IDENTIFYING SPATIAL PATTERNS AND DYNAMICS OF CLIMATE CHANGE USING RECURRENCE QUANTIFICATION ANALYSIS: A CASE STUDY OF QINGHAI–TIBET PLATEAU

Abstract

The climate system is a prototypical nonlinear complex system exhibiting nonstationary temporal variation and complicated spatial patterns. One of the ideal locations for studying climate systems is the Qinghai–Tibet Plateau (QTP), which is considered an amplifier of global climate change. In this study, recurrence quantification analysis (RQA) was used to analyze the annual temperature series of 17 stations in different climate zones of the QTP, based on station observation data of daily temperature (minimum, maximum and mean) from 1961 to 2008. Spatial patterns and variation of RQA indices of Determinism (DET) and Kolmogorov (K2) entropy suggested that there are marked differences in temperature pattern in the QTP. Correlation analysis between RQA indices of temperature series and environmental factors, such as topographical variation and Normalized Difference Vegetation Index suggest that both the source and effect of climate complexity are nonlinear. Results of this study indicate that RQA measurement was indeed an efficient approach to analyze the dynamics of a climate system.