Keyword

near-real-time

108 record(s)
 
Type of resources
Available actions
Topics
Keywords
Contact for the resource
Provided by
Years
Formats
Update frequencies
From 1 - 10 / 108
  • '''Short description:''' Global Ocean- in-situ Near Real time Carbon observations. The In Situ Thematic Assembly Centre (INS TAC) integrates near real-time in situ observation data. This Near-Real Time product contains observations of temperature, salinity and fugacity of carbon dioxide from the surface ocean. These data are collected from ICOS Ocean Thematic Centre (https://otc.icos-cp.eu/home) operational stations, using Standard Operating Procedures for the ocean carbon community. The data are quality controlled using the software QuinCe, which provides automatic Quality Control in the form of range checks, constant value and excessive gradient detection. This product is updated with new observations at a maximum frequency of once a day, depending on the connection capabilities of the platform.

  • '''This product has been archived''' For operationnal and online products, please visit https://marine.copernicus.eu '''Short description:''' The Global Ocean Satellite monitoring and marine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 surface chlorophyll concentration (mg m-3) derived from multi-sensor (MODIS-AQUA, NOAA20-VIIRS, NPP-VIIRS, and Sentinel3A-OLCI at 300m of resolution) (at 1 km resolution) and Sentinel3A-OLCI (at high resolution, 300m) Rrs spectra. Chlorophyll datasets are obtained by means of the Mediterranean Ocean Colour 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 at pixel-by-pixel level 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 1 and Case 2 information is performed estimating the Mahalanobis distance between the observed and reference spectra and using it as weight for the final merged value. This product identifies the average chlorophyll content of the surface layer as defined by the first optical depth (roughly one fifth of the euphotic depth). For multi-sensor observations, 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. The current day data temporal consistency is evaluated as Quality Index (QI): QI=(CurrentDataPixel-ClimatologyDataPixel)/STDDataPixel where QI is the difference between current data and the relevant climatological field as a signed multiple of climatological standard deviations (STDDataPixel). '''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 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. '''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 presence 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-l3-chl_1km_daily-rt-v02 *dataset-oc-med-chl-olci-l3-chl_300m_daily-rt-v02 '''Files format:''' *CF-1.4 *INSPIRE compliant '''DOI (product) :''' https://doi.org/10.48670/moi-00111

  • '''Short description:''' For the Atlantic Ocean - The product contains daily Level-3 sea surface wind with a 1km horizontal pixel spacing using Near Real-Time Synthetic Aperture Radar (SAR) observations and their collocated European Centre for Medium-Range Weather Forecasts (ECMWF) model outputs. Products are updated several times daily to provide the best product timeliness. '''DOI (product) :''' https://doi.org/10.48670/mds-00331

  • '''Short description:''' This product provides daily (nighttime), merged multi-sensor (Level-3S, L3S) maps of foundation Sea Surface Temperature (SST) - that is, the SST free from diurnal warming - over the Mediterranean Sea, at high (HR, 1/16°) and ultra-high (UHR, 1/100°) spatial resolutions, covering the period from 2008 to present. Each map represents nighttime SST values and is produced by the Italian National Research Council – Institute of Marine Sciences (CNR-ISMAR). L3S maps are generated by selecting only the highest-quality SST observations from upstream Level-2 (L2) data acquired within a short local nighttime window, in order to minimize cloud contamination and avoid the effects of the diurnal cycle. The main L2 sources currently ingested include SLSTR from Sentinel-3A and -3B, VIIRS from NOAA-21, NOAA-20, and Suomi-NPP, AVHRR from Metop-B and -C, and SEVIRI. These L3S data serve as input to an optimal interpolation procedure used to generate gap-free Level-4 (L4) SST fields, as implemented in product 010_004 (Buongiorno Nardelli et al., 2013). '''DOI (product) :''' https://doi.org/10.48670/moi-00171

  • ''' Short description: ''' For the Mediterranean Sea - the CNR diurnal sub-skin Sea Surface Temperature (SST) product provides daily gap-free (L4) maps of hourly mean sub-skin SST at 1/16° (0.0625°) horizontal resolution over the CMEMS Mediterranean Sea (MED) domain, by combining infrared satellite and model data (Marullo et al., 2014). The implementation of this product takes advantage of the consolidated operational SST processing chains that provide daily mean SST fields over the same basin (Buongiorno Nardelli et al., 2013). The sub-skin temperature is the temperature at the base of the thermal skin layer and it is equivalent to the foundation SST at night, but during daytime it can be significantly different under favorable (clear sky and low wind) diurnal warming conditions. The sub-skin SST L4 product is created by combining geostationary satellite observations aquired from SEVIRI and model data (used as first-guess) aquired from the CMEMS MED Monitoring Forecasting Center (MFC). This approach takes advantage of geostationary satellite observations as the input signal source to produce hourly gap-free SST fields using model analyses as first-guess. The resulting SST anomaly field (satellite-model) is free, or nearly free, of any diurnal cycle, thus allowing to interpolate SST anomalies using satellite data acquired at different times of the day (Marullo et al., 2014). [https://help.marine.copernicus.eu/en/articles/4444611-how-to-cite-or-reference-copernicus-marine-products-and-services How to cite] '''DOI (product) :''' https://doi.org/10.48670/moi-00170

  • '''This product has been archived''' For operationnal and online products, please visit https://marine.copernicus.eu '''Short description:''' For the Global Ocean- Gridded objective analysis fields of temperature and salinity using profiles from the in-situ near real time database are produced monthly. Objective analysis is based on a statistical estimation method that allows presenting a synthesis and a validation of the dataset, providing a support for localized experience (cruises), providing a validation source for operational models, observing seasonal cycle and inter-annual variability. '''DOI (product) :''' https://doi.org/10.48670/moi-00037

  • '''Short description:''' For the NWS/IBI Ocean- Sea Surface Temperature L3 Observations . This product provides daily foundation sea surface temperature from multiple satellite sources. The data are intercalibrated. This product consists in a fusion of sea surface temperature observations from multiple satellite sensors, daily, over a 0.02° resolution grid. It includes observations by polar orbiting and geostationary satellites . The L3S SST data are produced selecting only the highest quality input data from input L2P/L3P images within a strict temporal window (local nightime), to avoid diurnal cycle and cloud contamination. The observations of each sensor are intercalibrated prior to merging using a bias correction based on a multi-sensor median reference correcting the large-scale cross-sensor biases. 3 more datasets are available that only contain "per sensor type" data : Polar InfraRed (PIR), Polar MicroWave (PMW), Geostationary InfraRed (GIR) '''DOI (product) :''' https://doi.org/10.48670/moi-00310

  • '''This product has been archived''' For operational and online products, please visit https://marine.copernicus.eu '''Short description:''' For the '''North Atlantic''' Ocean '''Satellite Observations''', Plymouth Marine Laboratory (PML) is providing '''Bio-Geo_Chemical (BGC)''' products based on the ESA-CCI reflectance inputs. * Upstreams: SeaWiFS, MODIS, MERIS, VIIRS-SNPP, OLCI-S3A & OLCI-S3B for the '''""multi""''' products, and S3A & S3B only for the '''""olci""''' products. * Variables: Chlorophyll-a ('''CHL''') and Diffuse Attenuation ('''KD490'''). * Temporal resolutions:'''monthly'''. * Spatial resolutions: '''1 km''' (multi) or '''300 meters''' (olci). * 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-00285

  • '''Short description:''' For the Atlantic Ocean - The product contains daily Level-3 sea surface wind with a 1km horizontal pixel spacing using Synthetic Aperture Radar (SAR) observations and their collocated European Centre for Medium-Range Weather Forecasts (ECMWF) model outputs. Products are processed homogeneously starting from the L2OCN products. '''DOI (product) :''' https://doi.org/10.48670/mds-00339

  • '''Short description:''' For the Mediterranean Sea - The product contains daily Level-3 sea surface wind with a 1km horizontal pixel spacing using Near Real-Time Synthetic Aperture Radar (SAR) observations and their collocated European Centre for Medium-Range Weather Forecasts (ECMWF) model outputs. Products are updated several times daily to provide the best product timeliness. '''DOI (product) :''' https://doi.org/10.48670/mds-00334