A Medium/Long-Range Forecast of Pacific Subtropical High Based on Dynamic Statistic Model Reconstruction

作     者：洪梅 张韧 刘科峰 余丹丹 

作者机构：Institute of MeteorologyPLA University of Science and TechnologyNanjing 211101 LASGInstitute of Atmospheric PhysicsChinese Academy of SciencesBeijing 100029 Institute of MeteorologyPLA University of Science and TechnologyNanjing 211101 

出 版 物：《Acta meteorologica Sinica》 (Acta Meteorol. Sin.)

年 卷 期：2007年第21卷第3期

页      面：376-384页

核心收录：

学科分类：07[理学] 070601[理学-气象学] 0706[理学-大气科学] 

基　　金：the National Natural Science Foundation of China(40375019) the Tropical Marine and Meteorological Science Foundation(200609) 

主　　题：dynamical statistic model reconstruction genetic algorithm empirical orthogonal function (EOF) subtropical high forecast 

摘      要：Based on the 500-hPa geopotential height field series of T106 numerical forecast products, by empirical orthogonal function （EOF） time-space separation, and on the hypotheses of EOF space-models being stable, the EOF time coefficient series were taken as dynamical statistic model variables. The dynamic system reconstruction idea and genetic algorithm were introduced to make the dynamical model parameters optimized, and a nonlinear dynamic statistic model of EOF separating time coefficient series was established. By the model time integral and EOF time-space reconstruction, a medium/long-range forecast of subtropical high was carried out. The results show that the dynamical model forecast and T106 numerical forecast were approximately similar in the short-range forecast （≤5 days）, but in the medium/long-range forecast （≥5 days）, the forecast results of dynamical model was superior to that of T106 numerical products. A new method and idea were presented for diagnosing and forecasting complicated weathers such as subtropical high, and showed a better application outlook.