Analysis of the Nonlinear Trends and Non-Stationary Oscillations of Regional Precipitation in Xinjiang, Northwestern China, Using Ensemble Empirical Mode Decomposition

Bin Guo, Zhongsheng Chen, Jinyun Guo, Feng Liu, Chuanfa Chen and Kangli Liu
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Bin Guo: College of Geodesy and Geomatics, Shandong University of Science and Technology, Qingdao 266590, China
Zhongsheng Chen: State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China
Jinyun Guo: College of Geodesy and Geomatics, Shandong University of Science and Technology, Qingdao 266590, China
Feng Liu: College of Geodesy and Geomatics, Shandong University of Science and Technology, Qingdao 266590, China
Chuanfa Chen: College of Geodesy and Geomatics, Shandong University of Science and Technology, Qingdao 266590, China
Kangli Liu: College of Geodesy and Geomatics, Shandong University of Science and Technology, Qingdao 266590, China

IJERPH, 2016, vol. 13, issue 3, 1-20

Abstract: Changes in precipitation could have crucial influences on the regional water resources in arid regions such as Xinjiang. It is necessary to understand the intrinsic multi-scale variations of precipitation in different parts of Xinjiang in the context of climate change. In this study, based on precipitation data from 53 meteorological stations in Xinjiang during 1960–2012, we investigated the intrinsic multi-scale characteristics of precipitation variability using an adaptive method named ensemble empirical mode decomposition (EEMD). Obvious non-linear upward trends in precipitation were found in the north, south, east and the entire Xinjiang. Changes in precipitation in Xinjiang exhibited significant inter-annual scale (quasi-2 and quasi-6 years) and inter-decadal scale (quasi-12 and quasi-23 years). Moreover, the 2–3-year quasi-periodic fluctuation was dominant in regional precipitation and the inter-annual variation had a considerable effect on the regional-scale precipitation variation in Xinjiang. We also found that there were distinctive spatial differences in variation trends and turning points of precipitation in Xinjiang. The results of this study indicated that compared to traditional decomposition methods, the EEMD method, without using any a priori determined basis functions, could effectively extract the reliable multi-scale fluctuations and reveal the intrinsic oscillation properties of climate elements.

Keywords: ensemble empirical mode decomposition; precipitation; intrinsic mode function; nonlinear characteristics; Xinjiang (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2016
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