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. Be cause of different energy dynamics, this heterogeneous land cover prod uces a horizontal transfer of energy at a small scale, a process terme d local advection. An advection efficiency term (F-s), which represent s the fraction of the sensible heat from snow-free patches which is ad vected to snow patches, was determined from field studies and publishe d model results. Energy balance calculations demonstrated the strong c ontrast between the two surface cover types that drive advective proce sses, and F-s was found to decrease exponentially with decreasing snow cover fraction. The field results suggest higher values of F-s compar ed with the model results for single snow patches of varying size, but similar in magnitude to F-s for multiple small snow patches. Utilizin g exponential best-fit relationships between F-s and fractional snow c over shows an increase in sensible heat flux of over 100% for low snow cover fractions. When considering the average flux over a composite s now and snow-free surface, the average sensible heat flux obtained fro m weighting the fluxes for each surface by their respective areas unde restimates the composite flux when compared with when advection is con sidered. 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 di stribution patterns and fetch lengths needs to be considered more expl icitly. This has important implications in studies of areal energy flu ctuations over melting, patchy snow covers, basin water balance studie s and regional and global climate modelling. (C) 1998 John Wiley & Son s, Ltd.