Local advection of sensible heat in the snowmelt landscape of Arctic tundra

The spring landscape of the Arctic tundra is dominated by a snow cover which is highly variable in depth owing to redistribution by wind. Because of different energy dynamics, this heterogeneous land cover produces a horizontal transfer of energy at a small scale, a process termed local advection. An advection efficiency term (F-s), which represents the fraction of the sensible heat from snow-free patches which is advected to snow patches, was determined from field studies and published model results. Energy balance calculations demonstrated the strong contrast between the two surface cover types that drive advective processes, and F-s was found to decrease exponentially with decreasing snow cover fraction. The field results suggest higher values of F-s compared with the model results for single snow patches of varying size, but similar in magnitude to F-s for multiple small snow patches. Utilizing exponential best-fit relationships between F-s and fractional snow cover shows an increase in sensible heat flux of over 100% for low snow cover fractions. When considering the average flux over a composite snow and snow-free surface, the average sensible heat flux obtained from weighting the fluxes for each surface by their respective areas underestimates the composite flux when compared with when advection is considered. This work provides a simple method to estimate the effect of local advection on sensible heat to snow patches and the average flux from a composite surface during the snowmelt period, using only fluxes calculated independently for 0% snow cover and 100% snow cover and an estimate of F-s. It demonstrates a good first estimate of the role of advection, but for future study the influence of wind speed, patch distribution patterns and fetch lengths needs to be considered more explicitly. This has important implications in studies of areal energy fluctuations over melting, patchy snow covers, basin water balance studies and regional and global climate modelling. (C) 1998 John Wiley & Sons, Ltd.