• Title of article

    High and Ultra-High resolution processing of satellite Sea Surface Temperature data over Southern European Seas in the framework of MyOcean project

  • Author/Authors

    M Buongiorno Nardelli، نويسنده , , B. and Tronconi، نويسنده , , C. and Pisano، نويسنده , , A. and Santoleri، نويسنده , , R.، نويسنده ,

  • Issue Information
    روزنامه با شماره پیاپی سال 2013
  • Pages
    16
  • From page
    1
  • To page
    16
  • Abstract
    In the framework of the GMES (Global Monitoring for Environment and Security) MyOcean projects, funded by the European Commission, different remotely-sensed Sea Surface Temperature (SST) supercollated (L3S) and interpolated (L4) data are produced and distributed in near-real time by the Consiglio Nazionale delle Ricerche – Istituto di Scienze dellʹAtmosfera e del Clima – Gruppo di Oceanografia da Satellite (CNR). These SST products are based on the night-time images collected by the infrared sensors mounted on different satellite platforms and cover the whole Southern European Seas (i.e. the Mediterranean Sea, including the eastern Atlantic Ocean, and the Black Sea). The CNR processing chains include several modules, from the data extraction and preliminary quality control, to cloudy pixel removal and satellite images collating/merging up to L3S. A two-step algorithm finally allows to interpolate SST data at High (HR 1/16°) and Ultra-High (UHR 1/100°) spatial resolution. The basic design and the main algorithms used in MyOcean processing chains are described hereafter. A validation of the HR super-collating procedure developed during MyOcean is presented. The Mediterranean HR and UHR L3S and L4 operational products have then been validated vs in situ SST measurements from drifting buoys, covering two years of data (2010–2011). The validation includes a comparison between the UHR CNR L4 and the G1SST L4 developed by Chao et al. (2009).
  • Keywords
    Optimal interpolation , sea surface temperature , Operational oceanography
  • Journal title
    Remote Sensing of Environment
  • Serial Year
    2013
  • Journal title
    Remote Sensing of Environment
  • Record number

    1632866