基于去趋势波动的温度记录分析

Analysis on Temperature Records Based on Detrended Fluctuation

天气的持续性是众所周知的现象。热天之后是热天的可能性比是冷天的可能性要大的多,反过来也一样。本文研究天气变化的长期持续性,以s天为间隔的温度方差的相关系数c(s)服从一个幂函数c(s)∝s-γ。而DFA是一个在时间序列分析中很好的长期相关性预测的方法,高阶DFA的偏差在小的时间尺度内不断增强。对于短期的非稳态时间序列,揭示一个模拟DFA方法来消除数据中的这种趋势。通过对某地区近7年的温度记录分析,发现指数大约为0.68,说明未来100年全球变暖将没有模型预测的那么显著也不能排除。

The persistence of the weather is a well known phenomenon . A warm day is more likely to be followed by a warm day than by a cold one and vice versa. In this paper, we review the long term persistence that characterized by the correlation c （s） of temperature variations by s days, decays for large s as a power law c（s）∝s^-γ. DFA is a well -established method for the detection of long - range correlations in time - series. Deviations from scaling which appear at small time scales become stronger in higher orders of DFA, and suggest a modified DFA method to remove them in a non - stationary time - series. By using DFA method to analyze some area＇ s temperature record of nearly 7 years, the exponent has been found is about 0.68. From this point of view it cannot be excluded that the global warming in the next 100 yr will be less pronounced than predicted by the models.