In recent years, China has suffered from frequent extreme precipitation events, and predicting their future trends has become an essential part of the current research on this issue. Because of the inevitable uncertainties associated with individual models for climate prediction, this study uses a machine learning approach to integrate and fit multiple models. The results show that the use of several evaluation metrics provides better results than the traditional ensemble median method. The correlation coefficients with the actual observations were found to improve from about 0.8 to 0.9, while the correlation coefficients of the precipitation amount (PRCPTOT), very heavy precipitation days (R20mm), and extreme precipitation intensity (SDII95) reached 0.95. Based on this, the precipitation simulations of moderate forced scenario for sharing socio-economic path (SSP2-4.5) from 27 coupled models in the Coupled Model Intercomparison Project Phase 6 (CMIP6) were used to explore potential changes in future extreme precipitation events in China and to calculate the distribution and trends of the PRCPTOT, extreme precipitation amount (R95pTOT), maximum consecutive 5-day precipitation (Rx5day), precipitation intensity (SDII), SDII95, and R20mm for the early 21st century (2023–2050), mid-21st century (2051–2075), and late 21st century (2076–2100), respectively. The results showed that the most significant increase in extreme precipitation indices is expected to occur by the end of the century, with the R95pTOT, Rx5day, and SDII95 increasing by 13.73%, 9.43%, and 9.34%, respectively, from the base period. The remaining three precipitation indexes, the PRCPTOT, SDII, and R20mm, also showed increases of 8.77%, 6.84%, and 4.02%, respectively. Additionally, there were apparent differences in the spatial variation of extreme precipitation. There were significant increasing trends of extreme precipitation indexes in central China and northeast China in the three periods, among which the total annual precipitation showed an increasing trend in central and northern China and a decreasing trend in western and south China. An increasing trend of annual precipitation intensity was found to be mainly concentrated in central China and south China, and the annual precipitation frequency showed a larger increasing trend at the beginning of this century. The annual precipitation frequency showed an increasing trend in the early part of this century. In general, all the indices showed an overall increasing trend in the future period, with the PRCPTOT, Rx5day, and SDII95 showing the most significant overall increasing trends.

Tibetan Plateau (TP) vortices and the related 10–30-day intraseasonal oscillation in May–September 1998 are analyzed using the twice-daily 500-hPa synoptic weather maps, multiple reanalysis datasets, and satellite-retrieved brightness temperature. During the analysis period, distinctively active and suppressed periods of TP vortices genesis are noticed. In 1998, nine active periods of TP vortices occurred, which were largely clustered by the cyclonic circulations associated with the intraseasonal oscillation of 500-hPa relative vorticity. In addition to the well-recognized 30–60-day oscillation, the clustering of TP vorticity in the 1998 summer are more likely modulated by the 10–30-day oscillation, because all active periods of TP vortices fall into the positive phase of the 10–30-day oscillation in 1998. Even in the negative (i.e., anticyclonic) phases of the 30–60-day oscillation, the positive (i.e., cyclonic) 500-hPa 10–30-day oscillation can excite the clustering of TP vortices. This result indicates that the 10–30-day oscillation more directly modulates the activities of TP vortices by providing a favorable (unfavorable) cyclonic (anticyclonic) environment. The analysis of the 10–30-day atmospheric oscillation suggests that the westerly trough disturbances, in conjunction with convective instability due to low-level warm advection from the Indian monsoon region, are important in the clustering of TP vortex activities. In particular, the moisture flux from the southwest boundary of TP is essential to the accumulation of convective energy. Thus, a better understanding and prediction of the 10–30-day intraseasonal oscillation is needed to advance the extended-range forecasting of TP vortices and their downstream impacts on the weather and climate over East Asia.

In this study, we investigated the impact of the spring North Pacific Oscillation (NPO) on typhoon frequency over the Western North Pacific (WNP, north of the equator and west of dateline). To reduce the statistical uncertainty, all the data we used have been excluded the El Nino/Southern Oscillation signals. We found that the spring NPO positively correlated with the annual typhoon number over the WNP (hereafter TNWNP) during the period 1968–2010, with a correlation coefficient of 0.62 (above the 99% significance level). When the Northern Low and Southern High pattern over the north Pacific weakens, the TNWNP tends to increase. A positive phase of spring NPO is associated with the tropical circulation and sea surface temperature (SST) anomalies in the North Pacific, which may lead to unfavorable dynamical and thermal conditions for typhoon genesis over the WNP during JJAS. The negative anomaly of SST over the WNP, associated with the positive spring NPO anomaly, is connected to the tropical atmospheric circulations from spring to summer via good oceanic seasonal persistence and air–sea interaction. Thus, the spring NPO‐related variability of the tropical atmospheric circulation as well as the SST can affect typhoon activity over the WNP. In addition, the spring NPO can also be adopted as a predictor for the summer rainfall in South China, since the spring NPO can modulate the WNP SST and western Pacific subtropical high from spring to summer.

Global precipitation measurement (GPM) is one of the effective means employed to observe orographic precipitation, and its inversed GPM DPR data can be used to study the microphysical structure of precipitation particles. This study considers statistics on convective precipitation (CP) and stratiform precipitation (SP) events over three types of terrain (plains, mountains, and high mountains) using the DPR onboard the GPM Core Observatory from May to September of 2014–2021 to analyze the vertical structure of heavy CP and SP. In mountain areas and high mountain areas, the updraft rendered by topography or seeder-feeder mechanism is not only conducive to the collision and merger of raindrops into large raindrops, but also increases the concentration of small drops, which is the main reason why the occurrence probability of not only large but also small raindrops increases and the horizontal distribution domain of mass weighted average raindrop diameter (D_m) widens. For heavy SP, the occurrence probability of medium-diameter precipitation particles below the freezing height (FzH) over high mountains is greater than those over plains. The precipitation particles above 10 km altitude of high mountains have characteristics, such as lower droplet number concentration and larger diameter, compared with those over plains. Furthermore, the study also analyzed the correlation between storm top altitude (STA) and D_m, water vapor and STA respectively. This study is helpful to further understand the effect of topography on heavy precipitation through cloud microphysical processes and the vertical structure of precipitation.