Keyword

/Observational data/satellite

80 record(s)
 
Type of resources
Available actions
Topics
Keywords
Contact for the resource
Provided by
Years
Formats
Representation types
Update frequencies
status
Scale
Resolution
From 1 - 10 / 80
  • These gridded products are produced from the following upstream data: - for satellites SARAL/AltiKa, Cryosat-2, HaiYang-2B, Jason-3, Copernicus Sentinel-3A&B, Sentinel 6A, SWOT Nadir => NRT (Near-Real-Time) Nadir along-track (or Level-3) SEA LEVEL products (DOI: https://doi.org/10.48670/moi-00147) delivered by the Copernicus Marine Service (CMEMS, http://marine.copernicus.eu/ ). The gridded product is based on NRT L3 Nadir datasets for the period from July 1, 2024, to December 31, 2024. => MY (Multi-Year) Nadir along-track (or Level-3) SEA LEVEL products (DOI: https://doi.org/10.48670/moi-00146 ) delivered by the Copernicus Marine Service (CMEMS, http://marine.copernicus.eu/ ). The gridded product is based on MY L3 Nadir datasets for the period from March 28, 2023, to June 30, 2024. - for SWOT KaRIn : the SEA LEVEL products L3_LR_SSH (V2.0.1) delivered by AVISO for Expert SWOT L3 SSH KaRin (DOI: https://doi.org/10.24400/527896/A01-2023.018) for the period from March 28, 2023 to December 31, 2024. One mapping algorithm is proposed: the MIOST approach which give the global SSH solutions: the MIOST method is able of accounting for various modes of variability of the ocean surface topography (e.g., geostrophic, barotrope, equatorial waves dynamic …) by constructing several independent components within an assumed covariance model.

  • Archive de toutes les données de température de surface (SST) satellite produites dans le cadre du projet international GHRSST. Ifremer est un GDAC pour ces données, miroir du GDAC NASA/JPL. Ces données sont utilisées pour la génération de produits multi-capteurs (CMEMS, Medspiration) mais également dans le cadre d'un grand nombre d'études ou projets nécessitant l'utilisation de mesures de SST. L'archive regroupe plusieurs jeux de données provenant de différents satellite ainsi que des données in situ de référence pour leur validation. Elle est mise à jour en temps quasi-réel depuis 10 ans, avec service de diffusion opérationnelle associé (FTP et HTTP). Une fiche sextant (issue du catalogue CERSAT) sera fournie pour chaque dataset dans cette archive.

  • 387 points were surveyed with a SP80 DGPS by Maxime Paschal as part of the La Rochelle Zero Carbon Territory (LRTZC) project on 26/05/23. At each point, the type of vegetation was specified.

  • The ESA Sea State Climate Change Initiative (CCI) project has produced global multi-sensor time-series of along-track satellite altimeter significant wave height data (referred to as Level 4 (L4) data) with a particular focus for use in climate studies. This dataset contains the Version 3 Remote Sensing Significant Wave Height product, gridded over a global regular cylindrical projection (1°x1° resolution), averaging valid and good measurements from all available altimeters on a monthly basis (using the L2P products also available). These L4 products are meant for statistics and visualization. The altimeter data used in the Sea State CCI dataset v3 come from multiple satellite missions spanning from 2002 to 2021 ( 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).

  • This dataset provides the meridional and zonal components of both the stress-equivalent wind (U10S) and wind stress (Tau) vectors. The ERA* product is a correction of the ECMWF Fifth Reanalysis (ERA5) output by means of geo-located scatterometer-ERA5 differences over a 15-day temporal window. The product also contains ERA5 U10S and Tau. 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 ICM (Institute of Marine Sciences) / CSIC (Consejo Superior de Investigaciones Científicas) 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 provide a times series of daily mean fields of Sea Surface Temperature (SST) foundation at high resolution (UHR) on a 0.10 x 0.10 degree grid (approximately 10 x 10 km) for the Global Ocean, every 24 hours. An Optimal interpolation (OI) technique is used to combine coincident swath measures of SST from different types satellite sensors and to fill gaps where no observations are available or obstructed by clouds. This multi-sensor compositing and interpolation process categorizes this dataset as a Level 4 product. Each daily mean field is available the next day before 12:00. Whereas along swath observation data essentially represent the skin or sub-skin SST, the L4 SST product is defined to represent the SST foundation (SSTfnd). SSTfnd is defined within GHRSST-PP as the temperature at the base of the diurnal thermocline. It is so named because it represents the foundation temperature on which the diurnal thermocline develops during the day. SSTfnd changes only gradually along with the upper layer of the ocean, and by definition it is independent of skin SST fluctuations due to wind- and radiation-dependent diurnal stratification or skin layer response. It is therefore updated at intervals of 24 hrs. SSTfnd corresponds to the temperature of the upper mixed layer which is the part of the ocean represented by the top-most layer of grid cells in most numerical ocean models. It is never observed directly by satellites, but it comes closest to being detected by infrared and microwave radiometers during the night, when the previous day's diurnal stratification can be assumed to have decayed. The processing combines the observations of multiple polar orbiting and geostationary satellites, embedding infrared of microwave radiometers. All these sources are intercalibrated with eachother before merging. This dataset is generated daily within a 24 delay and is therefore suitable for assimilation into operational models. It is produced in the frame of Copernicus Marine Service and the data available through various tools and protocols with a simple user registration from this service (product identifier: SST_GLO_PHY_L4_NRT_010_043) at: https://data.marine.copernicus.eu/product/SST_GLO_PHY_L4_NRT_010_043

  • These gridded products are produced from the along-track (or Level-3) SEA LEVEL products (DOI: doi.org/10.48670/moi-00147) delivered by the Copernicus Marine Service (CMEMS, marine.copernicus.eu) for satellites SARAL/AltiKa, Cryosat-2, HaiYang-2B, Jason-3, Copernicus Sentinel-3A/B, Sentinel-6 MF, SWOT nadir, and SWOT Level-3 KaRIn sea level products (DOI: https://doi.org/10.24400/527896/A01-2023.018). Three mapping algorithms are proposed: MIOST, 4DvarNET, 4DvarQG: - the MIOST approach which give the global SSH solutions: the MIOST method is able of accounting for various modes of variability of the ocean surface topography (e.g., geostrophic, barotrope, equatorial waves dynamic …) by constructing several independent components within an assumed covariance model. - the 4DvarNET approach for the regional SSH solutions: the 4DvarNET mapping algorithm is a data-driven approach combining a data assimilation scheme associated with a deep learning framework. - the 4DvarQG approach for the regional SSH solutions: the 4DvarQG mapping technique integrates a 4-Dimensional variational (4DVAR) scheme with a Quasi-Geostrophic (QG) model.

  • This dataset provide a times series of daily multi-sensor composite fields of Sea Surface Temperature (SST) foundation at ultra-high resolution (HR) on a 0.02 x 0.02 degree grid (approximately 2 x 2 km) for the North East Atlantic, every 24 hours. An Optimal interpolation (OI) technique is used to combine coincident swath measures of SST from different types satellite sensors and to fill gaps where no observations are available or obstructed by clouds. This multi-sensor compositing and interpolation process categorizes this dataset as a Level 4 product. Each daily mean field is available the next day before 12:00. Whereas along swath observation data essentially represent the skin or sub-skin SST, the L3S SST product is defined to represent the SST foundation (SSTfnd). SSTfnd is defined within GHRSST as the temperature at the base of the diurnal thermocline. It is so named because it represents the foundation temperature on which the diurnal thermocline develops during the day. SSTfnd changes only gradually along with the upper layer of the ocean, and by definition it is independent of skin SST fluctuations due to wind- and radiation-dependent diurnal stratification or skin layer response. It is therefore updated at intervals of 24 hrs. SSTfnd corresponds to the temperature of the upper mixed layer which is the part of the ocean represented by the top-most layer of grid cells in most numerical ocean models. It is never observed directly by satellites, but it comes closest to being detected by infrared and microwave radiometers during the night, when the previous day's diurnal stratification can be assumed to have decayed. The processing combines the observations of multiple polar orbiting and geostationary satellites, embedding infrared of microwave radiometers. All these sources are intercalibrated with eachother before merging. This dataset is generated daily within a 24 delay and is therefore suitable for assimilation into operational models. It is produced in the frame of Copernicus Marine Service and the data available through various tools and protocols with a simple user registration from this service (product identifier: SST_ATL_SST_L4_NRT_OBSERVATIONS_010_025) at: https://data.marine.copernicus.eu/product/SST_ATL_SST_L4_NRT_OBSERVATIONS_010_025/

  • Data record (2004-2012) of level 3 hourly sub-skin Sea Surface Temperature derived from Meteosat at 0° longitude, covering 60S-60N and 60W-60E and re-projected on a 0.05° regular grid, in GHRSST compliant netCDF format. The satellite input data come from the imager SEVIRI on MSG satellites (Meteosat-8 and Meteosat-9). SST is retrieved from SEVIRI infrared channels (10.8 and 12.0 µm) using a multispectral algorithm and the cloud mask from CM SAF. NWP outputs (temperature and humidity profiles), OSTIA Sea Surface Temperature re-analysis and analysis, together with a radiative transfer model (RTTOV), are used to correct the multispectral algorithm for regional and seasonal biases due to changing atmospheric conditions. The product format is compliant with the GHRSST Data Specification (GDS) version 2. Users are advised to use data only with quality levels 3,4 and 5.

  • The ESA Sea State Climate Change Initiative (CCI) project has produced global multi-sensor time-series of along-track satellite altimeter significant wave height data (referred to as Level 2P (L2P) 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, separated per satellite and pass, including all measurements with flags, corrections and extra parameters from other sources. These are expert products with rich content and no data loss. The altimeter data used in the Sea State CCI dataset v3 come from multiple satellite missions spanning from 2002 to 2022021 (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).