Modeling subcanopy incoming longwave radiation to seasonal snow using air and tree trunk temperatures

Data collected at three Swiss alpine forested sites over a combined 11year period were used to evaluate the role of air temperature in modeling subcanopy incoming longwave radiation to the snow surface. Simulated subcanopy incoming longwave radiation is traditionally partitioned into that from the sky and that from the canopy, i.e., a two-part model. Initial uncertainties in predicting longwave radiation using the two-part model resulted from vertical differences in measured air temperature. Above-canopy (35m) air temperatures were higher than those within (10m) and below (2m) canopy throughout four snow seasons (December-April), demonstrating how the forest canopy can act as a cold sink for air. Lowest model root-mean-square error (RMSE) was using above-canopy air temperature. Further investigation of modeling subcanopy longwave radiation using above-canopy air temperature showed underestimations, particularly during periods of high insolation. In order to explicitly account for canopy temperatures in modeling longwave radiation, the two-part model was improved by incorporating a measured trunk view component and trunk temperature. Trunk temperature measurements were up to 25 degrees C higher than locally measured air temperatures. This three-part model reduced the RMSE by up to 7.7Wm(-2) from the two-part air temperature model at all sensor positions across the 2014 snowmelt season and performed particularly well during periods of high insolation when errors from the two-part model were up to 40Wm(-2). A parameterization predicting tree trunk temperatures using measured air temperature and incoming shortwave radiation demonstrate a simple method that can be applied to provide input to the three-part model across midlatitude coniferous forests.