Testing and application of a model for snow redistribution (Snow_Blow) in the Ellsworth Mountains, Antarctica

• Published in: Journal of Glaciology
• Main Authors: Mills, Stephanie C., Le Brocq, Anne M., Winter, Kate, Smith, Michael, Hillier, John, Ardakova, Ekaterina, Boston, Clare M., Sugden, David, Woodward, John
• Format: Article in Journal/Newspaper
• Language: English
• Published: Cambridge University Press (CUP) 2019
• Subjects: Antarc*; Antarctica; Journal of Glaciology; West Antarctica
• Online Access: http://dx.doi.org/10.1017/jog.2019.70; https://www.cambridge.org/core/services/aop-cambridge-core/content/view/S0022143019000704

Abstract Wind-driven snow redistribution can increase the spatial heterogeneity of snow accumulation on ice caps and ice sheets, and may prove crucial for the initiation and survival of glaciers in areas of marginal glaciation. We present a snowdrift model (Snow_Blow), which extends and improves the model of Purves, Mackaness and Sugden (1999, Journal of Quaternary Science 14, 313–321). The model calculates spatial variations in relative snow accumulation that result from variations in topography, using a digital elevation model (DEM) and wind direction as inputs. Improvements include snow redistribution using a flux routing algorithm, DEM resolution independence and the addition of a slope curvature component. This paper tests Snow_Blow in Antarctica (a modern environment) and reveals its potential for application in palaeoenvironmental settings, where input meteorological data are unavailable and difficult to estimate. Specifically, Snow_Blow is applied to the Ellsworth Mountains in West Antarctica where ablation is considered to be predominantly related to wind erosion processes. We find that Snow_Blow is able to replicate well the existing distribution of accumulating snow and snow erosion as recorded in and around Blue Ice Areas. Lastly, a variety of model parameters are tested, including depositional distance and erosion vs wind speed, to provide the most likely input parameters for palaeoenvironmental reconstructions.