论文部分内容阅读
To investigate the annual and interannual variability of ocean surface wind over the South China Sea(SCS), the vector empirical orthogonal function(VEOF) method and the Hilbert-Huang transform(HHT) method were employed to analyze a set of combined satellite scatterometer wind data during the period from December 1992 to October 2009. The merged wind data were generated from European Remote Sensing Satellite(ERS)-1/2 Scatterometer, NASA Scatterometer(NSCAT) and NASA’s Quick Scatterometer(QuikSCAT) wind products. The first VEOF mode corresponds to a winter-summer mode which accounts for 87.3% of the total variance and represents the East Asian monsoon features. The second mode of VEOF corresponds to a spring-autumn oscillation which accounts for 8.3% of the total variance. To analyze the interannual variability, the annual signal was removed from the wind data set and the VEOFs of the residuals were calculated. The temporal mode of the first interannual VEOF is correlated with the Southern Oscillation Index(SOI) with a four-month lag. The second temporal interannual VEOF mode is correlated with the SOI with no time lag. The time series of the two interannual VEOFs were decomposed using the HHT method and the results also show a correlation between the interannual variability and El Ni?o-Southern Oscillation(ENSO) events.
To investigate the annual and interannual variability of ocean surface wind over the South China Sea (SCS), the vector empirical orthogonal function (VEOF) method and the Hilbert-Huang transform (HHT) method were employed to analyze a set of combined satellite scatterometer wind data from the period from December 1992 to October 2009. The merged wind data were generated from the European Remote Sensing Satellite (ERS) -1/2 Scatterometer, NASA Scatterometer (NSCAT) and NASA’s Quick Scatterometer (QuikSCAT) wind products. The first VEOF mode corresponds to a winter-summer mode which accounts for 87.3% of the total variance and represents the East Asian monsoon features. The second mode of VEOF corresponds to a spring-autumn oscillation which accounts for 8.3% of the total variance. To analyze the interannual variability, the annual signal was removed from the wind data set and the VEOFs of the residuals were calculated. The temporal mode of the first interannual VEOF is correlated with the Southe The time series of the two interannual VEOFs were decomposed using the HHT method and the results also show a correlation between the interannual variability and El Niño-Southern Oscillation (ENSO) events.