Complexity analysis of spatial–temporal precipitation system by PCA and SDLE

In this paper, an ensemble technique combining the principal component analysis (PCA) with scale-dependent Lyapunov exponent (SDLE) is used to characterize complexity of precipitation dynamical system. The spatial–temporal precipitation data is decomposed by employing PCA method and then the SDLE for the first few principal components (PCs) time series are computed. The first few PCs time series are found to exhibit the different scaling laws on different time scales. The study illustrate that the spatial–temporal precipitation data is chaotic and the precipitation system is truly multiscaled and complex.