Spatiotemporal Variability of Snow Parameters over Himalayan–Tibetan Region Utilizing ERA-5 Data

This study aims at understanding the spatiotemporal pattern of snow cover, snow depth and its albedo in the Himalayan–Tibetan (H–T) region and to comprehend its relationship with atmospheric variables over the region. Snow cover and depth indicate a pattern of precipitation and albedo is its property which is also governed by geographical location, cycle of snow accumulation and ablation and atmospheric parameters. ERA-5 ARD (Analysis Ready Data) for a span covering 20 years, i.e., from 2000 to 2020 has been utilized to carry out this study. A comparative analysis of parameters has also been carried out broadly corresponding to Western, Central and Eastern Himalayan regions. Analyses over these three regions indicate that snow cover is highest in the Western Himalayas compared to the Central and Eastern Himalayas. Further, the temporal domain has been divided into seasonal classes as accumulation and ablation time. Snow depth has been observed to be inversely dependent on air temperature and directly associated with relative humidity during accumulation time. Examination of monthly snow depth with air temperature and relative humidity across these regions revealed varying characteristics in each terrain with respect to the seasons. Nonlinear association has been observed between air temperature and snow depth during accumulation (with r2 values between 0.78 and 0.86) and linear during ablation (with r2 values between 0.85 and 0.86) over all the three considered regions. Snow albedo has been observed to be low during ablation (with values less than 0.70) and high during accumulation (with values greater than 0.70). These characteristics of snow albedo indicate the occurrence of fresh snow present in the study areas. An observed difference in snow albedo compared to the amount of snow area present in the region is attributed to variations in the distribution of snow across the terrain. Understanding this relationship is crucial for informed climate change mitigation strategies and water resource management, as it directly impacts the livelihoods of millions and the ecological balance in the region.