The precipitation variability of wet and dry season at the interannual and interdecadal scales over eastern China (1901–2016): The impacts of the Pacific Ocean

Abstract. The spatiotemporal variability of rainfall in dry (October–March) and wet (April–September) seasons over eastern China is examined based on gridded rainfall dataset from University of East Angela Climatic Research Unit during 1901–2016. Principal component analysis is employed to identify the dominant variability modes, wavelet coherence is utilized to investigate the spectral characteristics of leading modes of precipitation and their coherences with the large-scale modes of climate variability, and Bayesian dynamical linear model is adopted to quantify the time-varying correlations between climate variability modes and rainfall in dry and wet seasons. Results show that first and second principal components (PCs) account for 34.2 % (16.1 %) and 13.4 % (13.9 %) of variance in dry (wet) season, and their changes are roughly coincident with phase shifts of the El Nino–Southern Oscillation (ENSO) in both seasons. The anomalous moisture fluxes responsible for the occurrences of precipitation events in eastern China are asymmetry during high and light rainfall years in dry (wet) season. ENSO has a 4- to 8-year signal of the statistically positive (negative) association with rainfall during dry (wet) season in eastern China. The statistically significant positive (negative) associations between Pacific Decadal Oscillation (PDO) and precipitation are found with 9- to 15-year (4- to 7-year) signal. The impacts of PDO on rainfall in eastern China exhibit multiple time scales as compared to ENSO episodes, while PDO triggers a stronger effect on precipitation in wet season than dry season. The interannual and interdecadal variations in rainfall over eastern China are substantially modulated by drivers originated from Pacific Ocean, the finding has meaningful implications for regional hydrologic predictability and water resources management.