Serveur wms du projet CHARM II

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.

Raw reads for the assembly of Gambusia holbrooki genome.

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 multi-sensor time-series of along-track satellite synthetic aperture radar (SAR) integrated sea state parameters (ISSP) data from Sentinel-1 (referred to as SAR WV onboard Sentinel-1 Level 2P (L2P) ISSP data) with a particular focus for use in climate studies. This dataset contains the Sentinel-1 SAR Remote Sensing Integrated Sea State Parameter product (v1.0), which forms part of the ESA Sea State CCI version 3.0 release. This product provides along-track primary significant wave height measurements and secondary sea state parameters, calibrated with CMEMS model data and reference in situ measurements at 20km resolution every 100km, processed using the Pleskachevsky et. al., 2021 emprical model, separated per satellite and pass, including all measurements with flags and uncertainty estimates. These are expert products with rich content and no data loss. The SAR Wave Mode data used in the Sea State CCI SAR WV onboard Sentinel-1 Level 2P (L2P) ISSP v3 dataset come from the Sentinel-1 satellite missions spanning from 2014 to 2021 (Sentinel-1 A, Sentinel-1 B).

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.

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.

This dataset provides surface Stokes drift as retrieved from the wave energy spectrum computed by the spectral wave model WAVEWATCH-III (r), under NOAA license, discretized in wave numbers and directions and the water depth at each location. It is estimated at the sea surface and expressed in m.s-1. WAVEWATCH-III (r) model solves the random phase spectral action density balance equation for wavenumber-direction spectra. Please refer to the WAVEWATCH-III User Manual for fully detailed description of the wave model equations and numerical approaches. 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 Ifremer / LOPS and is distributed by Ifremer / CERSAT in the frame of the World Ocean Circulation (WOC) project funded by the European Space Agency (ESA).

This dataset provides detections of fronts derived from low resolution optimally interpolated remote sensing microwave SST L4 from REMSS over North Atlantic region. 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 OceanDataLab and is distributed by Ifremer / CERSAT in the frame of the World Ocean Circulation (WOC) project funded by the European Space Agency (ESA).

The Level 4 merged microwave wind product is a complete set of hourly global 10-m wind maps on a 0.25x0.25 degree latitude-longitude grid, spanning 1 Jan 2010 through the end of 2020. The product combines background neutral equivalent wind fields from ERA5, daily surface current fields from CMEMS, and stress equivalent winds obtained from several microwave passive and active sensors to produce hourly surface current relative stress equivalent wind analyses. The satellite winds include those from recently launched L-band passive sensors capable of measuring extreme winds in tropical cyclones, with little or no degradation from precipitation. All satellite winds used in the analyses have been recalibrated using a large set of collocated satellite-SFMR wind data in storm-centric coordinates. To maximize the use of the satellite microwave data, winds within a 24-hour window centered on the analysis time have been incorporated into each analysis. To accomodate the large time window, satellite wind speeds are transformed into deviations from ERA5 background wind speeds interpolated to the measurement times, and then an optical flow-based morphing technique is applied to these wind speed increments to propagate them from measurement to analysis time. These morphed wind speed increments are then added to the background wind speed at the analysis time to yield a set of total wind speeds fields for each sensor at the analysis time. These individual sensor wind speed fields are then combined with the background 10-m wind direction to yield vorticity and divergence fields for the individual sensor winds. From these, merged vorticity and divergence fields are computed as a weighted average of the individual vorticity and divergence fields. The final vector wind field is then obtained directly from these merged vorticity and divergence fields. Note that one consequence of producing the analyses in terms of vorticity and divergence is that there are no discontinuities in the wind speed fields at the (morphed) swath edges. There are two important points to be noted: the background ERA5 wind speed fields have been rescaled to be globally consistent with the recalibrated AMSR2 wind speeds. This rescaling involves a large increase in the ERA5 background winds beyond about 17 m/s. For example, an ERA5 10 m wind speed of 30 m/s is transformed into a wind speed of 41 m/s, and a wind speed of 34 m/s is transformed into a wind speed of about 48 m/s. Besides the current version of the product is calibrated for use within tropical cyclones and is not appropriate for use elsewhere. This dataset was produced in the frame of ESA 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.