Comparison of different methods for detecting change points in hydroclimatic time series
Academic Article
Overview
Research
Identity
Additional Document Info
Other
View All
Overview
abstract
2019 An abrupt change is an important manifestation of hydroclimatic variability. Accurate detection of change points is a critical issue in hydroclimatic and climate change studies. In the article, we evaluated the performances of 12 methods (including both parametric and non-parametric) for detecting change points in hydroclimatic time series by considering the influences of eight major factors. Different methods exhibited different efficiencies and eight of the methods performed better which are recommended for application. Furthermore, the mean values of series and locations of change points were found to have little influence on the detection of change points. However, for a time series with smaller variance but bigger skewness and larger difference in the mean values before and after the change point, the abrupt changes can be more easily and accurately detected. Detection of change points in shorter series would have larger uncertainty. Based on the Monte-Carlo experiments, the efficiency of each method was quantified and its capability was quantitatively clarified. Detection of abrupt changes in precipitation over Southwest China showed that the Indian monsoon had a dominant influence on precipitation in the regions south of 30N and west of 110E. Since 2007 the Indian monsoon has maintained a weakening pattern, causing a decrease in precipitation on the Yunnan-Guizhou Plateau, which is one of the main causes of frequently occurring droughts. Results of this study can be a useful reference for choosing a method to detect change points in hydroclimate time series, and be an important complement for the detection and attribution of hydroclimatic variability.
