2022
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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).
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Particularly suited to the purpose of measuring the sensitivity of benthic communities to trawling, a trawl disturbance indicator (de Juan and Demestre, 2012, de Juan et al. 2009) was proposed based on benthic species biological traits to evaluate the sensibility of mega- and epifaunal community to fishing pressure known to have a physical impact on the seafloor (such as dredging and bottom trawling). The selected biological traits were chosen as they determine vulnerability to trawling: mobility, fragility, position on substrata, average size and feeding mode that can easily be related to the fragility, recoverability and vulnerability ecological concepts. The five categories retained are functional traits that were selected based on the knowledge of the response of benthic taxa to trawling disturbance (de Juan et al., 2009). They reflect respectively the possibility to avoid direct gear impact, to benefit from trawling for feeding, to escape gear, to get caught by the net and to resist trawling/dredging action, each of these characteristics being either advantageous or sensitive to trawling. To expand this approach to that proposed by Certain et al. (2015), the protection status of certain species was also indicated. To enable quantitative analysis, a score was assigned to each category: from low sensitivity (0) to high sensitivity (3). Biological traits of species have been defined, from the BIOTIC database (MARLIN, 2014) and from information given by Garcia (2010), Le Pape et al. (2007) and Brind’Amour et al. (2009). For missing traits, additional information from literature has been considered. The protection status of each taxa was also scored: Atlantic species listed in OSPAR List of Threatened and/or Declining Species and Habitats (https://www.ospar.org/work-areas/bdc/species-habitats/list-of-threatened-declining-species-habitats) and Mediterranean species listed in Vulnerable Marine Ecosystems (FAO, 2018 and Oceana, 2017) were scored 3 and other species were scored 1. The scores of 1085 taxa commonly found in bottom trawl by-catch in the southern North Sea, English Channel and north-western Mediterranean were described.
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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.
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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.
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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.
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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.
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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.
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Serveur wms du projet CHARM II
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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).
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Serveur wms sur les photos anciennes
Catalogue PIGMA