Subarctic woodlands comprise stands of spruce trees with varying degrees of
openness, giving rise to large contrasts in melt rates within the forest.
The spatial variability of the changing snow depth during a melt season was
investigated at three scales (2, 4 and 16 m), using an example from a site
in Yukon, Canada, where the computation of snowmelt takes into account the
differential rates within the woodland. During the melt period, the mean d
aily snow depth decreases but the variability increases as continued ablati
on leads to greater unevenness of the snow cover. At the three scales of re
presentation, increasing the grid size results in a reduction in the standa
rd deviation and the skewness of depth distribution. The blurring of snow c
over pattern at the larger scales is due to a loss in information, consider
ed as the absolute value of the difference in snow depth calculated at two
scales for the same location. This loss increases as the snow depth becomes
more variable during the melt season. Knowledge of the scale-induced infor
mation loss is relevant to the modelling of snowmelt that exhibits large sp
atial variations.