Spatio‐temporal variations of nonlinear trends of precipitation over an arid region of northwest China according to the extreme‐point symmetric mode decomposition method

Climate systems have both nonlinear and non‐stationary characteristics, and it is important to develop methods to reveal the nonlinear trends in these systems. Based on synthetic data with known signals and a precipitation anomaly time series from 74 meteorological stations in an arid region of northwest China (ARNC) from 1960 to 2015, the latest extreme‐point symmetric mode decomposition (ESMD) and ensemble empirical mode decomposition (EEMD) methods were employed to conduct multi‐scale mode decomposition. The results showed that both the ESMD and EEMD methods can separate synthetic signals and extract the nonlinear trends of precipitation in ARNC and can thus provide reliable decomposition results. This article employed the ESMD method to analyse the spatial and temporal variation features of nonlinear precipitation trends in ARNC from 1960 to 2015. The results indicated that over the past 50+ years, the overall precipitation in ARNC has exhibited an apparent nonlinear upwards trend. In addition, its changes have exhibited oscillation periods of 3, 6, and 11 years. The periods of the three components are significant (p < 0.05), and the variance contribution rate of the first intrinsic mode function (IMF1) is the largest, reaching 58%. Furthermore, there are obvious spatial differences in the nonlinear trends of average annual precipitation: northern Xinjiang has had a mainly rising trend; southern Xinjiang has had mainly rising and decreasing–rising trends; and the precipitation changes in the Hexi Corridor have been quite complicated. The ESMD method can reflect integrated changes in the nonlinear trends of precipitation over different time scales and has important practical significance and scientific value for revealing the complicated structural features of climate systems.

[1]  Zhi Li,et al.  Water resource formation and conversion and water security in arid region of Northwest China , 2016, Journal of Geographical Sciences.

[2]  Jianhua Xu,et al.  The regional features of temperature variation trends over Xinjiang in China by the ensemble empirical mode decomposition method , 2015 .

[3]  Fahu Chen,et al.  Physical Mechanisms of Summer Precipitation Variations in the Tarim Basin in Northwestern China , 2015 .

[4]  J. Xia,et al.  Decadal climate variability and vulnerability of water resources in arid regions of Northwest China , 2015, Environmental Earth Sciences.

[5]  G. Meehl,et al.  Regional precipitation simulations for the mid‐1970s shift and early‐2000s hiatus , 2014 .

[6]  Yaning Chen,et al.  Abrupt change of temperature and precipitation extremes in the arid region of Northwest China , 2014 .

[7]  Jianping Huang,et al.  Evolution of land surface air temperature trend , 2014 .

[8]  Yaning Chen,et al.  Dynamics of temperature and precipitation extremes and their spatial variation in the arid region of northwest China , 2014 .

[9]  T. Zhou,et al.  Multidecadal Variability of North China Aridity and Its Relationship to PDO during 1900–2010 , 2014 .

[10]  王 金良,et al.  The ESMD Method for Climate Data Analysis , 2014 .

[11]  Yaning Chen,et al.  Spatial distribution and temporal trends of mean precipitation and extremes in the arid region, northwest of China, during 1960–2010 , 2013 .

[12]  Yaning Chen,et al.  Temperature and precipitation changes in different environments in the arid region of northwest China , 2013, Theoretical and Applied Climatology.

[13]  Hung-Yi Hsu,et al.  Quantitative Non-stationary Assessment of cerebral Hemodynamics by Empirical Mode Decomposition of cerebral Doppler Flow velocity , 2013, Adv. Data Sci. Adapt. Anal..

[14]  Jin-Liang Wang,et al.  Extreme-Point Symmetric Mode Decomposition Method for Data Analysis , 2013, Adv. Data Sci. Adapt. Anal..

[15]  Maysam F. Abbod,et al.  Investigating Properties of the Cardiovascular System Using Innovative Analysis Algorithms Based on Ensemble Empirical Mode Decomposition , 2012, Comput. Math. Methods Medicine.

[16]  Klaus Fraedrich,et al.  Precipitation climate of Central Asia and the large-scale atmospheric circulation , 2012, Theoretical and Applied Climatology.

[17]  Yuping Yan,et al.  Changes in daily climate extremes in China and their connection to the large scale atmospheric circulation during 1961–2003 , 2011 .

[18]  W. Qian,et al.  Periodic oscillations in millennial global-mean temperature and their causes , 2010 .

[19]  A. Durand,et al.  Long‐term hydrological changes of the Seine River flow (France) and their relation to the North Atlantic Oscillation over the period 1950–2008 , 2010 .

[20]  Yongping Shen,et al.  Hydrology and water resources variation and its response to regional climate change in Xinjiang , 2010 .

[21]  W. Landman.  Climate change 2007: the physical science basis , 2010 .

[22]  O. Eisen,et al.  Ground‐based measurements of spatial and temporal variability of snow accumulation in East Antarctica , 2008 .

[23]  Norden E. Huang,et al.  A review on Hilbert‐Huang transform: Method and its applications to geophysical studies , 2008 .

[24]  Wan,et al.  The Influence of Mechanical and Thermal Forcing by the Tibetan Plateau on Asian Climate , 2007 .

[25]  H. L. Miller,et al.  IPCC, 2007: Summary for Policymakers , 2007 .

[26]  Chen Yaning,et al.  Plausible impact of global climate change on water resources in the Tarim River Basin , 2005 .

[27]  N. Huang,et al.  A study of the characteristics of white noise using the empirical mode decomposition method , 2004, Proceedings of the Royal Society of London. Series A: Mathematical, Physical and Engineering Sciences.

[28]  MU ZhiguoMA Peixue Gao Honglin.  REVIEW OF CYCLE AND MECHANISM OF ANCIENT CLIMATE , 2000 .

[29]  N. Huang,et al.  The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis , 1998, Proceedings of the Royal Society of London. Series A: Mathematical, Physical and Engineering Sciences.

[30]  Heigang Xiong,et al.  Why does precipitation in northwest China show a significant increasing trend from 1960 to 2010 , 2016 .

[31]  Corinne Le Quéré,et al.  Climate Change 2013: The Physical Science Basis , 2013 .

[32]  Duan Keqin.  Effects of North Atlantic Oscillation on Summer Precipitation over the Tibetan Plateau , 2012 .

[33]  Shi Hong-ling.  Multiple Time-scale Variation of Annual Runoff and Sediment at Lijin Station In the Lower Reach of Yellow River Based on EMD Analysis , 2012 .

[34]  Zhao Jing,et al.  Study on seismic signal features extraction based on EMD , 2012 .

[35]  Zhou Zhen-guo.  An improved texture image classification method based on bidimensional empirical mode decomposition , 2012 .

[36]  Norden E. Huang,et al.  Ensemble Empirical Mode Decomposition: a Noise-Assisted Data Analysis Method , 2009, Adv. Data Sci. Adapt. Anal..

[37]  M. Zhuguo.  Characteristics of Climate Changes in Xinjiang from 1960 to 2005 , 2009 .

[38]  S. Schiavon,et al.  Climate change 2007 : the physical science basis : contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change , 2007 .

[39]  Yang Da-yuan.  Trend and Characteristics of Climatic Change in Arid Region of Northwest China in Resent 50 Years , 2007 .

[40]  Hu Yu-xia,et al.  Analyese on Temporal-Spatial Features of Annual Precipitation in Northwest China in 1961-2000 , 2004 .

[41]  Xue Yan.  Change Trend of the Precipitation and Air Temperature in Xinjiang since Recent 50 Years , 2003 .

[42]  Shi Ya,et al.  Preliminary Study on Signal, Impact and Foreground of Climatic Shift from Warm-Dry to Warm-Humid in Northwest China , 2002 .

[43]  Xie Jin-nan.  A Preliminary Study on Trends and Interannual Variaration ofPrecipitation in Central and Western Portions ofNorthwest Region of China , 2001 .

[44]  Xing-zhong Yuan,et al.  Distributed under Creative Commons Cc-by 4.0 the Nonlinear Variation of Drought and Its Relation to Atmospheric Circulation in Shandong Province, East China , 2022 .