Xinjiang is a major part of China’s arid region and its water resource is extremely scarcity. The change in precipitation amounts and extremes is of significant importance for the reliable management of regional water resources in this region. Thus, this study explored the spatiotemporal changes in extreme precipitation using the Mann–Kendall (M–K) trend analysis, mutation test, and probability distribution functions, based on the observed daily precipitation data from 89 weather stations in Xinjiang, China during 1961–2018. We also examined the correlations between extreme precipitation and climate indices using the cross-wavelet analysis. The results indicated that the climate in Xinjiang is becoming wetter and the intensity and frequency of extreme precipitation has begun to strengthen, with these trends being more obvious after the 1990s. Extreme precipitation trends displayed spatial heterogeneity in Xinjiang. Extreme precipitation was mainly concentrated in mountainous areas, northern Xinjiang, and western Xinjiang. The significant increasing trend of extreme precipitation was also concentrated in the Tianshan Mountains and in northern Xinjiang. In addition, the climate indices, North Atlantic Oscillation, Atlantic Multidecadal Oscillation, Multivariate ENSO Index and Indian Ocean Dipole Index had obvious relationships with extreme precipitation in Xinjiang. The relationships between the extreme precipitation and climate indices were not clearly positive or negative, with many correlations advanced or delayed in phase. At the same time, extreme precipitation displayed periodic changes, with a frequency of approximately 1–3 or 4–7 years. These periodic changes were more obvious after the 1990s; however, the exact mechanisms involved in this require further study.

The Tibetan Plateau is among the region’s most sensitive areas to global climate change. The observation data from 113 meteorological stations on the Tibetan Plateau and surrounding regions in China for 1971–2017 were used to analyze the periodic oscillations and trends in precipitation and extreme precipitation on multiple time scales to ensemble empirical mode decomposition. The relationship between extreme precipitation and sea-surface temperature (SST) anomalies was also explored. The results were as follows. (1) The timing of extreme-precipitation events in the highlands is consistent, with increased total precipitation and increased frequency, intensity, and extreme values of extreme precipitation. (2) Changes in temperature and precipitation are not completely synchronized. The total extreme precipitation, number of extreme-precipitation days, maximum single-day precipitation, and extreme single-day precipitation intensity all showed increases with fluctuations; the quasi-3-year oscillation contributes the most to the extreme precipitation. PRCPTOT is most strongly correlated with R10 and R95p. (3) The spatiotemporal patterns of the first and second empirical orthogonal function modes of the indices differed significantly and were not spatiotemporally uniform, but exhibited local clustering. (4) The Indian Ocean Warm Pool Strength and Western Pacific Warm Pool Strength indices were most highly correlated with each extreme-precipitation index, and the timings of the extreme-precipitation events lagged behind those of the SST anomalies. This study improves our understanding of extreme precipitation events in the context of climate warming and provides a basic analysis for the further assessment and prediction of extreme precipitation on the Tibetan Plateau and the surrounding ecologically fragile areas.