Abstract

Climate-driven temperature variations manipulate the snowmelt process and affect various aspects of aquatic and terrestrial life. The objective of this study is to evaluate the impacts of sub-daily temperature fluctuations around the freezing temperature on the quantity and spatial distribution of macro-scale snowmelt simulations (i.e., over macro-scale basins and monthly or annual temporal scales). A macro-scale snow accumulation and ablation model was developed to account for sub-daily temperature fluctuations. Unlike other existing macro-scale models that rely upon a single daily average temperature, the new model incorporates minimum and maximum temperatures and their occurrence timing within the day in a hybrid temperature index method (HTIM). The model was applied to the Missouri River Basin (MRB) to simulate grid-based snowmelt for water years 2011 and 2012 and compared with the monthly snowmelt data from the SNOw Data Assimilation System (SNODAS), which is a physically-based energy and mass balance snow model. Also, the HTIM was compared with a standard TIM, in which only a daily average temperature was used for snowmelt simulations. Although the HTIM provided simulations comparable to the SNODAS snowmelt data (R2 = 0.9), overall results indicated that the TIM slightly outperformed the HTIM. When minimum temperatures fluctuated around the freezing temperature, HTIM underestimated the snowmelt over the MRB. However, HTIM showed a better performance particularly in the months when maximum temperatures fluctuated around the freezing temperature. Results suggested that the role of refreezing in the generation of snowmelt was overestimated by HTIM, which led to a more significant discrepancy between the SNODAS and HTIM snowmelt values in specific months. The findings from this study highlight the influence of sub-daily temperature fluctuations on macro-scale snowmelt simulations.

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