The Himalayas host some of the most sensitive parts of the cryosphere. Fast and ill planned development proves to be ill-fated, for both the cryosphere and its many human neighbors. The complex geography of the region poses a challenge not only to ground based observations, but also to understanding the processes driving the cryosphere and modeling its behavior. In this study we focus on the western Himalayas. An examination of precipitation of the region through regression, wavelet analysis, and machine learning suggested various climate indices indicative of ocean atmosphere coupling states to be drivers of snow cover. Seasons and sub regions show variation in sensitivity to these remote forcings. Finally, causal inference is employed to establish teleconnections as drivers and predictors of snow fall and snow cover.
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Sengupta et al. (2024) studied this question.
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