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气温变化的层次结构与未来气候变化趋势预测
引用本文:辛国君. 气温变化的层次结构与未来气候变化趋势预测[J]. 北京大学学报(自然科学版), 1997, 33(2): 254-261
作者姓名:辛国君
作者单位:北京大学地球物理学系,北京,100871
摘    要:用子波变换分析了Jones和Vinnikov南北半球近百年来气温资料,确定了气温变化的层次结构。结果发现,北半球在1923年前后、南半球在1939年前后发生了一次较大时间尺度的冷暖突变。提出了预测未来气候变化趋势的新思路,即根据气温变化的层次结构和不同层次的冷暖期特征时间尺度,预测未来气候变化。认为在北半球1923至2001年为大暖期,从2001年起将进入大冷期,大冷期约有77年;1991年至2001年是大暖期中相对凉爽的时期,80年代的增温事件将从1991年起趋于缓和。

关 键 词:气候突变  突变点  子波变换  子波方差  层次结构  
收稿时间:1996-05-22

Hierarchical Structure of SAT Variations and Trend of Future Climate Change
XIN Guojun. Hierarchical Structure of SAT Variations and Trend of Future Climate Change[J]. Acta Scientiarum Naturalium Universitatis Pekinensis, 1997, 33(2): 254-261
Authors:XIN Guojun
Affiliation:Department of Geophysics, Beijing University, Beijing, 100871
Abstract:In climatology, the cool/warm duration is defined as time duration which the mean temperature is lower/higher. The cool/warm duration is a relative concept. In this paper, the wavelet transform is applied to surface air temperature (SAT) time series analyses for the Northern/Southern Hemisphere (NH/SH) during the last one hundred years. The cool/warm duration in different time scales are revealed. They constitute the hierarchical structure of SAT variations. On the basis of the hierarchical structure, the trend of future climate change is predicted. The results are as following: 1. SAT variations obviously appear features of climate jump. For Jones climate time series: In large time scale, the cool/warm duration last about 77 years in NH and 90 years in SH. The climate jump happened at 1923 in NH and 1939 in SH. In small time scale, the cool/warm duration last about 14 years in NH and 5.6 years in SH. 2. According to the results of Jones climate time series, the trend of future climate change in NH will be: (1) The large warm duration is from 1923 to 2001. A large cool duration will begin at 2001; (2) The small cool duration is from 1991 to 2001, so the global warming caused by the strong increment of greenhouse effect will be stopped.
Keywords:climate jump  wavelet transform  wavelet variance  hierarchical structure
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