|
| A PREDICTION EXPERIMENT BY USING THE GENERALIZED CANONICAL MIXED REGRESSION MODEL BASED ON MSSA-SVD FOR ENSO |
| Received:August 22, 2000 Revised:December 24, 2001 |
| View Full Text View/Add Comment Download reader |
| KeyWord:Multichannel singular spectrum analysis;Canonical mixed regression model;ENSO prediction |
| Author Name | Affiliation | | Ding Yuguo | Nanjing Institute of Meteorology, Nanjing 210044 | | Cheng Zhengquan | Nanjing Institute of Meteorology, Nanjing 210044 | | Cheng Bingyan | Henan Climatic Center, Zhengzhou 450003 |
|
| Hits: 2740 |
| Download times: 2903 |
| Abstract: |
| A generalized Canonical Mixed Regression Model based on MSSA-SVD is presened to prediction of ENSO. The MSSA is a Multichannel Singular Spectrum Analysis and the SVD is Singular Value Decomposation. The basisc idea of the method is that (1) the prominent coupled oscillation signals are segregated between the forecasted fields and the forecastor fields by using MSSA-SVD method; (2) the generalized Canonical Mixed Regression Model is constructed according to the first several prominent coupled oscillation patterns for ENSO prediction. The results of statistical forecast test based on the MSSA-SVD method show that the predictional model possesses more advantages and better effects than other statistical prediction methods. |