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

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.