Attributes of Several Methods for Detecting Discontinuities in Mean Temperature Series

Abstract Simulated annual temperature series are used to compare seven homogenization procedures. The two that employ likelihood ratio tests routinely outperform other methods in their ability to identify modest (0.33°C; 0.6 standard deviation anomaly) shifts in the mean. The percentage of imposed shifts that are detected by these methods is similar to that based on tests that rely on a priori metadata information concerning the position of potential shifts. These methods, along with a two-phase regression approach, are also best at identifying and placing multiple shifts within a single time series. Although the regression procedure is better able to detect multiple breaks that are separated by relatively short time intervals, in its published form it suffers from a higher-than-expected Type I error rate. This was also found to be a problem with a metadata-based procedure currently in operational use. The likelihood tests are strongly influenced by the presence of trends in the difference series and shor...

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