Spatial Snow Surface Roughness across Two Resolutions

Variability in snow surface roughness is rarely incorporated into climate or hydrological models, yet it has the potential to have a large impact on both latent and sensible heat for a snow dominated system. We looked at the spatial variability of snow surface roughness using the data collected by the NASA Cold Land Processes Experiment (CLPX) during the winters of 2002 and 2003 for a number of 1 km2 intensive study areas (ISAs) across northern Colorado. Within each ISA, snow roughness data were derived from 100 images of snow roughness boards at sub-millimeter resolution and from airborne lidar measurements at meter resolution. Each board had an extent of one meter while the lidar data was continuous over the entire 1 kilometer. Roughness metrics were estimated for each dataset and examined geospatially to understand their spatial variability and the driving processes. While the spatial coherence of the roughness board data was limited across each ISA based on the Moran's I statistic, the lidar data was more spatially coherent. However, the roughness metrics could be scaled from the fine resolution boards to the coarser resolution lidar snow surfaces for most of each ISA.