Author(s):
Prof. Jeff Dozier - University Of California - Santa Barbara
Abstract:
One of Sam Outcalt’s longstanding research interests is the use of surface energy balance models and measurements in rugged topography. Our interest in this topic stems from its intellectually interesting appeal and from the pleasure in fieldwork in interesting terrain, and snow is a particularly fascinating application. Models of processes in the alpine snow cover fundamentally depend on the spatial distribution of the surface energy balance over areas where topographic variability causes huge differences in the radiation balance, in convective processes, and in snow depth because of redistribution by wind. Challenges arise from the need to measure some of the variables—albedo, grain size, temperature, liquid water, and depth or water equivalent—at a scale commensurate with that of the terrain. Modeling challenges arise because of the three-dimensional transport of heat and water vapor above the surface and liquid water within the snowpack. Our work to date shows that the radiation balance is usually the most important component in the energy balance calculations, and therefore spatially distributed albedo measurements from remote sensing dramatically improve model performance. Lateral flow of water in the snowpack is known to occur but is hard to measure, and it causes the current models to miss the early influx of water from the snow to the stream.
