%0 Journal Article
%T Abrupt climate change detection based on heuristic segmentation algorithm<br>基于启发式分割算法的气候突变检测研究
%A Feng Guo-Ling
%A Gong Zhi-Qiang
%A Dong Wen-Jie
%A Li Jian-Pin
%A <br>封国林
%A 龚志强
%A 董文杰
%A 李建平
%J 物理学报
%D 2005
%I 
%X 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,Berna ola Galvan recently proposed a heuristic segmentation algorithm to segment the t ime 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 v erify the effectiveness of heuristic segmentation algorithm in dealing with nonl inear time series by an ideal time series.Through detecting and analyzing the in formation of abrupt climate changes contained in recent 2000a's tree annual grow th ring,we succeeded in distinguishing abrupt changes with different scales.The research based on the newly defined paramcter of abrupt change density shows tha t 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.
%K abrupt climate change
%K mean segment
%K abrupt change density
%K human a ctivities
%K global temperature change<br>气候突变，
%K 均值段，
%K 突变密度，
%K 人为因素，
%K 全球变化
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=6E709DC38FA1D09A4B578DD0906875B5B44D4D294832BB8E&cid=47EA7CFDDEBB28E0&jid=29DF2CB55EF687E7EFA80DFD4B978260&aid=5A831744732957FC&yid=2DD7160C83D0ACED&vid=318E4CC20AED4940&iid=708DD6B15D2464E8&sid=C22353CD9DBD0490&eid=EC6AA297E57C49A3&journal_id=1000-3290&journal_name=物理学报&referenced_num=0&reference_num=20