摘要
基于1995～1997年夏季(5～8月)T106数值预报场资料,研究讨论了夏季西太平洋副热带高压面积指数的预报误差修正与预报优化问题。首先通过小波分解对预报目标进行频域分解和高频滤波,随后引入了人工神经网络BP模型与自组织特征映射网络(SOFM)相结合的方法,对副高指数的数值预报结果进行了预报优化与误差修正的训练建模。试验结果表明,所建模型能够较为客观、有效地修正副高指数的数值预报误差,优化和改进副高预报效果。
Based on the T106 numerical forecast model output product （May-August, 995- 1997）, an idea of forecast optimization technique for subtropical high＇s characteristic index and its errors revisal route were presented and discussed in the paper. Firstly, the time series of prediction target was decomposed into different frequency section by using wavelet method and some high frequency signals and noises were filtered then a synthetical technique of combining BP （Back-Propagation Network） lgorithm with SOFM （Self-Organizing Feature Map） model of ANN （Artifical Neural Network） was introduced, and some numerical forecast samples were well optimized and its errors were effectively revised by using the technique, experimental results showed that the methods here was promising in practice.
出处
《热带气象学报》
CSCD
北大核心
2007年第3期265-270,共6页
Journal of Tropical Meteorology
基金
国家自然科学基金项目(40375019)
热带海洋气象科学研究基金开放课题(200609)共同资助
关键词
副热带高压
预报优化
神经网络
小波分解
subtropical high
forecast optimization
artifical neural network
wavelet decomposition
