Climate Signal Detection Using Wavelet Transform: How to Make a Time Series Sing
Climate Signal Detection Using Wavelet Transform: How to Make a Time Series Sing
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DOI：
10.1175/1520-0477(1995)076
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发表时间：
1995-12
影响因子：
8
通讯作者：
K. Lau;H. Weng
中科院分区：
文献类型：
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作者：
K. Lau;H. Weng
本文介绍了小波变换在气候时间序列分析中的应用。还提供了对WT基本概念的教程描述，并将其与音乐中使用的类似概念进行了比较。利用时间序列的小波变换表示和乐谱之间的类比，作者说明了局部信息与全球信息在气候信号时频定位中的重要性。使用分析信号和真实气候时间序列演示了WT应用于气候数据分析的例子。本文给出了将WT应用于两个气候时间序列的结果，即具有2.5-Myr深海沉积δ18 O记录的代用古气候时间序列和具有140年北半球地表温度月记录的代用古气候时间序列。前者表明存在40-kyr和100-kyr的振荡，并且在0.7 Myr的振荡状态中出现突变，这与先前的研究一致。后者拥有无数的振荡模式，从……
In this paper, the application of the wavelet transform (WT) to climate time series analyses is introduced. A tutorial description of the basic concept of WT, compared with similar concepts used in music, is also provided. Using an analogy between WT representation of a time series and a music score, the authors illustrate the importance of local versus global information in the time–frequency localization of climate signals. Examples of WT applied to climate data analysis are demonstrated using analytic signals as well as real climate time series. Results of WT applied to two climate time series—that is, a proxy paleoclimate time series with a 2.5-Myr deep-sea sediment record of δ18 O and a 140-yr monthly record of Northern Hemisphere surface temperature—are presented. The former shows the presence of a 40-kyr and a 100-kyr oscillation and an abrupt transition in the oscillation regime at 0.7 Myr before the present, consistent with previous studies. The latter possesses a myriad of oscillatory modes from...