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Correlation approaches to detection

机译:相关检测方法

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摘要

Criticisms leveled at the use of pattern correlation methods in climate-change detection studies are addressed. We first explain how spatial autocorrelation effects are accounted for. We then show why it is important to consider both pattern similarity and spatial-mean results in detection studies, and evaluate a mean-square-error statistic in this context. We also show that the use of changes in climate, as opposed to absolute climate states, does not lead to spurious trends in the pattern correlation statistic R(t). In doing this, we explain how previous pattern correlation studies account for "time arrow" effects in considering changes relative to an arbitrary reference year. We conclude that criticisms of the pattern correlation method are without substance. [References: 19]
机译:解决了在气候变化检测研究中使用模式相关方法的批评。我们首先解释如何考虑空间自相关效应。然后,我们说明了为什么在检测研究中同时考虑模式相似性和空间均值结果并评估这种情况下的均方误差统计量是很重要的。我们还表明,与绝对气候状态相比,使用气候变化不会导致模式相关性统计量R(t)出现虚假趋势。通过这样做,我们解释了以前的模式相关性研究在考虑相对于任意基准年的变化时如何解释“时间箭头”效应。我们得出结论,对模式相关方法的批评是没有实质性的。 [参考:19]

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