Abstract
AbstractRecent progress has been made in quantifying snowmelt in the Himalaya. Although the conditions are favorable for refreezing, little is known about the spatial variability of meltwater refreezing, hindering a complete understanding of seasonal snowmelt dynamics. This study aims to improve our understanding about how refreezing varies in space and time. We simulated refreezing with the seNorge (v2.0) snow model for the Langtang catchment, Nepalese Himalaya, covering a 5-year period. Meteorological forcing data were derived from a unique elaborate network of meteorological stations and high-resolution meteorological simulations. The results show that the annual catchment average refreezing amounts to 122 mm w.e. (21% of the melt), and varies strongly in space depending on elevation and aspect. In addition, there is a seasonal altitudinal variability related to air temperature and snow depth, with most refreezing during the early melt season. Substantial intra-annual variability resulted from fluctuations in snowfall. Daily refreezing simulations decreased by 84% (annual catchment average of 19 mm w.e.) compared to hourly simulations, emphasizing the importance of using sub-daily time steps to capture melt–refreeze cycles. Climate sensitivity experiments revealed that refreezing is highly sensitive to changes in air temperature as a 2°C increase leads to a refreezing decrease of 35%.
Highlights
Seasonal snow contributes significantly to the annual runoff in the Himalaya (Bookhagen and Burbank, 2010; Lutz and others, 2014)
This study aims to contribute to a better understanding of how refreezing varies in space and time at a catchment scale in the Himalaya
The std dev.s of the melt parameters (Tm, Ft and Fsr) are based on the literature, but we reduced the std dev.s as these parameters are estimated from observed snow ablation time series in this study (0.5°C, 0.0125 mm w.e. h−1 °C−1 and 0.0004 mm w.e. h−1 °C−1) (Pellicciotti and others, 2012; Ragettli and others, 2015; Stigter and others, 2017)
Summary
Seasonal snow contributes significantly to the annual runoff in the Himalaya (Bookhagen and Burbank, 2010; Lutz and others, 2014). Processes related to snowmelt runoff generation remain not fully understood, as the spatial–temporal variability of meltwater refreezing in High Mountain Asia is rarely studied (Saloranta and others, 2019; Lund and others, 2020) and existing point-scale refreezing measurements are likely not representative of catchments with extreme topography (e.g. Ayala and others, 2017a; Saloranta and others, 2019). As refreezing prevents meltwater to be released as runoff (Samimi and Marshall, 2017), a detailed understanding of refreezing is important for the quantification of timing and volume of snowmelt runoff. Previous studies have shown that substantial portions of meltwater refreeze in alpine regions (Fujita and others, 1996; Fujita and Ageta, 2000; Mölg and others, 2012; Ayala and others, 2017a, 2017b; Samimi and Marshall, 2017; Saloranta and others, 2019; Pritchard and others, 2020; Stigter and others, 2021), thereby increasing snowpack persistence and causing a delay of meltwater runoff from the snowpack. The refreezing has been estimated to account for up to 100% of the total melt, with a large spatial and temporal variation, predominantly related to elevation and air temperature (Ayala and others, 2017a), and with representative values ranging between 10 and 36%
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