CHANGE POINT ANALYSIS: A STATISTICAL APPROACH TO DETECT POTENTIAL ABRUPT CHANGE

Abstract

Change-point analysis has proven to be an efficient tool in understanding the essential information contained in meteorological data, such as rainfall, ozone level, and carbon dioxide concentration. In this study, change-point analysis was used to discover potential significant changes in the annual means of total rainfall, temperature and relative humidity from 25 years of Malaysian climate data. Two methods, the CUSUM and bootstrap, were used in the analysis, where the CUSUM was used to analyze the data trends and patterns and bootstrapping was used to calculate the occurrence of change points based on the confidence level. The results of the analysis showed that potential abrupt shifts seem to have taken place in 1999, 2001 and 2002 with respect to the annual means for relative humidity, temperature and total rainfall, respectively. These identified change points will be further analyzed as potential candidates of abrupt change by extending the proposed method in a future study.