Characterizing local scale snow cover using point measurements during the winter season

Abstract

Snow cover is spatially heterogeneous at the local scale because of micro climatic, topographic and vegetative effects on snow accumulation, redistribution and ablation ‐ processes which vary between different environments. Automated, fixed point snow depth measurements are the norm at research as well as operational sites, and the ability of these single point measurements to characterize snow depth for the surrounding area is an important issue. In this study, data for three winter seasons (2002–03, 2003–04, 2004–05) from ten Boreal Ecosystem Research and Monitoring Sites (BERMS) in northern Saskatchewan were used to assess the relationships between local scale snow depth variability, ascertained from snow survey transects, and single point measurements made with sonic depth sensors. Analysis of the snow surveys showed a wide range of depths at each site, with increased variability as winter progressed. Single, fixed‐point measures of snow depth did not statistically represent the average snow depth at a site, even for relatively uniform snow covers. Consistent over‐ or under‐representation of the landscape mean allowed the development of a “scaling equation” for each point measurement, improving confidence in the use of these data for modelling and climate variability studies. Where manual snow surveys may not be practical, the use of multiple automated point depth measurements may be adopted, and for the BERMS sites it was found that the minimum number of point measurements required to represent the landscape mean within 25% ranged from 1 to 44, depending on the degree of variability in snow depth associated with the landscape type, and the magnitude of the site mean depth. The relationships between point snow depth measurements and mean areal snow depth are important to consider both when utilising historical point observations for climatological and hydro‐logical analysis, and for decision‐making with regards to snow depth observing networks.