New results acquired in south-Brittany (MD08-3204 CQ core: Bay of Quiberon and VK03-58bis core: south Glénan islands) allow depicting Holocene paleoenvironmental changes from 8.5 ka BP to present through a multi-proxy dataset including sedimentological and palynological data. First, grain-size analyses and AMS-14C dates highlight a common sedimentary history for both study cores. The relative sea level (RSL) slowdown was accompanied by a significant drop of the sedimentation rates between ca. 8.3 and 5.7 ka BP, after being relatively higher at the onset of the Holocene. This interval led to the establishment of a shell-condensed level, identified in core VK03-58bis by the “Turritella layer” and interpreted as a marker for the maximum flooding surface. Palynological data (pollen grains and dinoflagellate cyst assemblages) acquired in core MD08-3204 CQ argue for an amplification of the fluvial influence since 5.7 ka BP; the establishment of the highstand system tract (i.e., mixed marine and fluviatile influences on the platform) then accompanying the slowdown of the RSL rise-rates. On the shelf, the amplification of Anthropogenic Pollen Indicators (API) is then better detected since 4.2 ka BP, not only due to human impact increase but also due to a stronger fluvial influence on the shelf during the Late Holocene. Palynological data, recorded on the 8.5–8.3 ka BP interval along an inshore-offshore gradient, also demonstrate the complexity of the palynological signal such as i) the fluvial influence that promotes some pollinic taxa (i.e., Corylus, Alnus) from proximal areas and ii) the macro-regionalization of palynomorph sources in distal cores. In addition, the comparison of palynological tracers, including API, over the last 7 kyrs, with south-Brittany coastal and mid-shelf sites subjected to northern vs. southern Loire catchment areas, allowed discussing a major hydro-climatic effect on the reconstructed palynological signals. Strengthened subpolar gyre dynamics (SPG), combined with recurrent positive North Atlantic Oscillation (NAO) configurations, appear responsible for increased winter precipitations and fluvial discharges over northern Europe, such as in Brittany. Conversely, weakened SPG intervals, associated with negative NAO-like modes, are characterized by intensified winter fluvial discharges over southern Europe. Interestingly, we record, at an infra-orbital timescale, major peaks of API during periods of strengthened (/weakened) SPG dynamics in sites subjects to Brittany watersheds (/Loire watersheds) inputs.

The SARWAVE project is developing a new sea state processor from SAR images to be applied over open ocean, sea ice, and coastal areas, and exploring potential synergy with other microwave and optical EO products.

Serveur wms du projet CHARM II

French Zostera Marina et Zostera Noltei abundance data are collected during monitoring surveys on the English Channel / Bay of Biscay coasts. Protocols are impletmented in the Water Framework Directive. Data are transmitted in a Seadatanet format (CDI + ODV) to EMODnet Biology european database. 35 ODV files have been generated from period 01/01/2004 to 31/12/2021 for Z. Marina and from 01/01/2011 to 31/12/2021 for Z. Noltei.  

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.

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

Raw reads for the assembly of Gambusia holbrooki genome.

This dataset consists of metatranscriptomic sequencing reads corresponding to coastal micro-eukaryote communities sampled in Western Europe in 2018 and 2019.

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.

Wave impact is the primary cause of coastal structure failure. While wave impact is widely studied in controlled environments, in situ measurements of wave impact pressure are rare. The results of a campaign to measure wave impact pressure in situ are summarised here. Data were collected from 2016 to 2019 from anchored pressure gauges on the wall of the Artha breakwater in southwestern France. The acquisition frequency is 10 kHz and 10-minute bursts are recorded every hour. Two databases are published, one by burst and one by impact. The burst database summarises the main parameters describing the 10-minute record, while the impact database contains a list of parameters describing each impact.