摘要
Focusing on common and significant forecast errorsthe zonal mean errors in the numerical prediction model, this report proposes an approach to improving the dynamical extended-range (monthly) prediction. Firstly, the monthly pentad-mean nonlinear dynamical regional predic-tion model of the zonal-mean height based on a large num-ber of historical data is constituted by employing the recon-struction phase space theory and the spatio-temporal series predictive method. The zonal height thus produced is trans-formed to its counterpart in the numerical model and fur-ther used to revise the numerical model prediction during the integration process. In this way, the two different kinds of prediction are combined. The forecasting experimenal results show that the above hybrid approach not only re-duces the systematical error of the numerical model, but also improves the forecast of the non-axisymmetric components due to the wave-flow interaction.
Focusing on common and significant forecast errorsthe zonal mean errors in the numerical prediction model, this report proposes an approach to improving the dynamical extended-range (monthly) prediction. Firstly, the monthly pentad-mean nonlinear dynamical regional predic-tion model of the zonal-mean height based on a large num-ber of historical data is constituted by employing the recon-struction phase space theory and the spatio-temporal series predictive method. The zonal height thus produced is trans-formed to its counterpart in the numerical model and fur-ther used to revise the numerical model prediction during the integration process. In this way, the two different kinds of prediction are combined. The forecasting experimenal results show that the above hybrid approach not only re-duces the systematical error of the numerical model, but also improves the forecast of the non-axisymmetric components due to the wave-flow interaction.
基金
supported by the National Key Project for Development of Science and Technology(Grant No.96-908-02)
by the National Natural Science Foundation of China(Grant No.40175013)
partly by the Project of Chinese Academy of Sciences(Grant No.ZKCX2-SW-210).
关键词
天气预报
动态广义范围预报
非线性区域预测
每月预报
预报方法
dynamical extended-range prediction, zonal-mean com-ponent, nonlinear regional prediction, nudging.
