Spatiotemporal Characteristics of Precipitation and Drought Variability in Taiwan Using Multi-dimensional Complementary Ensemble Empirical Mode Decomposition

Spatiotemporal Characteristics of Precipitation and Drought Variability in Taiwan Using Multi-dimensional Complementary Ensemble Empirical Mode Decomposition

 

Abstract

Most time series observed in natural systems are nonlinear and nonstationary, particularly under the influence of climate change. Taiwan has experienced increasingly frequent drought events in recent decades. Droughts are characterized by their gradual development, cumulative impacts, and lack of clear early warning signals, which makes their detection and analysis challenging.

 

To address these issues, this study applies Multi-dimensional Complementary Ensemble Empirical Mode Decomposition (MCEEMD) to analyze long-term temperature and precipitation data in Taiwan from 1960 to 2023. MCEEMD is an effective time–frequency analysis method designed for nonlinear and nonstationary time series. It enables the decomposition of multi-dimensional signals into a set of Intrinsic Mode Functions (IMFs), allowing both spatial and temporal characteristics of climate variables to be examined. Through these IMFs, meaningful instantaneous frequencies and long-term trends in the signals can be identified.

 

This study considers both stochastic and deterministic influences by reconstructing the IMFs into two components based on their autocorrelation coefficients. The relationships between temperature, precipitation variability, and drought-related characteristics are then examined, providing insights into the spatiotemporal behavior of drought events in Taiwan.

 

Key word: Multi-dimensional Complementary Ensemble Empirical Mode Decomposition(MCEEMD ),Intrinsic Mode Functions (IMFs)