摘要
基于NCEP/NCAR再分析资料和COADS海洋资料中的全球月平均海平面气压场、850hPa纬向风场及海表温度场 ,利用Matlab中的NeuralNetworkToolbox仿真环境和BP模型改进算法比较准确地仿真和反演出了南方涛动指数、赤道纬向风指数和滞后的赤道东太平洋海温之间的动力结构和预报模型。该模型具有很好的拟合精度和可行的预报效果 ,可在一定时效内预测赤道东太平洋月平均海温的变化趋势。由于所建系统是具有直接因果关系的预报模型 ,因此不仅可直接用于预测 。
Based on NCEP/NCAR and COADS data set,a dynamic frame and prediction model between equator East-Pacific lag SST and SOI,ELWI is better retrieved and imitated by using BP model and its improved calculation method of Matlab neural network toolbox. The established network model has better coupled accuracy and feasible forecast effect, which can effectively predict the basic development and variation trend of equator East Pacific SST in suitable time range. For the established dynamic system is a prediction model with direct cause/effect function relation,which not only can be used to predict weather system directly, but also can effectively avoid such instability of predicted results caused by initial condition sensitivity of non linear differential equations.
出处
《海洋科学》
CAS
CSCD
北大核心
2001年第2期38-42,共5页
Marine Sciences
基金
教育部优秀青年教师基金资助项目