Snow and blue-ice distribution patterns on the coastal Antarctic Ice Sheet

Liston, Glen E.; Winther, Jan‐Gunnar; Bruland, Oddbjørn; Elvehøy, Hallgeir; Sand, Knut; Karlöf, Lars

doi:10.1017/s0954102000000109

Cited by 51 publications

(40 citation statements)

References 18 publications

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“…SnowTran-3D is a three dimensional, physically based model which simulates snow-depth evolution resulting from wind-blown snow. The model was originally developed and validated in the arctic tundra of Alaska but has since its introduction been applied in a wide range of landscapes (Green et al, 1999;Liston et al, 2000;Prasad et al, 2001;Hiemstra et al, 2002;Liston and Sturm, 2002;Hasholt et al, 2003;Bruland et al, 2004;Hiemstra et al, 2006). Recently, the use of modelled wind fields has allowed to apply and validate the model in the high mountain area of the Berchtesgaden National Park (Bernhardt et al, 2008a, b 1 ).…”

Section: Wind-induced Snow Transportmentioning

confidence: 99%

Is snow sublimation important in the alpine water balance?

et al. 2008

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Abstract. In alpine terrain, snow sublimation represents an important component of the winter moisture budget, representing a proportion of precipitation which does not contribute to melt. To quantify its amount we analyze the spatial pattern of snow sublimation at the ground, from a canopy and from turbulent suspension during wind-induced snow transport for a high alpine area in the Berchtesgaden National Park (Germany), and we discuss the efficiency of these processes with respect to seasonal snowfall. Therefore, we utilized interpolated meteorological recordings from a network of automatic stations, and a distributed simulation framework comprising validated, physically based models. The applied simulation tools were: a detailed model for shortwave and longwave radiative fluxes, a mass and energy balance model for the ground snow cover, a model for the microclimatic conditions within a forest canopy and related snow-vegetation interactions including snow sublimation from the surface of the trees, and a model for the simulation of wind-induced snow transport and related sublimation from suspended snow particles. For each of the sublimation processes, mass rates were quantified and aggregated over an entire winter season. Sublimation from the ground and from most canopy types are spatially relatively homogeneous and sum up to about 100 mm of snow water equivalent (SWE) over the winter period. Accumulated seasonal sublimation due to turbulent suspension is small in the valley areas, but can locally, at very wind-exposed mountain ridges, add up to more than 1000 mm of SWE. The fraction of these sublimation losses of winter snowfall is between 10 and 90%.

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Section: Wind-induced Snow Transportmentioning

confidence: 99%

Is snow sublimation important in the alpine water balance?

et al. 2008

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“…A detailed description of the snow density development and the other process formulations is given by Liston and Elder (2006) and Liston and Sturm (1998). SnowTran3D has proven its applicability for a wide range of environments from Arctic plains (Liston and Sturm, 1998;Liston and Sturm, 2002) to mountainous terrain (Greene et al, 1999;Liston et al, 2000;Prasad et al, 2001;Hiemstra et al, 2003Hiemstra et al, , 2006Hasholt et al, 2003;Bruland et al, 2004;Bernhardt et al, 2009). …”

Section: Modelmentioning

confidence: 99%

“…vegetation strips (Pomeroy et al, 1993;Liston and Sturm, 1998;Hiemstra et al, 2003). The resulting heterogeneity of snow cover has effects on the energy balance, the total amount of snow water equivalent (SWE) and the timing and intensity of snowmelt runoff as well as avalanche risk (Liston, 1995;Liston and Sturm, 1998;Liston et al, 2000;Lehning et al, 2006). Furthermore, snow transport may be responsible for an increase in sublimation rates of the snow cover itself as well as of airborne snow particles (Strasser et al, 2008).…”

Section: Introductionmentioning

confidence: 99%

High resolution modelling of snow transport in complex terrain using downscaled MM5 wind fields

et al. 2010

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Abstract. Snow transport is one of the most dominant processes influencing the snow cover accumulation and ablation in high mountain environments. Hence, the spatial and temporal variability of the snow cover is significantly modified with respective consequences on the total amount of water in the snow pack, on the temporal dynamics of the runoff and on the energy balance of the surface. For the present study we used the snow transport model SnowModel in combination with MM5 (Penn State University -National Center for Atmospheric Research MM5 model) generated wind fields. In a first step the MM5 wind fields were downscaled by using a semi-empirical approach which accounts for the elevation difference of model and real topography, and vegetation. The target resolution of 30 m corresponds to the resolution of the best available DEM and land cover map of the test site Berchtesgaden National Park. For the numerical modelling, data of six automatic meteorological stations were used, comprising the winter season (September-August) of 2003/04 and 2004/05. In addition we had automatic snow depth measurements and periodic manual measurements of snow courses available for the validation of the results. It could be shown that the model performance of SnowModel could be improved by using downscaled MM5 wind fields for the test site. Furthermore, it was shown that an estimation of snow transport from surrounding areas to glaciers becomes possible by using downscaled MM5 wind fields.

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“…The advantages of using SnowModel are that, within SnowModel, SnowTran-3D simulates distribution by wind-blown snow, spatial snow deposition patterns (evolution of snowpack) in response to erosion and deposition, and EnBal calculates energy flux available for snowmelt and blowing-snow sublimation. SnowTran-3D simulations have been compared against observations in glacier and glacier-free alpine, Arctic, and Antarctic landscapes (Greene et al, 1999;Liston et al, 2000;Prasad et al, 2001;Hiemstra et al, 2002;Liston and Sturm, 2002;Hasholt et al, 2003;Bruland et al, 2004). In Mernild et al (2006aMernild et al ( ,b, 2007a, spatially distributed SnowModel simulations of snow cover extent for Zackenberg and Sermilik, Ammassalik Island (southeast Greenland, 65°41 0 N; 37°48 0 W), were compared with field observations: snow pit depths, glacier winter mass balance, depletion curves, photographic time lapses, and (after DHI (1993) and Refsgaard and Storm (1995)).…”

Section: Modelling Snow Distribution and Surface Melt (Snowmodel)mentioning

confidence: 99%

Climatic control on river discharge simulations, Zackenberg River drainage basin, northeast Greenland

Mernild

Hasholt

Liston

2007

Hydrological Processes

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Abstract:A spatially distributed, physically based, hydrologic modeling system (MIKE SHE) was applied to quantify intra-and interannual discharge from the snow and glacierized Zackenberg River drainage basin (512 km 2 ; 20% glacier cover) in northeast Greenland. Evolution of snow accumulation, distribution by wind-blown snow, blowing-snow sublimation, and snow and ice surface melt were simulated by a spatially distributed, physically based, snow-evolution modelling system (SnowModel) and used as input to MIKE SHE. Discharge simulations were performed for three periods 1997-2001 (calibration period), 2001-2005 (validation period), and 2071-2100 (scenario period). The combination of SnowModel and MIKE SHE shows promising results; the timing and magnitude of simulated discharge were generally in accordance with observations (R 2 D 0Ð58); however, discrepancies between simulated and observed discharge hydrographs do occur (maximum daily difference up to 44Ð6 m 3 s 1 and up to 9% difference between observed and simulated cumulative discharge). The model does not perform well when a sudden outburst of glacial dammed water occurs, like the 2005 extreme flood event. The modelling study showed that soil processes related to yearly change in active layer depth and glacial processes (such as changes in yearly glacier area, seasonal changes in the internal glacier drainage system, and the sudden release of glacial bulk water storage) need to be determined, for example, from field studies and incorporated in the models before basin runoff can be quantified more precisely. The SnowModel and MIKE SHE model only include first-order effects of climate change. For the period 2071-2100, future IPCC A2 and B2 climate scenarios based on the HIRHAM regional climate model and HadCM3 atmosphere-ocean general circulation model simulations indicated a mean annual Zackenberg runoff about 1Ð5 orders of magnitude greater (around 650 mmWE year 1 ) than from today 1997-2005 (around 430 mmWE year 1 ), mainly based on changes in negative glacier net mass balance.

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Snow and blue-ice distribution patterns on the coastal Antarctic Ice Sheet

Cited by 51 publications

References 18 publications

Is snow sublimation important in the alpine water balance?

Is snow sublimation important in the alpine water balance?

High resolution modelling of snow transport in complex terrain using downscaled MM5 wind fields

Climatic control on river discharge simulations, Zackenberg River drainage basin, northeast Greenland

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