Improving the Community Land Model (version 4) Regional Snowpack Predictions in the Western United States Using High Resolution Forcing Data

Thursday, 18 December 2014
Trevor Crawford and Jiming Jin, Utah State University, Logan, UT, United States
To improve snow water equivalent (SWE) model output of regional land simulations, the Community Land Model version 4 (CLM4) was decoupled from the Community Earth System Model (CESM) version 1.0 and forced with four-kilometer (0.04° latitude by 0.04° longitude) resolution data from the Parameter-elevation Regressions on Independent Slopes Model (PRISM) climate data set. Other essential atmospheric forcing variables have been interpolated from default CLM offline forcing data. CLM4 physically describes variable snowpacks with up to five snow layers, taking into consideration snow compaction and the conservation of mass and heat transfer of water and ice content. This decoupled CLM4 model is evaluated between the water years of 1982-2011 over the Western United States (WUS) mountain region where snowmelt is critical for agricultural and urban activities. The results from this study show a significant improvement in SWE model output, which is underestimated with offline CLM4 runs using default coarse grids. An important cause for underestimation of SWE is coarse variable information that does not account for geospatial variability within the mountainous WUS. CLM4 grid point outputs are then quantitatively compared to associated locations of SNOTEL station observations. In addition, single-point analysis is provided at select geographical locations, that directly use SNOTEL precipitation data to force CLM4. This investigation will lead to future work providing realistic parameterizations into future CLM model runs for future snowpack predictions over the WUS.