Raleigh, Mark SÌý1
1ÌýNational Center for Atmospheric Research
Coniferous forest canopies play a significant role in seasonal snowpack development and land-atmosphere feedbacks. Depending on climate, storm dynamics, and forest characteristics, melt or sublimation of snow intercepted in the canopy may reduce snow water equivalence on the ground by 10-80%. Additionally, snow in the forest canopy reduces the aggregate albedo of an area, thereby substantially altering surface energy exchanges and feedbacks between the land and the atmosphere in areas with dense and expansive forests (e.g., the boreal forest). Despite the importance of canopy interception to mountain hydrology and climate, measurements have generally been limited to short-term research studies and are typically sparse in coverage. As a result, there is limited knowledge about how canopy interception varies spatially, with scale (i.e., from tree to forest), and with annual climate variations.
Satellite remote sensing is a novel resource for monitoring snow interception variations and for evaluating representations of this process in land surface models. Here I present a conceptual framework for extracting snow interception information (i.e., timing and duration of interception events) from Moderate Resolution Imaging Spectroradiometer (MODIS) data and apply the methodology over the California Sierra Nevada from water years 2002-2011 as an initial case study. Preliminary results show interesting interannual variations in canopy interception (i.e., number of days with snow in canopy), with some years (e.g., 2008 and 2009) exhibiting enhanced snow interception dynamics (e.g., twice as many days with snow in the canopy relative to other years), which are presumably related to annual climate and storm variations. I demonstrate the value of time-lapse photography for evaluating the MODIS interception data at multiple locations in Yosemite National Park. Finally, I describe a new network of time-lapse cameras in the Niwot Ridge LTER and Boulder Critical Zone Observatory and emerging avenues of collaboration on this topic with other researchers at NCAR and CU. This new network is designed to examine variations of snow interception with spatial location (e.g., elevation and aspect), forest characteristics, and scale, and will enable further testing of the MODIS interception methodology and representation of snow interception in land surface models.