Format

*

6016 record(s)
 
Type of resources
Available actions
Topics
Keywords
Contact for the resource
Provided by
Years
Formats
Representation types
Update frequencies
status
Service types
Scale
Resolution
From 1 - 10 / 6016
  • '''This product has been archived''' For operationnal and online products, please visit https://marine.copernicus.eu '''Short description:''' The Global Ocean Satellite monitoring and marine ecosystem study group (GOS) of the Italian National Research Council (CNR), in Rome, distributes Level-4 product including the daily interpolated chlorophyll field with no data voids starting from the multi-sensor (MODIS-Aqua, NOAA-20-VIIRS, NPP-VIIRS, Sentinel3A-OLCI at 300m of resolution) (at 1 km resolution) and the monthly averaged chlorophyll concentration for the multi-sensor (at 1 km resolution) and Sentinel-OLCI Level-3 (at 300m resolution). Chlorophyll field are obtained by means of the Mediterranean regional algorithms: an updated version of the MedOC4 (Case 1 waters, Volpe et al., 2019, with new coefficients) and AD4 (Case 2 waters, Berthon and Zibordi, 2004). Discrimination between the two water types is performed by comparing the satellite spectrum with the average water type spectral signature from in situ measurements for both water types. Reference insitu dataset is MedBiOp (Volpe et al., 2019) where pure Case II spectra are selected using a k-mean cluster analysis (Melin et al., 2015). Merging of Case I and Case II information is performed estimating the Mahalanobis distance between the observed and reference spectra and using it as weight for the final merged value. The interpolated gap-free Level-4 Chl concentration is estimated by means of a modified version of the DINEOF algorithm by GOS (Volpe et al., 2018). DINEOF is an iterative procedure in which EOF are used to reconstruct the entire field domain. As first guess, it uses the SeaWiFS-derived daily climatological values at missing pixels and satellite observations at valid pixels. The other Level-4 dataset is the time averages of the L3 fields and includes the standard deviation and the number of observations in the monthly period of integration. '''Processing information:''' Multi-sensor products are constituted by MODIS-AQUA, NOAA20-VIIRS, NPP-VIIRS and Sentinel3A-OLCI. For consistency with NASA L2 dataset, BRDF correction was applied to Sentinel3A-OLCI prior to band shifting and multi sensor merging. Hence, the single sensor OLCI data set is also distributed after BRDF correction. Single sensor NASA Level-2 data are destriped and then all Level-2 data are remapped at 1 km spatial resolution (300m for Sentinel3A-OLCI) using cylindrical equirectangular projection. Afterwards, single sensor Rrs fields are band-shifted, over the SeaWiFS native bands (using the QAAv6 model, Lee et al., 2002) and merged with a technique aimed at smoothing the differences among different sensors. This technique is developed by The Global Ocean Satellite monitoring and marine ecosystem study group (GOS) of the Italian National Research Council (CNR, Rome). Then geophysical fields (i.e. chlorophyll, kd490, bbp, aph and adg) are estimated via state-of-the-art algorithms for better product quality. Level-4 includes both monthly time averages and the daily-interpolated fields. Time averages are computed on the delayed-time data. The interpolated product starts from the L3 products at 1 km resolution. At the first iteration, DINEOF procedure uses, as first guess for each of the missing pixels the relative daily climatological pixel. A procedure to smooth out spurious spatial gradients is applied to the daily merged image (observation and climatology). From the second iteration, the procedure uses, as input for the next one, the field obtained by the EOF calculation, using only a number of modes: that is, at the second round, only the first two modes, at the third only the first three, and so on. At each iteration, the same smoothing procedure is applied between EOF output and initial observations. The procedure stops when the variance explained by the current EOF mode exceeds that of noise. '''Description of observation methods/instruments:''' Ocean colour technique exploits the emerging electromagnetic radiation from the sea surface in different wavelengths. The spectral variability of this signal defines the so-called ocean colour which is affected by the pre+D2sence of phytoplankton. '''Quality / Accuracy / Calibration information:''' A detailed description of the calibration and validation activities performed over this product can be found on the CMEMS web portal. '''Suitability, Expected type of users / uses:''' This product is meant for use for educational purposes and for the managing of the marine safety, marine resources, marine and coastal environment and for climate and seasonal studies. '''Dataset names:''' *dataset-oc-med-chl-multi-l4-chl_1km_monthly-rt-v02 *dataset-oc-med-chl-multi-l4-interp_1km_daily-rt-v02 *dataset-oc-med-chl-olci-l4-chl_300m_monthly-rt-v02 '''Files format:''' *CF-1.4 *INSPIRE compliant '''DOI (product) :''' https://doi.org/10.48670/moi-00113

  • '''Short description:''' For the '''Global''' Ocean '''Satellite Observations''', Brockmann Consult (BC) is providing '''Bio-Geo_Chemical (BGC)''' products based on the ESA-CCI inputs. * Upstreams: SeaWiFS, MODIS, MERIS, VIIRS-SNPP, OLCI-S3A & OLCI-S3B for the '''""multi""''' products. * Variables: Chlorophyll-a ('''CHL'''). * Temporal resolutions: '''monthly'''. * Spatial resolutions: '''4 km''' (multi). * Recent products are organized in datasets called Near Real Time ('''NRT''') and long time-series (from 1997) in datasets called Multi-Years ('''MY'''). To find these products in the catalogue, use the search keyword '''""ESA-CCI""'''. '''DOI (product) :''' https://doi.org/10.48670/moi-00283

  • This dataset stems from the Joint Research Centre (JRC) Biomass Mandate (https://knowledge4policy.ec.europa.eu/projects-activities/jrc-biomass-mandate_en) and it is available for viewing and download on EMODnet - Human Activities web portal (www.emodnet-humanactivities.eu) and on the platform from the European Commission’s Knowledge Centre for Bioeconomy (https://knowledge4policy.ec.europa.eu/visualisation/bioeconomy-different-countries_en#algae_prod_plants). Its aim is to build a reliable database to characterize the algae sector and to support informed European policies on Blue Growth and Bioeconomy. More detailed information on the Status of the Algae Production Industry in Europe can be found in a JRC-led study published in Frontiers in Marine Science (https://publications.jrc.ec.europa.eu/repository/handle/JRC122250). Information on the location (geographic coordinates) of the production facilities, group of produced organism (macroalgae, microalgae and spirulina), production method (Fermenters, Harvesting , Photobioreactors, Open ponds, Semi Open ponds, land-based or at sea Aquaculture, Integrated multi-trophic or not) and species (see dataset) have been collected in the following countries: Austria, Belgium, Bulgaria, Croatia, Czech Republic, Denmark, Estonia, Faroe Islands, France, Germany, Greece, Greenland, Hungary, Iceland, Ireland, Italy, Latvia, the Netherlands, Norway, Portugal, Spain, Sweden, Switzerland and the UK. In November 2021, the JRC has updated the database with the latest information on the production units operational at the time.

  • '''This product has been archived''' For operationnal and online products, please visit https://marine.copernicus.eu '''Short description:''' This product provides analysis-forecast outputs from a wave model for the North-West European Shelf coupled with an ocean model. The wave model is WAVEWATCH III and the North-West Shelf configuration is based on a two-tier Spherical Multiple Cell grid mesh (3 and 1.5 km cells) derived from with the 1.5km grid used for [https://resources.marine.copernicus.eu/?option=com_csw&view=details&product_id=NORTHWESTSHELF_ANALYSIS_FORECAST_PHY_004_013 NORTHWESTSHELF_ANALYSIS_FORECAST_PHY_004_013]. The model is forced by lateral boundary conditions from the Met Office Global wave forecast model. The atmospheric forcing is given by the operational ECMWF Numerical Weather Prediction model and surface current forcing is provided by the North-West Shelf ocean physics analysis and forecast model described in [https://resources.marine.copernicus.eu/?option=com_csw&view=details&product_id=NORTHWESTSHELF_ANALYSIS_FORECAST_PHY_004_013 NORTHWESTSHELF_ANALYSIS_FORECAST_PHY_004_013]. Model outputs comprise wave parameters integrated from the two-dimensional (frequency, direction) wave spectrum and describe wave height, period and directional characteristics for both the overall sea-state and wind-sea and swell components. The data are delivered on a regular grid at approximately 1.5km resolution, consistent with the physical ocean product. See [http://catalogue.marine.copernicus.eu/documents/PUM/CMEMS-NWS-PUM-004-013_014.pdf CMEMS-NWS-PUM-004-013_014] for more information. Further details of the model, including source term physics, propagation schemes, forcing and boundary conditions, and validation, are provided in the [http://catalogue.marine.copernicus.eu/documents/QUID/CMEMS-NWS-QUID-004-014.pdf CMEMS-NWS-QUID-004-014]. '''Associated products:''' The analysis-forecast product from the ocean physics model is: [https://resources.marine.copernicus.eu/?option=com_csw&view=details&product_id=NORTHWESTSHELF_ANALYSIS_FORECAST_PHY_004_013 NORTHWESTSHELF_ANALYSIS_FORECAST_PHY_004_013]. '''DOI (product) :''' https://doi.org/10.48670/moi-00055