It has been demonstrated several times that when principal component analysis (PCA) is used for detection of modes of atmospheric circulation variability (teleconnections), principal components must be rotated. Despite it, unrotated PCA is still often used. Here we demonstrate on the examples of North Atlantic Oscillation (NAO), Arctic Oscillation (AO), Barents Oscillation (BO), and the summer East Atlantic (SEA) pattern that unrotated PCA results in patterns that are artifacts of the analysis method rather than true modes of variability. This claim is based on the comparison of the spatial patterns of the modes with spatial autocorrelations, on the sensitivity of the patterns to spatial and temporal subsampling, and, for the SEA pattern, on correlations with tropical sea surface temperature. Unlike NAO, which is defined by rotated PCA, the other modes, that is, AO, BO, and SEA pattern, defined by unrotated PCA, do not correspond well to underlying autocorrelation structures and are more sensitive to choices of spatial domain and time interval over which they are defined. We reiterate that a great care must be taken when interpreting outputs of PCA when applied to the detection of modes of circulation variability: a comparison with spatial autocorrelations and check for their spatial and temporal stability are necessary to distinguish true modes from statistical artifacts, which we call “ghost patterns.”

中文翻译：

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如何识别大气环流变异的真实模式

多次证明，当使用主成分分析（PCA）来检测大气环流变化模式（电话连接）时，必须旋转主成分。尽管如此，仍经常使用未旋转的PCA。在这里，我们以北大西洋涛动（NAO），北极涛动（AO），巴伦特涛动（BO）和夏季东大西洋（SEA）模式为例，这些模式未旋转的PCA导致的模式是分析方法而不是分析方法的伪像真正的可变性模式。此声明基于以下两种模式的空间模式的比较：具有空间自相关性，模式对空间和时间二次采样的敏感性，以及对于SEA模式而言，是基于与热带海表温度的相关性。与由旋转PCA定义的NAO不同，其他模式，即由未旋转的PCA定义的AO，BO和SEA模式，与底层自相关结构不太好对应，并且对定义它们的空间域和时间间隔的选择更敏感。我们重申，在将PCA的输出应用于循环变异性模式的检测时，必须格外小心：与空间自相关性进行比较并检查其空间和时间稳定性，才能将真实模式与统计伪像区分开来。称为“鬼影模式”。