• Title of article

    Validation and potential applications of Environment Canada Ice Concentration Extractor (ECICE) algorithm to Arctic ice by combining AMSR-E and QuikSCAT observations

  • Author/Authors

    Shokr، نويسنده , , Mohammed and Agnew، نويسنده , , Thomas A.، نويسنده ,

  • Issue Information
    روزنامه با شماره پیاپی سال 2013
  • Pages
    18
  • From page
    315
  • To page
    332
  • Abstract
    The Environment Canadaʹs Ice Concentration Extractor (ECICE) combines observations from several different satellite sensors to resolve heterogeneous components of a given footprint. To validate the algorithm and demonstrate its applicability, results are presented from combining the enhanced AMSR-E 36.5 GHz passive microwave data with dual-polarization QuikSCAT active microwave scatterometer observations of Arctic ice during September to May; 2007/08. Validation is performed using comparison with results from other algorithms in addition to operational ice charts. Three ice types are resolved: young, first-year and multiyear. Total ice concentration from ECICE under cold Arctic winter conditions is in agreement with estimates from previous algorithms such as the enhanced NASA Team. Distribution of multiyear ice concentration from ECICE is presented along with evolution of daily concentration of each ice type. Events of melt-refreeze, which are common during seasonal transition periods, cause misidentification of multiyear ice as first-year ice in the fall. The reverse is observed in the spring. This is a limitation on ice type identification. ECICE is an optimal approach that minimizes the error between observations and predicted concentrations. It provides a confidence measure associated with each ice concentration estimate. It is a generic algorithm, i.e. its applications are not limited to AMSR-E and QuikSCAT.
  • Keywords
    QuikSCAT , Multiyear ice , AMSR-E , sea ice , Ice concentration , Retrieval algorithms , Arctic ice
  • Journal title
    Remote Sensing of Environment
  • Serial Year
    2013
  • Journal title
    Remote Sensing of Environment
  • Record number

    1632863