Abstract

Snow darkening by deposited light-absorbing particles (LAP) has the potential to accelerate snowmelt and shift the snow melt-out date. Here we investigate the sensitivity of the seasonal snow cover duration to changes in LAP at a high altitude valley site in the Central Himalayas, India. First, the variation of the albedo of the seasonal snow was emulated using two seasons of automatic weather station (AWS) data and applying a constant, but realistic deposition of LAP to the snow. Then, the number of days with snowmelt were evaluated based on the estimated net energy budget of the seasonal snow cover and the derived surface temperature. The impact on the energy budget by LAP combined with the melt-day analysis resulted in very simple relations to determine the contribution of LAP to the number of days with snowmelt of the seasonal snow in Himalaya. Above a concentration of 1 ng g-1 (Elemental Carbon equivalent, ECeq, which in this study includes EC and the absorption equivalent EC contribution by other light absorbing particles, such as mineral dust) in new snow, the number of days with snowmelt can be estimated by; days=0.0109(log⁡(〖EC〗_eq )+1)PP±0.0033(log⁡(〖EC〗_eq )+1)PP, where PP is the seasonal precipitation in mm snow water equivalent. A change in ECeq by a factor of two corresponds to about 1/3 of a day per 100 mm precipitation. Although the change in the number of days with melt caused by the changes in ECeq is small, the estimated total change in the snow melt-out date by LAP can be significant. For our realistic base case scenario for the Sunderdhunga Valley, Central Himalayas, India, of ECeq=100 ng g-1 and PP=400 mm, this yields in an advancement of the melt-out date of about 13 days.

Highlights

  • Seasonal snow cover in the Himalaya is an integral component of the regional hydrological cycle, with the timing of the melting phase being crucial for the supply of fresh water with growing importance at increasing altitudes (e.g. Armstrong et al, 2018; Mimeau et al, 2019)

  • Based on automatic weather station (AWS) data and an important assumption of a constant light-absorbing particles (LAP) deposition, a set of very simplified equations (10-13) to calculate the shift in snow melt-out date were derived. To arrive at these equations, a first step consisted of displaying that the observed daily variation in albedo could be emulated based on the assumption about constant LAP deposition and only two other variables from the AWS, namely air temperature and snow depth

  • By combining the information from this sequence the potential contribution from LAP to the #SM be estimated based on the LAP content and amount of precipitation

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Summary

Introduction

Seasonal snow cover in the Himalaya is an integral component of the regional hydrological cycle, with the timing of the melting phase being crucial for the supply of fresh water with growing importance at increasing altitudes (e.g. Armstrong et al, 2018; Mimeau et al, 2019). The model took into account the absorptivity of the snow and the amount of incoming shortwave radiation, as well as the number of days with a temperature above 0 °C, to estimate a summer snowmelt rate increase of up 6.3% due to LAP. Through analysis of these two seasons and a series of assumptions and simplifications, the complex system of LAP and albedo reduction is condensed down into a dependence of only a few variables With these simplified relations we attempt to answer the question: what is the contribution to the number of days with snowmelt from a given change of LAP in the seasonal snow for the study region?. The results are combined into simple relations to estimate the influence on the contribution of LAP to the number of days with snowmelt, based on the LAP content in the snowpack and the seasonal precipitation

Automatic weather station
Light-absorbing particles
Effective grain size, pristine albedo and specific surface area of snow
Albedo reduction by LAP
Influence from ground albedo and adjustment of parameter d
Comparison between observed and parameterized albedo
Relative contribution to net SW radiation due to LAP
Melt days
Findings
Discussion and conclusions
Full Text
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