The Evolutionary Modeling and Short-range Climatic Prediction for Meteorological Element Time Series
The time series of precipitation in flood season (May-September) at Wuhan Station, which is set as an example of the kind of time series with chaos characters, is split into two parts: One includes macro climatic timescale period waves that are affected by some relatively steady climatic factors such as astronomical factors (sunspot, etc.), some other known and/or unknown factors, and the other includes micro climatic timescale period waves superimposed on the macro one. The evolutionary modeling (EM), which develops from genetic programming (GP), is supposed to be adept at simulating the former part because it creates the nonlinear ordinary differential equation (NODE) based upon the data series. The natural fractals (NF)are used to simulate the latter part. The final prediction is the sum of results from both methods, thus the model can reflect multi-time scale effects of forcing factors in the climate system. The results of this example for 2002 and 2003 are satisfactory for climatic prediction operation. The NODE can suggest that the data vary with time, which is beneficial to think over short-range climatic analysis and prediction. Comparison in principle between evolutionary modeling and linear modeling indicates that the evolutionary one is a better way to simulate the complex time series with nonlinear characteristics.
作 者： YU Kangqing ZHOU Yuehua YANG Jing'an KANG Zhuo 作者单位： YU Kangqing,ZHOU Yuehua,YANG Jing'an(Institute of Heavy Rain, China Meteorological Administration, Wuhan 430074)KANG Zhuo(Computation Center, Wuhan University, Wuhan 430072)
刊 名： 气象学报（英文版） SCI 英文刊名： ACTA METEOROLOGICA SINICA 年，卷(期)： 2005 19(3) 分类号： P4 关键词： time series evolutionary modeling short-range climatic prediction