The occurrence of extreme precipitation events during Indian Summer Monsoon Rainfall (ISMR) has increased significantly in recent decades. Natural spatio-temporal variability of extreme precipitation events in India has been linked to various climatic variables like El Niño Southern Oscillation (ENSO), Equatorial Indian Ocean Oscillation (EQUINOO), Pacific Decadal Oscillation (PDO), and Atlantic Multidecadal Oscillation (AMO). In this study, extreme precipitation indices are used to characterize the ISMR extremes and possible individual and coupled association with climatic variables identified using wavelet analysis. Region-based analysis revealed that ENSO, EQUINOO, PDO, and AMO influence extreme precipitation events on spatio-temporal scales. Variability of the duration of extreme precipitation events strongly depends on the ENSO at interannual scale compared to the other climate variables whereas, total precipitation greater than 95th percentile and maximum consecutive 5-day precipitation values were significantly coherent on inter-decadal scale with ENSO, EQUINOO, and PDO. It is also found that the climate variables together cause variability in ISMR extremes, particularly AMO-ENSO-EQUINOO and AMO-ENSO-PDO combinations explain the variability better than any other combination. An increase in the number of climate variables did not improve the coherence, since these climatic variables are correlated with each other. Further, the decomposition of wavelets at different scales shows that more than half of the grid points considered were significant at interdecadal and multidecadal scales even though they are designated with different time scales. This indicates that the non-stationary behavior of the ISMR extremes is directly linked to the climatic variables at higher scales.

近几十年来，印度夏季风降雨（ISMR）期间极端降水事件的发生显着增加。印度极端降水事件的自然时空变化与厄尔尼诺南方涛动 (ENSO)、赤道印度洋涛动 (EQUINOO)、太平洋年代际涛动 (PDO) 和大西洋多年代际涛动 (AMO) 等各种气候变量有关。在本研究中，极端降水指数用于表征 ISMR 极端值以及与使用小波分析确定的气候变量可能的个体和耦合关联。基于区域的分析表明，ENSO、EQUINOO、PDO 和 AMO 在时空尺度上影响极端降水事件。与其他气候变量相比，极端降水事件持续时间的变化在很大程度上取决于年际尺度上的 ENSO，而总降水量大于 95% 和最大连续 5 天降水值在年代际尺度上与 ENSO、EQUINOO 显着一致, 和 PDO。还发现气候变量共同导致 ISMR 极端值的变化，特别是 AMO-ENSO-EQUINOO 和 AMO-ENSO-PDO 组合比任何其他组合更好地解释了这种变化。气候变量数量的增加并没有提高一致性，因为这些气候变量是相互关联的。更远，不同尺度的小波分解表明，超过一半的考虑的网格点在年代际和多年代尺度上是显着的，即使它们被指定为不同的时间尺度。这表明 ISMR 极值的非平稳行为与更高尺度的气候变量直接相关。