门限自回归模型在降水量预报中的应用——以中国义乌市为例

Threshold Autoregressive Model in Rainfall Forecasting—A Case Study in Yiwu

摘要: 气象要素既受影响因子的综合作用，又有自身的演变规律。但是，多元分析忽视了气象要素自身的演变规律，而时间序列分析没有充分利用影响因子的隐含信息。本文运用门限自回归模型通过逐段线性化手段来处理气象要素的非线性问题，既考虑影响因子的叠加作用，又兼顾气象要素自身的演变规律，其拟合和预报效果相对较好。但目前气象要素的时间序列普遍较短，一般都在40~60年左右，属不完全信息系统，其外推值不宜过长。最好能够逐年及时地补充新的信息，以改善拟合和预报效果。

Abstract: The meteorological elements are not only combined effected by the impact factors, but also their own evolution. Multivariate analysis ignores the evolution of meteorological elements themselves, and the time-series analysis did not take full advantage of the implicit information about the impact factor. This article uses threshold autoregressive model by piecewise linearization method of nonlinear problem to deal with the meteorological elements, both considering influence factors of superimposition, and balancing the evolution law of meteorological elements themselves; the fitting and forecasting effect is relatively good. But now the time sequence of the meteorological elements is generally short, usually around 40 to 60 years, which belongs to the incomplete information system, the extrapolation value should not be too long. It would be best to gradually replenish the new information in a timely manner to improve the fitting and forecasting results.