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Climate system is nonlinear,non-stationary and hierarchical,which makes even harder to detect and analyze abrupt climate changes.Based on Student's t-test,Bernaola Galvan recently proposed a heuristic segmentation algorithm to segment the time series into several subsets with different scales,which is more effective in detecting the abrupt changes of nonlinear time series.In this paper,we try to verify the effectiveness of heuristic segmentation algorithm in dealing with nonlinear time series by... Climate system is nonlinear,non-stationary and hierarchical,which makes even harder to detect and analyze abrupt climate changes.Based on Student's t-test,Bernaola Galvan recently proposed a heuristic segmentation algorithm to segment the time series into several subsets with different scales,which is more effective in detecting the abrupt changes of nonlinear time series.In this paper,we try to verify the effectiveness of heuristic segmentation algorithm in dealing with nonlinear time series by an ideal time series.Through detecting and analyzing the information of abrupt climate changes contained in recent 2000a's tree annual growth ring,we succeeded in distinguishing abrupt changes with different scales.The research based on the newly defined paramcter of abrupt change density shows that human activities might have lead to the recent 1000a's unbalanced distribution of serial and spares segments of abrupt climate changes,which may be one of the manifestations of global temperature change. 气候系统的非线性、多层次性和非平稳性对气候突变的检测方法提出了较高的要求.基于t检验将非平稳序列分割为多个不同尺度的自平稳子序列,Bernaola Galvan提出的启发式分割算法(BG算法),对非平稳时间序列的突变检测效果较好.在BG算法的基础上,通过理想时间序列验证BG算法处理非平稳时间序列的有效性,并对近2000a北半球树木年轮距平宽度序列基于不同层次的思想,检测和分析其中包含的各种尺度的气候突变事件,成功地区分不同尺度的突变.定义的新物理量——突变密度的分析表明,自然因素作用的基础上,人为因素影响的加剧可能导致近1000a来突变密集段和稀疏段分布失衡,这可能是全球变化的重要表现之一. Global change science is a new research field, and one of the most important topics of which is the climate change study, to which great importance is attached by all governments of the world, and climatic abrupt change is one of manifestations of climate changes. Nowadays, research of climate change is mainly based on climatic proxy using traditional statistical method. However, climatic system is nonlinear, non-stationary and hierarchical, which makes even harder to detect and analyze abrupt climate changes.... Global change science is a new research field, and one of the most important topics of which is the climate change study, to which great importance is attached by all governments of the world, and climatic abrupt change is one of manifestations of climate changes. Nowadays, research of climate change is mainly based on climatic proxy using traditional statistical method. However, climatic system is nonlinear, non-stationary and hierarchical, which makes even harder to detect and analyze abrupt climate changes. As well known, climatic system is made up of several sub-systems, and there may be inherent connections between them; however, there is only a few research methods and theories in this field. This article introduces a new detecting method, the heuristic segmentation algorithm, which is well fitted to nonlinear and non-stationary time series. Then, dealing with northern hemisphere tree rings and Beijing stalagmite based on high and low frequency series, we try to distinguish abrupt changes in different scales and disclose its physial mechanism. Defining a new physical quantity, the abrupt density, and analyzing the distribution characteristics of abrupt changes before and after 1000 a, We take Huabei area's climatic change as an example to explore the inherent connections between local and global areas. 全球变化已成为当代科学界瞩目的新领域,气候变化是其研究的核心内容之一,它受到各国政府的极大重视.气候突变是气候变化的重要表现形式之一,目前对气候突变的研究主要针对代用资料,运用传统的统计学方法进行处理,尽管取得了不少进展,但气候系统的非线性、多层次性和非平稳性对分析和检测气候突变的方法提出了较高的要求.众所周知,气候系统可能是由多个不同区域气候子系统构成的复杂体系,因而局地和全球气候变化之间必然存在一定的内在联系,但目前关于这方面研究的理论和方法还较少.介绍了一种适合非线性和非平稳时间序列的突变检测新方法———启发式分割算法(BG算法),运用该方法对北半球树木年轮宽度和北京石花洞石笋微层厚度距平序列分别基于高频和低频进行处理,试图区分不同性质的突变,揭示其变化的物理机理.定义了新的物理量———突变密度,对比前后千年内突变的疏密分布特点,就人为因素对气候变化可能产生的影响作初步探讨.对树轮和石笋资料的高频序列从不同的角度进行检测和分析,进而以华北气候变化的特征为例,研究局地和全球气候变化之间的内在的联系.
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