An integrated characterization of the surface radiation balance during spring snowmelt in Central Eurasia

Quantifying spatial variability of snow can be greatly assisted with remote sensors. Remote sensing data and techniques have been applied to determine the spatial variability of snow characteristics for several decades, particularly extent. In the last decade, new satellite sensors have allowed characterization of the spatial variability of snow beyond extent. One such characteristic is the impact of snow on the radiation balance. Here we utilize radiation balance terms determined with the CERES sensor on Terra and Aqua satellites to examine the impact of spatially distributed snow extent on surface radiation balance in a region covering western Siberia and the Urals during the spring melt season (April and early May) of 2005. Data include short and longwave radiation fluxes at the surface, surface albedo, cloud cover, and surface air pressure. This allows an examination of the synoptic, cloud, and surface cover influences on spring melt, in a region where land cover itself is changing due to intensive petroleum production, increased wildfires, logging, and the northward shift of ecosystems with a warming climate. Radiation balance terms change drastically during the melt season, and show marked spatial patterns with significant spatial variability. Over both snow-covered land and transitioning snow cover, land cover was found to be an important forcing of radiation balance. The most significant differences are found over the boreal forest, where the change in albedo is the smallest, which reflects on much of the remainder of radiation balance terms. This integrative study demonstrates how CERES and land cover data can be applied to understand the impact on radiation balance during melt season. This will become increasingly important as snow extent is projected to diminish, and land cover to change, in the 21st century.