Abstract
Abstract. In situ observations of summer (June through August, or JJA) albedo are presented for the period 2002–2017 from Haig Glacier in the Canadian Rocky
Mountains. The observations provide insight into the seasonal evolution and interannual variability of snow and ice albedo, including the effects of
summer snowfall, the decay of snow albedo through the melt season, and the potential short-term impacts of regional wildfire activity on glacier-albedo reductions. Mean JJA albedo (± 1σ) recorded at an automatic weather station in the upper ablation zone of the glacier was
αS=0.55 ± 0.07 over this period, with no evidence of long-term trends in surface albedo. Each summer the surface conditions
at the weather station undergo a transition from a dry, reflective spring snowpack (αS∼0.8) to a wet, homogeneous midsummer
snowpack (αS∼0.5) to exposed, impurity-rich glacier ice, with a measured albedo of 0.21 ± 0.06 over the study
period. The ice albedo drops to ∼ 0.12 during years of intense regional wildfire activity such as 2003 and 2017, but it recovers from this in
subsequent years. This seasonal albedo decline is well simulated through a parameterization of snow-albedo decay based on cumulative positive degree
days (PDDs), but the parameterization does not capture the impact of summer snowfall events, which cause transient increases in albedo and significantly
reduce glacier melt. We introduce this effect through a stochastic parameterization of summer precipitation events within a surface energy balance
model. The amount of precipitation and the date of snowfall are randomly selected for each model realization based on a predefined number of
summer snow events. This stochastic parameterization provides an improved representation of the mean summer albedo and mass balance at Haig Glacier.
We also suggest modifications to conventional degree-day melt factors to better capture the effects of seasonal albedo evolution in temperature-index or positive-degree-day melt models on mountain glaciers. Climate, hydrology, or glacier mass balance models that use these methods typically
use a binary rather than continuum approach to prescribing melt factors, with one melt factor for snow and one for ice. As alternatives, monthly
melt factors effectively capture the seasonal albedo evolution, or melt factors can be estimated as a function of the albedo where these data are
available.
Funder
Natural Sciences and Engineering Research Council of Canada
Subject
Earth-Surface Processes,Water Science and Technology
Reference79 articles.
1. Abermann, J., Kinnard, C., and MacDonell, S.:
Albedo variations and the impact of clouds on glaciers in the Chilean semi-arid Andes
J. Glaciol.,
60, 183–191, 2014.
2. Adhikari, S. and Marshall, S. J.: Influence of high-order mechanics on simulation of glacier response to climate change: insights from Haig Glacier, Canadian Rocky Mountains, The Cryosphere, 7, 1527–1541, https://doi.org/10.5194/tc-7-1527-2013, 2013.
3. Andreas, E. L.:
Parameterizing scalar transfer over snow and ice: a review,
J. Hydrometeorol.,
3, 417–432, 2002.
4. Aoki, T., Kuchiki, K., Niwano, M., Kodama Y., Hosaka M., and Tanaka, T.:
Physically based snow albedo model for calculating broadband albedos and the solar heating profile in snowpack for general circulation models,
J. Geophys. Res.,
116, D11114, https://doi.org/10.1029/2010JD015507, 2011.
5. Arendt, A. and Sharp, M. J.:
Energy balance measurements on a Canadian high Arctic glacier and their implications for mass balance modelling,
IAHS Publ. 256,
Symposium at Birmingham, 1 July 1999 – Interactions between the Cryosphere, Climate and Greenhouse Gases, 165–172, 1999.
Cited by
17 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献