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The inter‐decadal variation of autumn rain of west China (ARWC) and its relationship with atmospheric circulation and sea surface temperature anomalies (SSTAs) was analysed. The intensity of ARWC shows significant inter‐decadal variability. The year 1990 is one of the abrupt change points of ARWC in both the southern and northern zone, and the year 2000 is another one in the northern zone. The inter‐annual correlation between the intensity of ARWC in the northern (southern) zone and the El Niño–Southern Oscillation continuously weakens (strengthens) from 1961. The relationship between the intensity of ARWC in the northern zone and atmospheric circulation of September–October mean significantly weakens after 2000, so does the relationship with the SSTAs in the equatorial central Pacific. On the contrary, the relationship between the intensity of ARWC in the southern zone and atmospheric circulation of September–October mean significantly strengthens after 1990, so does the relationship with the east–west contrast pattern of SSTAs in the equatorial central–western Pacific. The positive phase of the east–west contrast pattern of SSTAs in the equatorial central–western Pacific (i.e., when the tropical central [western] Pacific is colder [warmer] than normal) gradually strengthening and maintaining from the preceding spring to September–October is favourable for a stronger western Pacific subtropical high, which further facilitates northwards transportation of water vapour and provides better dynamic conditions for ARWC in the southern zone by strengthening the local Hadley circulation. [ABSTRACT FROM AUTHOR]

Accurate short-term climate predictions, specifically the prediction of dominant rain belts during flood seasons, represent a significant challenge, particularly in the absence of notable external forcing signal anomalies in the previous winter. To address this challenge, we propose a novel climate index based on an Auto-Encoder (AE) Neural Network that exhibits superior performance in indicating several significant precipitation events in the Yangtze and Huaihe River Basins under varying El Niño conditions. Notably, the novel climate index rectifies the discrepancy between the 2019/2020 Niño index and the 2020 summer precipitation. In order to understand the information source of AE, the causality between AE and other indices was further analyzed by Granger Causality. The results show that AE index mainly contains the information of subtropical high index and ocean index, which is consistent with previous studies. • AE obtained by Auto-encoder can make up for the "failure" of Nino index in abnormally heavy precipitation events. • In terms of magnitude and state, AE has better description of precipitation than Nino3.4. • The main indices of AE information are subtropical high-pressure index and sea surface temperature index. [ABSTRACT FROM AUTHOR]