Annual to multidecadal climate modes linking precipitation of the northern and southern slopes of the Tianshan Mts

Lixing An, Yonghong Hao, Tian Chyi Jim Yeh, Baoju Zhang

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9 Scopus citations

Abstract

Precipitation in the Tianshan Mts is one of the main sources of subsurface and surface water in arid Xinjiang, China. Precipitation on the northern slope is significantly larger than that on the southern slope in the Tianshan Mts (i.e., annual average precipitation from 1951 to 2017 was 143 and 75 mm on the northern and southern slopes, respectively). The spatial distribution characteristics of precipitation largely influence the regional ecological environment and sustainable economic development. For better understanding the spatial difference of precipitation and the relations with climate modes in Tianshan Mts, this project selected Indian summer monsoon (ISM), El Niño–Southern Oscillation (ENSO), and Pacific Decadal Oscillation (PDO), which represent annual, interannual, and multidecadal climate modes, respectively, to investigate the relations between the climate modes and precipitation on the northern and southern slopes of Tianshan Mts. The linkages of the climate modes to precipitation of the northern and southern slopes were investigated by ensemble empirical mode decomposition (EEMD) and wavelet coherence analysis. The results show that these three climate modes are positively correlated with precipitation over entire Tianshan Mts. At annual scale, ISM strongly and almost equally affects precipitation on the northern and southern slopes. At interannual scales, ENSO mainly affects the precipitation of the northern slope, which is the major factor causing precipitation larger on the north than that on the south. At multidecadal scale, the effects of PDO on precipitation of northern and southern slopes are ambiguous.

Original languageEnglish (US)
Pages (from-to)453-465
Number of pages13
JournalTheoretical and Applied Climatology
Volume140
Issue number1-2
DOIs
StatePublished - Apr 1 2020

ASJC Scopus subject areas

  • Atmospheric Science

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