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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。
How to objectively preserve the low-frequency climate information of the tree-ring sequence is a hot and difficult issue in tree-ring climatology. In this paper, the tree width of Sabina tibetic Kom. In Langkawi, Tibet, is used as an example to demonstrate the new eigenvalue analysis method. The eigenvectors and eigenvalues are calculated by constructing the covariance matrix between different tree-round sequences, and the eigenvalues chronology is reconstructed by using the eigenvectors and principal components. The eigenvalue chronology established was compared with the traditional standard chronology (STD) and regional chronology (RCS) chronology to analyze the differences in the retention ability of tree ring sequence low-frequency climatic information with different de-tended methods. The results show that the relative eigenvalue chronology and the RCS chronology can keep the low frequency climate information well, which shows that the eigenvalue analysis method has higher potential in the field of tree ring climatology.