Wind influence on snow depth distribution and accumulation over glaciers

Dadić, Ruzica; Mott, Rebecca; Lehning, Michael; Burlando, Paolo

doi:10.1029/2009jf001261

Cited by 168 publications

(220 citation statements)

References 29 publications

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“…Targeted observations and a more sophisticated snow-accumulation model are also needed to help reduce the uncertainty in B w . Development of a detailed snow distribution model would be valuable (e.g., Dadic, Mott, Lehning, & Berlando, 2010) and is recommended for future study. Snowpack extent varies from year to year, but patterns of snow deposition on glaciers typically recur, because snow redistribution through processes such as avalanching and wind scouring is primarily a function of the terrain.…”

Section: Discussion a Observed And Modelled Mass Balancementioning

confidence: 99%

Glacier Meltwater Contributions and Glaciometeorological Regime of the Illecillewaet River Basin, British Columbia, Canada

Hirose

Marshall

2013

Atmosphere-Ocean

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This study characterizes the meteorological parameters influencing glacier runoff and quantifies recent glacier contributions to streamflow in the Illecillewaet River basin, British Columbia. The Illecillewaet is a glacierized catchment that feeds the Columbia River, with terrain, glacial cover, and topographic relief that are typical of Columbia River headwaters basins in southwestern Canada. Meteorological and mass balance data collected on Illecillewaet Glacier are used to develop and constrain a distributed model for glacier melt, based on temperature and absorbed solar radiation. The melt model is applied to all of the glaciers in the Illecillewaet River basin for the summers of 2009 to 2011. Modelled glacier runoff for the three years has an average value of 112 ± 12 × 10 6 m 3 , approximately 10% of Illecillewaet River yields for 2009 to 2011. Glaciers contributed 25% to August flows for the three years. On average, 66% of modelled glacial discharge is derived from the seasonal snowpack, with the remaining 34% resulting from the melting of glacier ice and firn. For the lowest flow year in the basin, 2009, snow and ice melt from glaciers in the basin contributed 14% and 33%, respectively; 81% of the August glacier runoff is derived from glacier storage (ice and firn). Climate sensitivity studies for Illecillewaet Glacier indicate that the glacier mass balance is strongly influenced by summer temperature, with a net balance change of −0.6 metres of water equivalent (m w.e.) under a 1°C warming. A 30% increase in winter precipitation is needed to offset this. Our values are initial estimates, and long-term monitoring is essential to characterize glacier and climate variability in the region better, to refine estimates of glacier runoff, and to quantify the sensitivity of runoff to glacier retreat.RÉSUMÉ [Traduit par la rédaction] La présente étude caractérise les paramètres météorologiques qui influencent le ruissellement des glaciers et quantifie les contributions récentes des glaciers à l'écoulement fluvial dans le bassin de la rivière Illecillewaet, en Colombie-Britannique. L'Illecillewaet est un bassin hydrographique englacé qui alimente le fleuve Columbia, avec un terrain, une couverture de glace et des éléments topographiques caractéristiques des bassins du cours supérieur du fleuve Columbia dans le sud-ouest du Canada. Nous utilisons les données météorologiques et de bilan massique recueillies sur le glacier Illecillewaet pour mettre au point et contraindre un modèle distribué de fonte des glaciers, basé sur la température et le rayonnement solaire absorbé. Le modèle de fonte est appliqué à tous les glaciers situés dans le bassin de la rivière Illecillewaet pour les étés de 2009 à 2011. Le ruissellement modélisé des glaciers pour les trois années a une valeur moyenne de 112 ± 12 × 10 6 m 3 , approximativement 10% de l'écoulement de la rivière Illecillewaet pour 2009 à 2011. Les glaciers ont contribué pour 25% de l'écoulement en août les trois années. En moyenne, 66% du ruissellement modélisé ...

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Section: Discussion a Observed And Modelled Mass Balancementioning

confidence: 99%

Glacier Meltwater Contributions and Glaciometeorological Regime of the Illecillewaet River Basin, British Columbia, Canada

Hirose

Marshall

2013

Atmosphere-Ocean

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“…ALS enables area-wide data to be gathered in a very high spatial resolution and accuracy. Hopkinson et al (2004) and Deems et al (2006) showed that ALS was an appropriate and accurate method for gathering snow depth measurements, and since then, a rising number of data sets have become available (Deems et al, 2006;Moreno Banos et al, 2009;Dadic et al, 2010a;DeBeer and Pomeroy, 2010;Grünewald and Lehning, 2011;Schöber et al, 2011;Hopkinson et al, 2012). Detailed descriptions of the ALS measurement principle can be found in Geist et al (2009), Baltsavias (1999 and Wehr and Lohr (1999).…”

Section: Airborne Laser Scanningmentioning

confidence: 99%

Statistical modelling of the snow depth distribution in open alpine terrain

Grünewald¹,

Stötter

Pomeroy

et al. 2013

Hydrol. Earth Syst. Sci.

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Abstract. The spatial distribution of alpine snow covers is characterised by large variability. Taking this variability into account is important for many tasks including hydrology, glaciology, ecology or natural hazards. Statistical modelling is frequently applied to assess the spatial variability of the snow cover. For this study, we assembled seven data sets of high-resolution snow-depth measurements from different mountain regions around the world. All data were obtained from airborne laser scanning near the time of maximum seasonal snow accumulation. Topographic parameters were used to model the snow depth distribution on the catchment-scale by applying multiple linear regressions. We found that by averaging out the substantial spatial heterogeneity at the metre scales, i.e. individual drifts and aggregating snow accumulation at the landscape or hydrological response unit scale (cell size 400 m), that 30 to 91 % of the snow depth variability can be explained by models that are calibrated to local conditions at the single study areas. As all sites were sparsely vegetated, only a few topographic variables were included as explanatory variables, including elevation, slope, the deviation of the aspect from north (northing), and a wind sheltering parameter. In most cases, elevation, slope and northing are very good predictors of snow distribution. A comparison of the models showed that importance of parameters and their coefficients differed among the catchments. A "global" model, combining all the data from all areas investigated, could only explain 23 % of the variability. It appears that local statistical models cannot be transferred to different regions. However, models developed on one peak snow season are good predictors for other peak snow seasons.

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“…We suggest that a correct reproduction of glacier-wide surface mass balance requires an evaluation scheme to resolve the accumulation distribution. However, snow accumulation patterns are highly variable in space and time, due to variations in the amount of solid precipitation, the preferential deposition of snow, and the redistribution by wind and avalanching (Lehning et al, 2008;Dadic et al, 2010;Grünewald et al, 2010). Thus, the sparsity of accumulation measurements can be a major source of uncertainty in the glaciologically derived glacier-wide mass balance (Funk et al, 1997;Fountain and Vecchia, 1999).…”

Section: Introductionmentioning

confidence: 99%

Mass Balance Re-analysis of Findelengletscher, Switzerland; Benefits of Extensive Snow Accumulation Measurements

et al. 2016

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A re-analysis is presented here of a 10 year mass balance series at Findelengletscher, a temperate mountain glacier in Switzerland. Calculating glacier-wide mass balance from the set of glaciological point balance observations using conventional approaches, such as the profile or contour method, resulted in significant deviations from the reference value given by the geodetic mass change over a 5 year period. This is attributed to the sparsity of observations at high elevations and to the inability of the evaluation schemes to adequately estimate accumulation in unmeasured areas. However, measurements of winter mass balance were available for large parts of the study period from snow probings and density pits. Complementary surveys by helicopter-borne ground-penetrating radar (GPR) were conducted in three consecutive years. The complete set of seasonal observations was assimilated using a distributed mass balance model. This model-based extrapolation revealed a substantial mass loss at Findelengletscher of −0.43 m w.e. a −1 between 2004 and 2014, while the loss was less pronounced for its former tributary, Adlergletscher (−0.30 m w.e. a −1 ). For both glaciers, the resulting time series were within the uncertainty bounds of the geodetic mass change. We show that the model benefited strongly from the ability to integrate seasonal observations. If no winter mass balance measurements were available and snow cover was represented by a linear precipitation gradient, the geodetic mass balance was not matched. If winter balance measurements by snow probings and snow density pits were taken into account, the model performance was substantially improved but still showed a significant bias relative to the geodetic mass change. Thus, the excellent agreement of the model-based extrapolation with the geodetic mass change was owed to an adequate representation of winter accumulation distribution by means of extensive GPR measurements.

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Wind influence on snow depth distribution and accumulation over glaciers

Cited by 168 publications

References 29 publications

Glacier Meltwater Contributions and Glaciometeorological Regime of the Illecillewaet River Basin, British Columbia, Canada

Glacier Meltwater Contributions and Glaciometeorological Regime of the Illecillewaet River Basin, British Columbia, Canada

Statistical modelling of the snow depth distribution in open alpine terrain

Mass Balance Re-analysis of Findelengletscher, Switzerland; Benefits of Extensive Snow Accumulation Measurements

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