A Precipitation Forecast Model Based on Regression Analysis and Time Series Analysis

TANG Ya-song; ZHANG Xin; CAI Huan-jie; WANG Jian

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A Precipitation Forecast Model Based on Regression Analysis and Time Series Analysis

- A Precipitation Forecast Model Based on Regression Analysis and Time Series Analysis
- Bulletin of Soiland Water Conservation Vol. 28, Issue 1, Pages: 88-91(2009)
- 作者机构：
  
  1. 西北农林科技大学水利与建筑工程学院, 陕西杨凌,712100
  2. 武汉大学水利水电学院,湖北,武汉,430072
- 作者简介：
- 基金信息：
- DOI：
  CLC：
- Published：2009
- 稿件说明：
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TANG Ya-song, ZHANG Xin, CAI Huan-jie, et al. A Precipitation Forecast Model Based on Regression Analysis and Time Series Analysis[J]. Bulletin of Soiland Water Conservation, 2009, 28(1): 88-91.
DOI：

TANG Ya-song, ZHANG Xin, CAI Huan-jie, et al. A Precipitation Forecast Model Based on Regression Analysis and Time Series Analysis[J]. Bulletin of Soiland Water Conservation, 2009, 28(1): 88-91. DOI：

摘要

中长期降水预报存在的问题是资料不足和预报精度较低。运用回归分析与时序分析相结合的方法

将实测降水序列分解成趋势、周期、随机3种成分

并分别构建各分量的子模型;将3个子模型线性叠加

并对拟合的纯随机序列进行修正

得到降水预报的第三类模型;进而给出了模型精度评价方法。实例分析表明

运用修正后的模型进行降水预报

可以缩小峰值处的误差

预报精度比其余两类模型有所提高。该方法可仅根据历史资料进行降水预报

对资料要求较低

精度可靠

是一种实用的方法。

Abstract

In this paper

a composite model based on regression analysis and time series analysis is constructed to improve forecast accuracy and deal with problems of data deficiencies in mid-to-long-term precipitation forecast.Generally speaking

hydrologic time series may be split into the trend

cyclic

and random components.Under this guideline

firstly

precipitation sequence is split into the three components mentioned above by using regression analysis and time series analysis methods;three submodels are respectively constructed for the three components;the independent random sequence is stabilized to modify traditional model structure;and the three submodels are added by linear superposition to establish a new precipitation forecast model(the 3rd type).Later

the paper gives accuracy assessment indexes.Results show that errors of the modified model are lower in rain spell

i.e.

its accuracy is higher than other two models.So

using historical data

the model can work well in precipitation forecast and get a proper accuracy.It is proved to be a practical model for forecast.

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