-In this paper, the maximum entropy spectral, the cross-spectral and the frequency response analyses are madeon the basis of the data of monthly mean sea levels at coastal stations in the Bohai Sea during 1965-1986. T...-In this paper, the maximum entropy spectral, the cross-spectral and the frequency response analyses are madeon the basis of the data of monthly mean sea levels at coastal stations in the Bohai Sea during 1965-1986. The results show that the annual fluctuations of the monthly mean sea levels in the Bohai Sea are the results of the coupling response of seasonal variations of the marine hydrometeorological factors. Furthermore, the regression prediction equation is obtained by using the double screening stepwise regression analysis method . Through the prediction test , it is proved that the obtained results are desirable.展开更多
This paper summarizes the general methods,existing problems and their causes of the period analysis for the monthly mean sea level and points out that it is the key to the analysing period signals and forecasting the ...This paper summarizes the general methods,existing problems and their causes of the period analysis for the monthly mean sea level and points out that it is the key to the analysing period signals and forecasting the change trend of the monthly mean sea level that the periods of the signals are selected reasonably. As there are often many period signals in these series, nonlinear effects exist between pairs of period signals. In order to avoid the false periods that may be introduced due to the effects of side lobes and the periods with statistical phase significance coherence that may be introduced due to the effects of nonlinear effects and their restraint to other period signals, the maximum entropy spectral analysis and the corresponding significance period test may be performed repeatedly on the basis of the bispectrum analysis and meanwhile the most significant period component is filtered out by the least square filtering method, i. e., the method of the significance period analysis with mixed spectra modeled by a nonlinear system is adopted and the signal periods approaching the reality are selected one by one. The examples of the bispectrum analysis, the signal period analysis by mixed spectra and the fitting parameters for combined period components with linear trend in the time series of monthly mean sea level are given in this paper.展开更多
Monthly changes of sea level recorded on the seas adjacent to Korea (the Huanghai Sea, the East ChinaSea and the East As) are investigated. The major influences on the spatial and temporal variation of mean sea level ...Monthly changes of sea level recorded on the seas adjacent to Korea (the Huanghai Sea, the East ChinaSea and the East As) are investigated. The major influences on the spatial and temporal variation of mean sea level arequantitatively identified. A set of modes of monthly air pressure variation over the Huanghai Sea, East China Sea andEast Sea for the period of 1978-1992 is obtained. Each monthly air pressure distribution can be precisely defined bylinear combination of these modes. Hence, the set of air pressure series can be replaced by a set of time varying coefficents, where each coefficient describes the contribution of a particular mode to a given air pressure distribution. A selected set of the modal coefficients is then added to a multiple Fegresion model, consisting of a trend, monthly wind stress and tidal term, in an attempt to represent the effect of meteorological variations on monthly mean sea level on the seas adjacent to Korea. It is found that although the model may account for over 90% of the observed mean sea level variance, there still remains a high correlation between the residuals, hence identifying a regional variation for further study.展开更多
文摘-In this paper, the maximum entropy spectral, the cross-spectral and the frequency response analyses are madeon the basis of the data of monthly mean sea levels at coastal stations in the Bohai Sea during 1965-1986. The results show that the annual fluctuations of the monthly mean sea levels in the Bohai Sea are the results of the coupling response of seasonal variations of the marine hydrometeorological factors. Furthermore, the regression prediction equation is obtained by using the double screening stepwise regression analysis method . Through the prediction test , it is proved that the obtained results are desirable.
文摘This paper summarizes the general methods,existing problems and their causes of the period analysis for the monthly mean sea level and points out that it is the key to the analysing period signals and forecasting the change trend of the monthly mean sea level that the periods of the signals are selected reasonably. As there are often many period signals in these series, nonlinear effects exist between pairs of period signals. In order to avoid the false periods that may be introduced due to the effects of side lobes and the periods with statistical phase significance coherence that may be introduced due to the effects of nonlinear effects and their restraint to other period signals, the maximum entropy spectral analysis and the corresponding significance period test may be performed repeatedly on the basis of the bispectrum analysis and meanwhile the most significant period component is filtered out by the least square filtering method, i. e., the method of the significance period analysis with mixed spectra modeled by a nonlinear system is adopted and the signal periods approaching the reality are selected one by one. The examples of the bispectrum analysis, the signal period analysis by mixed spectra and the fitting parameters for combined period components with linear trend in the time series of monthly mean sea level are given in this paper.
文摘Monthly changes of sea level recorded on the seas adjacent to Korea (the Huanghai Sea, the East ChinaSea and the East As) are investigated. The major influences on the spatial and temporal variation of mean sea level arequantitatively identified. A set of modes of monthly air pressure variation over the Huanghai Sea, East China Sea andEast Sea for the period of 1978-1992 is obtained. Each monthly air pressure distribution can be precisely defined bylinear combination of these modes. Hence, the set of air pressure series can be replaced by a set of time varying coefficents, where each coefficient describes the contribution of a particular mode to a given air pressure distribution. A selected set of the modal coefficients is then added to a multiple Fegresion model, consisting of a trend, monthly wind stress and tidal term, in an attempt to represent the effect of meteorological variations on monthly mean sea level on the seas adjacent to Korea. It is found that although the model may account for over 90% of the observed mean sea level variance, there still remains a high correlation between the residuals, hence identifying a regional variation for further study.