NON-LINEAR DYNAMIC MODEL RETRIEVAL OF SUBTROPICAL HIGH BASED ON EMPIRICAL ORTHOGONAL FUNCTION AND GENETIC ALGORITHM

• Published in: Applied mathematics and mechanics Vol. 27; no. 12; pp. 1645 - 1653
• Main Author: 张韧 洪梅 孙照渤 牛生杰 朱伟军 闵锦忠 万齐林
• Format: Journal Article
• Language: English
• Published: Nanjing University of Information Science & Technology,KLME, Nanjing,210044,P. R. China 01.12.2006; Institute of Tropical and Marine Meteorology,CMA,Guangzhou,510080,P. R. Chna%Institute of Meteorology, PLA University of Science and Technology,Nanjing,211101, P. R. China%Nanjing University of Information Science & Technology,KLME, Nanjing,210044, P. R. China%Institute of Tropical and Marine Meteorology, CMA, Guangzhou,510080, P. R. China; Institute of Meteorology,PLA University of Science and Technology,Nanjing,211101,P.R.China
• Subjects: Dynamic models; Dynamical systems; Genetic algorithms; Mathematical analysis; Mathematical models; Nonlinear dynamics; Orthogonal functions; Retrieval; 亚热带; 大气动力学; 遗传算法; 非线形动力模型; genetic algorithm; subtropical high; empirical orthogonal function; non-linear model retrieval
• ISSN: 0253-4827; 1573-2754
• DOI: 10.1007/s10483-006-1207-z

Aiming at the difficulty of accurately constructing the dynamic model of subtropical high, based on the potential height field time series over 500 hPa layer of T106 numerical forecast products, by using EOF（empirical orthogonal function） temporal-spatial separation technique, the disassembled EOF time coefficients series were regarded as dynamical model variables, and dynamic system retrieval idea as well as genetic algorithm were introduced to make dynamical model parameters optimization search, then, a reasonable non-linear dynamic model of EOF time-coefficients was established. By dynamic model integral and EOF temporal-spatial components assembly, a mid-/long-term forecast of subtropical high was carried out. The experimental results show that the forecast results of dynamic model are superior to that of general numerical model forecast results. A new modeling idea and forecast technique is presented for diagnosing and forecasting such complicated weathers as subtropical high.