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
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;
Conference_Titel :
Robotics and Applications (ISRA), 2012 IEEE Symposium on
Conference_Location :
Kuala Lumpur
Print_ISBN :
978-1-4673-2205-8
DOI :
10.1109/ISRA.2012.6219159