremer / CERSAT in the frame of the Ifremer Wind and Wave Operation Center (IWWOC) co-funded by Ifremer and CNES and dedicated to the processing of the delayed mode data of CFOSAT mission.

The Mediterranean Sea is generally described as an oligotrophic area where primary productivity is limited to a few coastal environments with nutrient-enriched fluvial input. However, several studies have revealed that the hydrology of the western Mediterranean has major seasonal productive patterns linked either to significant riverine input or to seasonal upwelling cells. This study aims to: i) discuss organic microfossils (i.e. pollen and dinoflagellate cyst assemblages, as well as other non-pollen palynomorphs) from two different productive areas of the western Mediterranean Sea, and ii) examine the importance of the interconnections between marine and continental influences responsible for modern palynomorph distributions. Based on 25 samples from the Gulf of Lion (GoL) and Algerian Margin, this study key findings are: i) that GoL marine productivity is driven by the combination of discharges from the Rhône River and seasonal upwelling mechanisms, ii) that the strong productive pattern of the northern African coast is driven by water density front mixings and related upwellings. These two patterns are discussed in the light of major links that provide a better understanding of the signatures of marine and continental bio-indicators. The dinocyst Lingulodinium machaerophorum can be considered as a tracer of Rhône River plume influence in the GoL. Brigantedinium taxa are shown to be upwelling-sensitive in both studied areas. Typical differences in vegetation across the north–south climate gradient in the western Mediterranean Basin are highlighted by the larger ratio of Euro-Siberian to Mediterranean pollen taxa in the northern sector. Synoptic maps also illustrate the complex interactions of environmental drivers determining the distributions of continental and marine palynomorphs in the western Mediterranean Sea.

In recent years, large datasets of in situ marine carbonate system parameters (partial pressure of CO2 (pCO2), total alkalinity, dissolved inorganic carbon and pH) have been collated. These carbonate system datasets have highly variable data density in both space and time, especially in the case of pCO2, which is routinely measured at high frequency using underway measuring systems. This variation in data density can create biases when the data are used, for example for algorithm assessment, favouring datasets or regions with high data density. A common way to overcome data density issues is to bin the data into cells of equal latitude and longitude extent. This leads to bins with spatial areas that are latitude and projection dependent (eg become smaller and more elongated as the poles are approached). Additionally, as bin boundaries are defined without reference to the spatial distribution of the data or to geographical features, data clusters may be divided sub-optimally (eg a bin covering a region with a strong gradient). To overcome these problems and to provide a tool for matching in situ data with satellite, model and climatological data, which often have very different spatiotemporal scales both from the in situ data and from each other, a methodology has been created to group in situ data into ‘regions of interest’, spatiotemporal cylinders consisting of circles on the Earth’s surface extending over a period of time. These regions of interest are optimally adjusted to contain as many in situ measurements as possible. All in situ measurements of the same parameter contained in a region of interest are collated, including estimated uncertainties and regional summary statistics. The same grouping is done for each of the other datasets, producing a dataset of matchups. About 35 million in situ datapoints were then matched with data from five satellite sources and five model and re-analysis datasets to produce a global matchup dataset of carbonate system data, consisting of 287,000 regions of interest spanning 54 years from 1957 to 2020. Each region of interest is 100 km in diameter and 10 days in duration. An example application, the reparameterisation of a global total alkalinity algorithm, is shown. This matchup dataset can be updated as and when in situ and other datasets are updated, and similar datasets at finer spatiotemporal scale can be constructed, for example to enable regional studies. This dataset was funded by ESA Satellite Oceanographic Datasets for Acidification (OceanSODA) project which aims at developing the use of satellite Earth Observation for studying and monitoring marine carbonate chemistry.

This dataset provides Level 4 total current including geostrophy and a data-driven approach for Ekman and near-inertial current, based on a convolution between drifter observation and wind history, to fit empirically a complex and time-lag dependant transfert function between ERA5 wind stress and current 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 Datlas and is distributed by Ifremer / CERSAT in the frame of the World Ocean Circulation (WOC) project funded by the European Space Agency (ESA).

The diet and stable isotopic (i.e. δ15N and δ13C values) compositions of eels have been studied during each season of 2019 with a fyke net in six estuaries located along the French coast of the eastern English Channel (Slack, Wimereux, Liane, Canche, Authie and Somme estuaries) (10.1371/journal.pone.0270348).