Complexity of daily precipitation and its change in China during 1961–2015 based on approximate entropy

Abstract

Approximate entropy (ApEn) can measure the regularity and complexity of a nonlinear system. We find that the results of ApEn are relatively stable when the sample size of a time series exceeds 100, which indicates that the estimation results of the ApEn algorithm are robust to small sample data. In this study, the complexity of the daily precipitation records in China from 1961 to 2015 was first analyzed by using ApEn, and then we further investigated the spatial and temporal variability of the dynamical characteristics of precipitation. The results show that the ApEn values of daily precipitation in China during 1961–2015 present the following characteristics: larger in southern and eastern China and smaller in northern and western China. In addition, ApEn in Northwest China and the Tibetan Plateau has been increasing since 1961. However, since the 1970s, ApEn in the south of the middle and lower reaches of the Yangtze River shows a gradual decrease. The temporal instances of abrupt ApEn changes in daily precipitation occur from region to region. The number of stations with an abrupt ApEn shift has a statistically significant increase since 1984 at a significant level of α = 0.01, which means the complexity characteristic of daily precipitation in China has been more prone to abrupt shifts since 1984 than in the previous period.