Analyzing and forecasting the Indian Summer Monsoon Rainfall (ISMR) is vital for South Asia’s socio-economic stability. Using 35 climate models from the latest generation of the Coupled Model Intercomparison Project (CMIP6) to simulate and project ISMR, we integrated statistical methods, such as Taylor diagrams, comprehensive rating indicators, and interannual variability scores, to compare performance differences between various models and analyze influencing mechanisms. The results show that the majority of models effectively simulate the climatology of the ISMR. However, they exhibit limitations in accurately capturing its interannual variability. Importantly, we observed no significant correlation between a model’s ability to simulate ISMR’s general climatology and its accuracy in representing annual variability. After a comprehensive assessment, models, like BCC-ESM1, EC-Earth3-Veg, GFDL-CM4, INM-CM5-0, and SAM0-UNICON were identified as part of the prime model mean ensemble (pMME), demonstrating superior performance in spatiotemporal simulations. The pMME can accurately simulate the sea surface temperature changes in the North Indian Ocean and the atmospheric circulation characteristics of South Asia. This accuracy is pivotal for CMIP6’s prime models to precisely simulate ISMR climatic variations. CMIP6 projections suggest that, by the end of the 21st century, ISMR will increase under low, medium, and high emission scenarios, with a significant rise in rainfall under the high emission scenario, especially in the western and northern parts of India. Among the pMME, the projected increase in rainfall across India is more moderate, with an estimated increase of 30%. The findings of this study suggest that selecting the best models for regional climate downscaling research will project regional climate changes more accurately. This provides valuable recommendations for model improvements in the Indian region.

The El Niño–Southern Oscillation (ENSO) plays an important role in pre-flood season (PFS) precipitation over South China. In this work, the analysis of observational and reanalysis data shows that PFS precipitation is closely related to the onset time of El Niño events. The PFS precipitation tended to be higher (lower) than normal for spring (summer) El Niño events during the 1979–2016 period. Our composite analyses reveal that, for spring El Niño events, the sea surface temperature (SST) anomaly in the central-east equatorial Pacific (CEEP) Ocean provided favourable large-scale circulation for abundant PFS precipitation, where the Hadley cell served as a bridge. In the year following an El Niño event, SST anomalies in the CEEP persist from January to June, while for April-May-June (AMJ) positive SST anomalies are seen offshore near China. These anomalies are associated with the AMJ–enhanced convective instability over South China through a weakened Walker circulation and a zonal teleconnection wavetrain pattern at 700 hPa in the northern hemisphere. Meanwhile, a weakened 200 hPa anticyclonic shear was seen over the Indochina Peninsula. There was a southwestward shift of the 500 hPa western Pacific subtropical high, and anomalous 850 hPa southwesterly wind-enhanced water vapour and warm advection toward South China. Therefore, the circulation-induced moisture environment and dynamical conditions both facilitated enhanced PFS precipitation over South China. For summer El Niño events, the moisture environment and dynamical conditions were unfavourable for producing precipitation, which resulted in below-normal PFS precipitation levels. Categorizing El Niño events by the onset time is very important because it provides useful information for predicting PFS precipitation with lead times of two or three seasons.

For this paper, a new global atmospheric model (Global-to-Regional Integrated forecast SysTem; GRIST) with improved sub-grid scale orographic parameterization was verified and assessed, with an emphasis on the precipitation caused by typhoons. Four typical typhoon cases were selected for the verification of the model. The results indicate that, compared to the control experiments, the sensitivity experiments consistently simulated the trends in the three-hour cumulative precipitation changes and the high-value regions of total precipitation better. However, the improved experiments only had an ameliorating effect on the cumulative precipitation modelling biases for Typhoon LEKIMA and Typhoon HAGUPIT, not all of them. Precipitation bias is smaller on flat land than that on mountainous land, but the precipitation bias on windward/leeward slopes depends on the typhoon case. Precipitation modelling accuracy varies considerably between flat and mountainous terrain but very little between windward and leeward slopes. The precipitation simulation is poor for all terrains, with large precipitation thresholds in three typhoon cases, but for Typhoon HOTA, after improving the terrain, the model has the ability to forecast the heavy rainfall scenarios of the mountainous terrain.

Winter precipitation over South China tended to be much higher than normal for the spring El Niño events during 1979–2016. For the spring El Niño events, the meridional and zonal circulations served as a bridge, linking the warmer sea surface temperature (SST) in the eastern equatorial Pacific (EEP) and South China winter precipitation. This possible physical process can be described as follows: During boreal winter, a positive SST anomaly in the EEP was concurrent with strong anomalous convection activity over South China via anomalous Walker circulation, an anomalous Hadley Cell along 110°–130° E, and a zonal westward teleconnection wave train pattern at 700 hPa in the Northern Hemisphere. In addition, an anomalous pumping effect at 200 hPa contributed to the convective activity. Meanwhile, the western Pacific subtropical high moved southwards and strengthened at 500 hPa, and abnormal southwesterly winds brought plentiful water vapor to South China at 850 hPa. All these factors favored an increase in precipitation over South China. For the summer El Niño events, the aforementioned anomalies were weaker, which resulted in a precipitation close to normal over South China.

El Niño–Southern Oscillation (ENSO) has large impacts on Australia’s rainfall. A composite analysis technique was utilized to distinguish the impact of onset time of El Niño on summer rainfall over southeastern Australia. Summer rainfall tended to be lower than normal in austral autumn El Niño events during December–January–February (DJF) and higher than normal in austral winter El Niño events, in 1980–2017. During autumn El Niño events, the Walker circulation and meridional cells served as a bridge, linking the warmer sea surface temperature (SST) in the eastern equatorial Pacific (EEP) and lower summer rainfall over southeastern Australia. This physical process can be described as follows: During DJF, a positive SST anomaly in the EEP was concurrent with anomalous downdraft over southeastern Australia via zonal anomalous Walker circulation, meridional anomalous cells along 170° E–170° W, and a Pacific South American (PSA) teleconnection wave train at 500 hPa. In addition, an anomalous convergence at 200 hPa depressed the convection. Meanwhile, an 850 hPa abnormal westerly was not conducive to transport marine water vapor into this area. These factors resulted in below-normal rainfall. During winter El Niño events, a positive SST anomaly in the central equatorial Pacific (CEP) and the changes in Walker circulation and meridional cells were weaker. The PSA teleconnection wave train shifted westward and northward, and there was a low-level anomalous ascent over southeastern Australia. At the western flank of the anomalous anticyclone, northerly transported water vapor from the ocean to southeastern Australia resulted in a sink of water vapor over this area. The development of low-level convective activity and the plentiful water vapor supply favored more rainfall over southeastern Australia. Onset time of El Niño may be a useful metric for improving the low predictive skill of southeastern Australian summer rainfall.

In this paper, precipitation data from the Tropical Rainfall Measuring Mission (TRMM), together with atmospheric reanalysis data, are employed to identify warm-season precipitation (1998–2014) changes and their association with rapid urbanization in south China. Three urban clusters (Chenyu, Yangtze Delta, and Fujian Guangdong coast) are focused. The results reveal that, for the inland Chengyu urban cluster, a lack of precipitation trend is likely due to insignificant trends in convective available potential energy (CAPE) and total column water vapor (TCWV). They are likely resulted from a reduced local moisture recycling in urban areas, balanced by an increased evapotranspiration of rural areas, together with a stable advection of water vapor input. For the Yangtze River Delta urban cluster, a negative trend in precipitation is associated with a slightly decreased CAPE and an increased TCWV, but is very likely related to urbanization induced an increased planetary boundary layer (PBL) and reduced land surface evaporation. For the Fujian Guangdong coast urban cluster, a marked positive precipitation trend is well explained by positive trends in CAPE and TCWV. The increased precipitation likely benefits from enhanced moisture recycling due to improved vegetation cover in rural areas, and enhanced advection moisture inputs due to urbanization along the coast. These results suggest urbanization effects on precipitation vary with regional conditions. In the coastal area, urbanization enhances sea breezes, which may benefit precipitation if sea breezes go along with the prevailing moisture. In inland area, urbanization likely leads to a warmer-dryer climate if large-scale land cover keeps stationary.