• DocumentCode
    2336417
  • Title

    The application of statistical computation for fitting the global sea temperature

  • Author

    Wang, Xiaoying ; Jiang, Song ; Yin, Junping

  • Author_Institution
    North China Electr. Power Univ., Beijing, China
  • fYear
    2012
  • fDate
    3-5 June 2012
  • Firstpage
    204
  • Lastpage
    207
  • Abstract
    We present the statistical fittings for global sea temperatures using the data of the World Ocean Atlas (WOA). We have gridded fittings for annual, monthly, and seasonal means of temperatures on standard levels (typically at 33 depths). To decrease bias, we apply the statistical regression models which combine the high-order polynomials with the mutually orthogonal polynomials. The comparison of the fitted results with the data of WOA are given, which demonstrate the accurateness of the fitted results.
  • Keywords
    geophysics computing; ocean temperature; regression analysis; WOA data; World Ocean Atlas data; global sea temperature fitting; high order polynomial; mutually orthogonal polynomial; statistical computation; statistical regression model; Fitting; Meteorology; Ocean temperature; Polynomials; Temperature distribution; Temperature measurement; Statistical fitting; multivariate regression models; mutually orthogonal polynomials; sea temperature;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Robotics and Applications (ISRA), 2012 IEEE Symposium on
  • Conference_Location
    Kuala Lumpur
  • Print_ISBN
    978-1-4673-2205-8
  • Type

    conf

  • DOI
    10.1109/ISRA.2012.6219159
  • Filename
    6219159