Parameterization of Blowing-Snow Sublimation in a Macroscale Hydrology Model

Abstract

An algorithm that parameterizes the topographically induced subgrid variability in wind speed, snow transport, and blowing-snow sublimation was designed for use within macroscale hydrology models and other large-scale land surface schemes (LSSs). The algorithm is intended to provide consistent estimates of the relative influence of sublimation from blowing snow for continental-scale river basins, while balancing the land surface water and energy budgets. In addition to the standard LSS inputs, the model requires specification of the standard deviation of terrain slope, the mean fetch, and the lag-1 autocorrelation of terrain gradients. Sublimation fluxes are solved for each vegetation class, for each model grid cell. Model results are compared to observed snow water equivalent (SWE) and simulated estimates of sublimation from blowing snow for two small tundra watersheds: Imnavait Creek, Alaska, and Trail Valley Creek, Northwest Territories, Canada, produced by two different small-scale distributed blowing-snow algorithms. The macroscale algorithm reproduced most aspects of the variability between years and between vegetation types predicted by the more detailed models. The macroscale model was subsequently used to estimate sublimation from blowing snow and the snowpack for the 8000-km2 Kuparuk River watershed in northern Alaska. Annual average sublimation from blowing snow predicted by the model for this region varies from 47 mm in the foothills of the Brooks Range to approximately 31 mm on the Arctic coastal plain; sublimation was primarily controlled by topographic limitations on fetch in the foothills and by precipitation and vapor pressure on the coastal plain.