Effects of interaction of multiple large-scale atmospheric circulations on precipitation dynamics in China

Dong，Haixia1; Huang，Shengzhi1; Wang，Hao2; Shi，Haiyun3; Singh，Vijay P.4,5; She，Dunxian6; Huang，Qiang1; Leng，Guoyong7; Gao，Liang8; Wei，Xiaoting1; Peng，Jian9,10

2024-05-01

10.1016/j.scitotenv.2024.171528

Science of the Total Environment   影响因子和分区

0048-9697

1879-1026

Different scenarios of precipitation, that lead to such phenomena as droughts and floods are influenced by concurrent multiple teleconnection factors. However, the multivariate relationship between precipitation indices and teleconnection factors, including large-scale atmospheric circulations and sea surface temperature signals in China, is rarely explored. Understanding this relationship is crucial for drought early warning systems and effective response strategies. In this study, we comprehensively investigated the combined effects of multiple large-scale atmospheric circulation patterns on precipitation changes in China. Specifically, Pearson correlation analysis and Partial Wavelet Coherence (PWC) were used to identify the primary teleconnection factors influencing precipitation dynamics. Furthermore, we used the cross-wavelet method to elucidate the temporal lag and periodic relationships between multiple teleconnection factors and their interactions. Finally, the multiple wavelet coherence analysis method was used to identify the dominant two-factor and three-factor combinations shaping precipitation dynamics. This analysis facilitated the quantification and determination of interaction types and influencing pathways of teleconnection factors on precipitation dynamics, respectively. The results showed that: (1) the Atlantic Multidecadal Oscillation (AMO), EI Niño-Southern Oscillation (ENSO), East Asia Summer Monsoon (EASM), and Indian Ocean Dipole (IOD) were dominant teleconnection factors influencing Standardized Precipitation Index (SPI) dynamics; (2) significant correlation and leading or lagging relationships at different timescales generally existed for various teleconnection factors, where AMO was mainly leading the other factors with positive correlation, while ENSO and Southern Oscillation (SO) were mainly lagging behind other factors with prolonged correlations; and (3) the interactions between teleconnection factors were quantified into three types: enhancing, independent and offsetting effects. Specifically, the enhancing effect of two-factor combinations was stronger than the offsetting effect, where AMO + NAO (North Atlantic Oscillation) and AMO + AO (Atlantic Oscillation) had a larger distribution area in southern China. Conversely, the offsetting effect of three-factor combinations was more significant than that of the two-factor combinations, which was mainly distributed in northeast and northwest regions of China. This study sheds new light on the mechanisms of modulation and pathways of influencing various large-scale factors on seasonal precipitation dynamics.

Interaction effects Multiple wavelet coherence Partial wavelet coherence Standardized precipitation index Teleconnection factors

SCI ; EI

英语

其他

ENVIRONMENT/ECOLOGY

2-s2.0-85187199344

Scopus

1.State Key Laboratory of Eco-Hydraulic in Northwest Arid Region of China,Xi'an University of Technology,Xi'an,710048,China
2.China Institute of Water Resources and Hydropower Research,State Key Lab Simulat & Regular Water Cycle River,Beijing,100038,China
3.Shenzhen Key Laboratory of Precision Measurement and Early Warning Technology for Urban Environmental Health Risks,School of Environmental Science and Engineering,Southern University of Science and Technology,Shenzhen,518055,China
4.Department of Biological and Agricultural Engineering & Zachry Department of Civil and Environmental Engineering,Texas A&M University,College Station,77843,United States
5.National Water & Energy Center,UAE University Al Ain,United Arab Emirates
6.State Key Laboratory of Water Resources and Hydropower Engineering Science,Wuhan University,Wuhan,430072,China
7.Key Laboratory of Water Cycle and Related Land Surface Processes,Institute of Geographic Sciences and Natural Resources Research,Chinese Academy of Sciences,Beijing,100101,China
8.State Key Laboratory of Internet of Things for Smart City and Department of Ocean Science and Technology,University of Macau,Macao,999078,China
9.Department of Remote Sensing,Helmholtz Centre for Environmental Research–UFZ,Leipzig,Permoserstrasse 15,04318,Germany
10.Remote Sensing Centre for Earth System Research,Leipzig University,Leipzig,04103,Germany

Dong，Haixia,Huang，Shengzhi,Wang，Hao,et al. Effects of interaction of multiple large-scale atmospheric circulations on precipitation dynamics in China[J]. Science of the Total Environment,2024,923.

Dong，Haixia.,Huang，Shengzhi.,Wang，Hao.,Shi，Haiyun.,Singh，Vijay P..,...&Peng，Jian.(2024).Effects of interaction of multiple large-scale atmospheric circulations on precipitation dynamics in China.Science of the Total Environment,923.

Dong，Haixia,et al."Effects of interaction of multiple large-scale atmospheric circulations on precipitation dynamics in China".Science of the Total Environment 923(2024).