One part of the Clark et al. (2015) study explored the impact of the choice of canopy shortwave radiation parameterizations on simulations of below canopy shortwave radiation for three representative water years at the aspen site in the Reynolds Mountain East catchment. This study looked at four different canopy shortwave radiation parameterizations: BeersLaw method(as implemented in VIC), NL_scatter method(Nijssen and Lettenmaier, JGR 1999:NL 1999), UEB_2stream method(Mahat and Tarboton, WRR 2011:MT 2012), CLM_2stream method(Dick 1983) In this Jupyter Notebook, the pySUMMA library is used to reproduce this analysis. First, the four different canopy shortwave radiation parameterisations are described. Next, the Methods section describes how the pySUMMA can be used to create four different canopy shortwave radiation parameterizations of the Reynolds Mountain East catchment model. The Results section shows how to use pySUMMA and the Pandas library to reproduce Figure 1(above) from Clark et al. (2015). Collectively, this Jupyter Notebook serves as an example of how hydrologic modeling can be conducted directly within a Jupyter Notebook by leveraging the pySUMMA library.
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