Cross wavelet analysis: significance testing and pitfalls
Cross wavelet analysis: significance testing and pitfalls
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DOI：
10.5194/npg-11-505-2004
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发表时间：
2004-01-01
影响因子：
2.2
通讯作者：
Kurths, J
中科院分区：
文献类型：
--
作者：
Maraun, D;Kurths, J
在本文中，我们提出了一个详细的评价交叉小波分析的二元时间序列。我们开发了一个统计测试的基础上，零子波相干蒙特卡罗模拟。如果所考虑的两个过程中至少有一个是高斯白色噪声，则可以利用临界值的近似公式。在第二部分中，子波互谱和子波相干性的典型陷阱进行了讨论。小波互谱似乎不适合检验两个过程之间的相互关系。相反，应该应用小波相干性。此外，我们调查的问题，由于多重测试。基于这些结果，我们表明，ENSO和NAO之间的相干性是一个假象的大部分时间从1900年至1995年。然而，在1920年至1940年的一个不同时期，这两种现象之间发生了显著的一致性。
In this paper, we present a detailed evaluation of cross wavelet analysis of bivariate time series. We develop a statistical test for zero wavelet coherency based on Monte Carlo simulations. If at least one of the two processes considered is Gaussian white noise, an approximative formula for the critical value can be utilized. In a second part, typical pitfalls of wavelet cross spectra and wavelet coherency are discussed. The wavelet cross spectrum appears to be not suitable for significance testing the interrelation between two processes. Instead, one should rather apply wavelet coherency. Furthermore we investigate problems due to multiple testing. Based on these results, we show that coherency between ENSO and NAO is an artefact for most of the time from 1900 to 1995. However, during a distinct period from around 1920 to 1940, significant coherency between the two phenomena occurs.