地理科学 ›› 2004, Vol. 24 ›› Issue (2): 177-182.doi: 10.13249/j.cnki.sgs.2004.02.177

• 论文 • 上一篇    下一篇

Hurst指数估计中存在的若干问题——以在气候变化研究中的应用为例

江田汉1, 邓莲堂2   

  1. 1. 北京大学环境科学系, 北京 100871;
    2. 国家气象中心, 北京 100081
  • 收稿日期:2003-06-25 修回日期:2003-09-13 出版日期:2004-03-20 发布日期:2004-03-20
  • 基金资助:
    国家气象中心自筹经费项目(ZK2002ASZ-07)资助。

Some Problems in Estimating a Hurst Exponent—A Case Study of Applicatings to Climatic Change

JIANG Tian-Han1, DENG Lian-Tang2   

  1. 1. Department of Environmental Sciences, Peking University, Beijing 100871;
    2. National Meteorological Center, Beijing 100081
  • Received:2003-06-25 Revised:2003-09-13 Online:2004-03-20 Published:2004-03-20

摘要: 用7种方法估计中国近百年月平均温度距平序列的Hurst指数,并用随机重排法与高斯随机数做均值对比。结果表明:R/S分析法、小波分析法和Whittle法优于残差方差法、绝对值法、聚合方差法和周期图法;中国近百年月平均温度距平序列的Hurst指数的估计值约为0.76±0.003,表现出较强的持续性。未来中国月平均温度变化将与自20世纪80年代增温的趋势一致,将来整体趋势还是增温。

Abstract: The phenomena with self-similarity and long-range dependence are widespread in the nature. One of the main approaches that quantificationally measure the long range dependence is to estimate a Hurst exponent, which has been extensively applied in hydrology, climatology, geology, and seismology, etc. Based on the analysis of several popular estimating methods and their virtues and limitations, some common problems in their applications are pointed out, and the corresponding solutions are proposed in this paper. Then, seven methods are used to estimate the Hurst exponent for average monthly temperature anomaly in China from January,1873 to December,1990.To test the effect of the results, mean values are compared with a set of Gaussian distribution random numbers using the randomly shuffling method. The results are as follows: R/S method, Abry-Veitch method, and Whittle method are superior to Variance of residuals, Absolute Value method, Aggregated Variance method, and Periodogram method. The appropriate value of the Hurst exponent is, indicating persistence, i.e., the trend of temperature variations in China in near future will generally be the same as the past. The temperature warming trend from the 1980s indicates another warming trend for hereafter.

中图分类号: 

  • P463.3