Stationary influence of the North Atlantic Oscillation on summer precipitation in the Central-Eastern Himalayas during 1994-2010

The Central-Eastern Himalayas (CEH), a key high-altitude barrier on the southern edge of the Tibetan Plateau, experiences concentrated summer rainfall and is a crucial water source for Asian countries. Understanding the interannual variability of summer precipitation across the CEH is essential for guiding efficient water management and supporting socio-economic development in South Asia. Here, we investigated the relationship between the CEH summer precipitation and all kinds of signals from the oceans. Analysis of long-term observations and reanalysis data revealed that the summer North Atlantic Oscillation (SNAO) has driven a positive summer precipitation in the CEH during 1994-2010. The SNAO triggered an anomalous anticyclone over Indian subcontinent during the specific period. The anticyclone directed low-level horizontal winds from North Indian toward the Himalayas’ southern slope. The southern slope forces the abnormal horizontal winds to generate a strong climbing flow component, leading changes in the precipitation distribution of CEH. Experiments with removing the plateau topographic features show that the positive precipitation distribution in the CEH shifts into a dipole-like pattern. The CEH was dominated by negative precipitation distribution after removing the plateau topography. All these results supported that the summer precipitation in the CEH during 1994-2010 was governed by the upstream atmospheric circulation from the Atlantic Ocean. While in other years, SNAO influences on CEH summer precipitation was not clear. This is due to the position shift of the SNAO-driven anticyclone to the south of the CEH. The position of SNAO-driven anticyclone modulates the coupled and decoupled relationship between SNAO and CEH summer precipitation variability. Therefore, understanding the dynamic links between the SNAO and CEH summer precipitation is key to enhancing precipitation prediction accuracy.