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.

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.

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

A prerequisite for a successful development of a multi-mission wind dataset is to ensure good inter-calibration of the different extreme wind datasets to be integrated in the product. Since the operational hurricane community is working with the in-situ dropsondes as wind speed reference, which are in turn used to calibrate the NOAA Hurricane Hunter Stepped Frequency Microwave Radiometer (SFMR) wind data, MAXSS has used the latter to ensure extreme-wind inter-calibration among the following scatterometer and radiometer systems: the Advanced Scatterometers onboard the Metop series (i.e., ASCAT-A, -B, and -C), the scatterometers onboard Oceansat-2 (OSCAT) and ScatSat-1 (OSCAT-2), and onboard the HY-2 series (HSCAT-A, -B); the Advanced Microwave Scanning Radiometer 2 onboard GCOM-W1(AMSR-2), the multi-frequency polarimetric radiometer (Windsat), and the L-band radiometers onboard the Soil Moisture and Ocean Salinity (SMOS) and the Soil Moisture Active Passive (SMAP) missions. In summary, a two-step strategy has been followed to adjust the high and extreme wind speeds derived from the mentioned scatterometer and radiometer systems, available in the period 2009-2020. First, the C-band ASCATs have been adjusted against collocated storm-motion centric SFMR wind data. Then, both SFMR winds and ASCAT adjusted winds have been used to adjust all the other satellite wind systems. In doing so, a good inter-calibration between all the systems is ensured not only under tropical cyclone (TC) conditions, but also elsewhere. This dataset was produced in the frame of the ESA funded Marine Atmosphere eXtreme Satellite Synergy (MAXSS) project. The primary objective of the ESA Marine Atmosphere eXtreme Satellite Synergy (MAXSS) project is to provide guidance and innovative methodologies to maximize the synergetic use of available Earth Observation data (satellite, in situ) to improve understanding about the multi-scale dynamical characteristics of extreme air-sea interaction.

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 ESA Sea State Climate Change Initiative (CCI) project has produced global daily merged multi-sensor time-series of along-track satellite altimeter significant wave height data (referred to as Level 3 (L3) data) with a particular focus for use in climate studies. This dataset contains the Version 3 Remote Sensing Significant Wave Height product, which provides along-track data at approximately 6 km spatial resolution. It has been generated from upstream Sea State CCI L2P products, edited and merged into daily products, retaining only valid and good quality measurements from all altimeters over one day, with simplified content (only a few key parameters). This is close to what is delivered in Near-Real Time by the CMEMS (Copernicus - Marine Environment Monitoring Service) project. It covers the date range from 2002-2021. The altimeter data used in the Sea State CCI dataset v3 come from multiple satellite missions (Envisat, CryoSat-2, Jason-1, Jason-2, Jason-3, SARAL, Sentinel-3A), therefore spanning over a shorter time range than version 1.1. Unlike version 1.1, this version 3 involved a complete and consistent retracking of all the included altimeters. Many altimeters are bi-frequency (Ku-C or Ku-S) and only measurements in Ku band were used, for consistency reasons, being available on each altimeter but SARAL (Ka band).

Understanding the dynamics of species interactions for food (prey-predator, competition for resources) and the functioning of trophic networks (dependence on trophic pathways, food chain flows, etc.) has become a thriving ecological research field in recent decades. This empirical knowledge is then used to develop population and ecosystem modelling approaches to support ecosystem-based management. The TrophicCS data set offers spatialized trophic information on a large spatial scale (the entire Celtic Sea continental shelf and upper slope) for a wide range of species. It combines ingested prey (gut content analysis) and a more integrated indicator of food sources (stable isotope analysis). A total of 1337 samples of large epifaunal invertebrates (bivalve mollusks and decapod crustaceans), zooplankton, fish and cephalopods, corresponding to 114 species, were collected and analyzed for stable isotope analysis of their carbon and nitrogen content. Sample size varied between taxa (from 1 to 52), with an average of 11.72 individuals sampled per species, and water depths ranged from 57 to 516 m. The gut contents of 1026 fish belonging to ten commercially important species: black anglerfish (Lophius budegassa), white anglerfish (Lophius piscatorius), blue whiting (Micromesistius poutassou), cod (Gadus morhua), haddock (Melanogrammus aeglefinus), hake (Merluccius merluccius), megrim (Lepidorhombus whiffiagonis), plaice (Pleuronectes platessa), sole (Solea solea) and whiting (Merlangius merlangus) were analyzed. The stomach content data set contains the occurrence of prey in stomach, identified to the lowest taxonomic level possible. To consider potential ontogenetic diet changes, a large size range was sampled. The TrophicCS data set was used to improve understanding of trophic relationships and ecosystem functioning in the Celtic Sea. When you use the data in your publication, we request that you cite this data paper. If you use the present data set (TrophicCS) for the majority of the data analyzed in your study, you may wish to consider inviting at least one author of the core team of this data paper to become a collaborator /coauthor of your paper.

French benthic invertebrates composition and abundance taxa data are collected during monitoring surveys on the English Channel / Bay of Biscay coasts and Mediterranean coast (Quadrige program code : REBENT_FAU, RSL_FAU). Protocols are implemented in the Water Framework Directive.  Data are transmitted in a Seadatanet format (CDI + ODV) to EMODnet Biology european database. 498 ODV files have been generated from period 01/01/2003 to 31/12/2021.

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.