Multi-Scale Climate Change and Its Influencing Factors in Northern Shaanxi during 1960–2020

Abstract

Based on the observed data of precipitation and air temperature in Northern Shaanxi during 1960–2020, the characteristics of precipitation and air temperature at multiple time scales in Northern Shaanxi were analyzed by using CEEMDAN (Adaptive Complete Set Empirical Model) and back propagation neural network time series model. At the same time, the cross-wavelet and wavelet coherence methods were used to explore the factors affecting climate change in Northern Shaanxi. The results show that there are certain rules of precipitation and temperature in the decadal, interannual, seasonal and monthly scales in Northern Shaanxi. The interdecadal fluctuations of precipitation and temperature were dominant, and the periods were about 12–23 years and 13–21.1 years, respectively. According to the analysis of trend term, in addition to the stable fluctuation of precipitation in Northern Shaanxi, the temperature showed a fluctuating upward trend. Arctic oscillation index, Pacific decadal oscillation index, Niño 3.4 Region sea surface temperatures index and relative number of sunspots all have a certain influence on the climate change in Northern Shaanxi.

Keywords

• CEEMDAN method
• wavelet analysis
• BP neural network
• multi-scale
• Northern Shaanxi
• climate