Representativeness of local snow data for large scale hydrologic investigat- ions

Arctic snow cover usually attains maximum values at the end of winter and such information is important for hydrological investigations because most floods are associated with spring snowmelt. Snow data from weather stations or collected at some local sites are often extrapolated to large areas, but without verifying that the upscaling procedure yields correct results. This study compares maximum snow cover data gathered over two large target areas (170 to 300 km2) with weather station snow course measurements to determine the representativeness of local-scale data for areas typically occupied by large grid cells of macro-hydrological models, The field snow survey results confirmed the controlling role of terrain on snow distribution in the High Arctic. The variability of areal mean snow water equivalence for a grid cell (with dimensions of 1 × 1 km2 to 13 × 13 km2) increases with terrain complexity but decreases with grid size. Although point data do not represent the snow cover over an area, an attempt was made to upscale the weather station data to the target areas using an index method. Test results show that this index approach works well in the area with a shallow snow cover, but the error increases for an area with relatively deep snow. More effort is needed to refine this method, perhaps in conjunction with remote sensing, so that point data can be upscaled to yield snow information suitable for large-scale hydrological models or land surface schemes.