中文摘要：

如何客观保留树轮序列的低频气候信息是树轮气候学研究的热点和难点问题.本文以西藏浪卡子地区大果圆柏（Sabina tibetic Kom.）的树轮宽度为资料,对新提出的特征值分析方法进行实例演示.通过构建不同树轮序列之间的协方差矩阵,计算其特征向量和特征值,并利用特征向量和主成分重建了特征值年表.将建立的特征值年表与传统的标准化年表（STD年表）和区域曲线标准化年表（RCS年表）进行比较,分析不同去趋势方法对树轮序列低频气候信息保留能力的差异.结果表明,相对STD年表,新建立的特征值年表与RCS年表能够较好地保留低频气候信息,显示了特征值分析方法在树轮气候学研究领域具有较高的应用潜力.

英文摘要：

Removing biological growth trend and extracting low-frequency climatic information are the key problems in the dendroclimatological research.The standardized detrending （STD） and regional curve standardization （RCS） are the two commonly used detrending methods.The STD method can extract climatic signals at a decadal scale.The RCS method has its advantage of preserving low-frequency climatic signals in the tree-ring data.Due to the distorted trending problem caused by different growth rate of trees,the RCS method has its limitation concerning the existing long-term false or distorted trend in the produced chronologies.The latest Eigen Analysis method （EGA） shows superiority in terms of amelioration of the ‘ distorted trending’ problem and preserving low-frequency climatic signals in tree-ring chronology.In this paper,we exemplify the application of the EGA technique using a ring-width dataset of Tibetan junipers （Sabina tibetica Kom.） in the Langkazi region of Tibet.By constructing the intra-record covariance matrix and calculating the eigen vectors （EV） and eigen values,the EGA chronology has been prepared.Meanwhile,the STD and RCS chronologies have also been developed.The STD,RCS and EGA chronologies were compared with respect to the capability in preserving low-frequency climatic signals.Results showed that the EGA chronology has equal ability with the RCS chronology in the preservation of low-frequency climatic signals.The EGA method showed a great potential in future dendroclimatological research.