Using wind fields from a high‐resolution atmospheric model for simulating snow dynamics in mountainous terrain

Bernhardt, Matthias; Zängl, Günther; Liston, Glen E.; Strasser, Ulrich; Mauser, Wolfram

doi:10.1002/hyp.7208

Cited by 49 publications

(79 citation statements)

References 61 publications

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“…A common way of dealing with snow accumulations without the need for intensive field campaigns is using wind speed and direction to model lateral snow transport (e.g. Bernhardt et al, 2009Shulski and Seeley, 2004;Winstral et al, 2002;Liston and Sturm, 1998). Wind information may be obtained by meteorological stations or by computed wind fields.…”

Section: S Frey and H Holzmann: A Conceptual Distributed Snow Redimentioning

confidence: 99%

A conceptual, distributed snow redistribution model

Frey

Holzmann

2015

Hydrol. Earth Syst. Sci.

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Abstract. When applying conceptual hydrological models using a temperature index approach for snowmelt to high alpine areas often accumulation of snow during several years can be observed. Some of the reasons why these "snow towers" do not exist in nature are vertical and lateral transport processes. While snow transport models have been developed using grid cell sizes of tens to hundreds of square metres and have been applied in several catchments, no model exists using coarser cell sizes of 1 km 2 , which is a common resolution for meso-and large-scale hydrologic modelling (hundreds to thousands of square kilometres). In this paper we present an approach that uses only gravity and snow density as a proxy for the age of the snow cover and land-use information to redistribute snow in alpine basins. The results are based on the hydrological modelling of the Austrian Inn Basin in Tyrol, Austria, more specifically the Ötztaler Ache catchment, but the findings hold for other tributaries of the river Inn. This transport model is implemented in the distributed rainfall-runoff model COSERO (Continuous Semidistributed Runoff). The results of both model concepts with and without consideration of lateral snow redistribution are compared against observed discharge and snow-covered areas derived from MODIS satellite images. By means of the snow redistribution concept, snow accumulation over several years can be prevented and the snow depletion curve compared with MODIS (Moderate Resolution Imaging Spectroradiometer) data could be improved, too. In a 7-year period the standard model would lead to snow accumulation of approximately 2900 mm SWE (snow water equivalent) in high elevated regions whereas the updated version of the model does not show accumulation and does also predict discharge with more accuracy leading to a Kling-Gupta efficiency of 0.93 instead of 0.9. A further improvement can be shown in the comparison of MODIS snow cover data and the calculated depletion curve, where the redistribution model increased the efficiency (R 2 ) from 0.70 to 0.78 (calibration) and from 0.66 to 0.74 (validation).

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Section: S Frey and H Holzmann: A Conceptual Distributed Snow Redimentioning

confidence: 99%

A conceptual, distributed snow redistribution model

Frey

Holzmann

2015

Hydrol. Earth Syst. Sci.

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“…Fields of simulated wind directions are derived using the Penn State University -National Center for Atmospheric Research MM5 model (Grell , 1995) and downscaled with an energy-conserving procedure considering small-scale topography (Bernhardt et al, 2008a).…”

Section: Datamentioning

confidence: 99%

“…Only wind speed and direction data were provided using a library of local wind fields simulated with the Penn State University -National Center for Atmospheric Research MM5 model (Grell et al, 1995), applying the procedure described in Bernhardt et al (2008a). The efficiency of the sublimation process during blowingsnow events depends on the amount of snow in the simulated layers of saltation and turbulent suspension.…”

Section: Sublimation Of Snow From Turbulent Suspensionmentioning

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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“…At high elevations above treeline, snow is redistributed by wind (Föhn and Meister, 1983;Doorschot et al, 2001;Bernhardt et al, 2009), of which some is lost via sublimation to the atmosphere .…”

Section: Introductionmentioning

confidence: 99%

Multi-variable evaluation of hydrological model predictions for a headwater basin in the Canadian Rocky Mountains

Fang

Pomeroy

Ellis

et al. 2013

Hydrol. Earth Syst. Sci.

114

151

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Abstract.One of the purposes of the Cold Regions Hydrological Modelling platform (CRHM) is to diagnose inadequacies in the understanding of the hydrological cycle and its simulation. A physically based hydrological model including a full suite of snow and cold regions hydrology processes as well as warm season, hillslope and groundwater hydrology was developed in CRHM for application in the Marmot Creek Research Basin (∼ 9.4 km 2 ), located in the Front Ranges of the Canadian Rocky Mountains. Parameters were selected from digital elevation model, forest, soil, and geological maps, and from the results of many cold regions hydrology studies in the region and elsewhere. Non-calibrated simulations were conducted for six hydrological years during the period 2005-2011 and were compared with detailed field observations of several hydrological cycle components. The results showed good model performance for snow accumulation and snowmelt compared to the field observations for four seasons during the period 2007-2011, with a small bias and normalised root mean square difference (NRMSD) ranging from 40 to 42 % for the subalpine conifer forests and from 31 to 67 % for the alpine tundra and treeline larch forest environments. Overestimation or underestimation of the peak SWE ranged from 1.6 to 29 %. Simulations matched well with the observed unfrozen moisture fluctuation in the top soil layer at a lodgepole pine site during the period 2006-2011, with a NRMSD ranging from 17 to 39 %, but with consistent overestimation of 7 to 34 %. Evaluations of seasonal streamflow during the period 2006-2011 revealed that the model generally predicted well compared to observations at the basin scale, with a NRMSD of 60 % and small model bias (1 %), while at the sub-basin scale NRMSDs were larger, ranging from 72 to 76 %, though overestimation or underestimation for the cumulative seasonal discharge was within 29 %. Timing of discharge was better predicted at the Marmot Creek basin outlet, having a Nash-Sutcliffe efficiency (NSE) of 0.58 compared to the outlets of the sub-basins where NSE ranged from 0.2 to 0.28. The Pearson product-moment correlation coefficient of 0.15 and 0.17 for comparisons between the simulated groundwater storage and observed groundwater level fluctuation at two wells indicate weak but positive correlations. The model results are encouraging for uncalibrated prediction and indicate research priorities to improve simulations of snow accumulation at treeline, groundwater dynamics, and small-scale runoff generation processes in this environment. The study shows that improved hydrological cycle model prediction can be derived from improved hydrological understanding and therefore is a model that can be applied for prediction in ungauged basins.

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Using wind fields from a high‐resolution atmospheric model for simulating snow dynamics in mountainous terrain

Cited by 49 publications

References 61 publications

A conceptual, distributed snow redistribution model

A conceptual, distributed snow redistribution model

Is snow sublimation important in the alpine water balance?

Multi-variable evaluation of hydrological model predictions for a headwater basin in the Canadian Rocky Mountains

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