Abstract
We compared and evaluated the performance of five methods for detecting abrupt climate changes using a time series with artificially generated abrupt characteristics. Next, we analyzed these methods using annual mean surface air temperature records from the Shenyang meteorological station. Our results show that the movingt-test (MTT), Yamamoto (YAMA), and LePage (LP) methods can correctly and effectively detect abrupt changes in means, trends, and dynamic structure; however, they cannot detect changes in variability. We note that the sample size of the subseries used in these tests can affect their results. When the sample size of the subseries ranges from one-quarter to three-quarters of the jump scale, these methods can effectively detect abrupt changes; they perform best when the sample size is one-half of the jump scale. The Cramer method can detect abrupt changes in the mean and trend of a series but not changes in variability or dynamic structure. Finally, we found that the Mann-Kendall test could not detect any type of abrupt change. We found no difference in the results of any of the methods following removal of the mean, creation of an anomaly series, or normalization. However, detrending and study period selection affected the results of the Cramer and Mann-Kendall methods; in the latter case, they could lead to a completely different result.
Highlights
Climate change includes continuous or gradual changes in climate that can be defined by a trend and discontinuous or abrupt changes in climate [1]
Abrupt climate changes have received extensive attention because of the abrupt shift identified in the North Pacific Ocean in 1977 [16, 17]; this abrupt change could be related to a decadal-scale change in the Pacific Ocean [18]
We showed that the moving t-test (MTT), YAMA, and LP methods are sensitive to the choice of subseries length
Summary
Climate change includes continuous or gradual changes in climate that can be defined by a trend and discontinuous or abrupt changes in climate [1]. Abrupt climate changes can be defined as abrupt shifts in climate from one stable state (or stable and continuous trend) to another stable state (or stable and continuous trend). These shifts are associated with changes in the statistical characteristics of climate variables in time and space. Similar to the shift in the North Pacific Ocean, an abrupt change occurred in the East Asian summer monsoon at the end of the 1970s [19, 20]. Ding and Zhang [22] investigated trends and change points in temperature and precipitation on the Qinghai-Tibet Plateau and six other regions in China, finding that rapid warming in northeastern China occurred earlier than in other regions and that rapid changes on the QinghaiTibet Plateau lagged changes in the region north of the Discrete Dynamics in Nature and Society
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