High resolution land surface parameters for the Community Land Model
Land surface heterogeneity is prominent in many regions around the world due to large spatial variability in land surface parameters such as land cover and land use, topography, and soil properties. Applying a higher resolution regionally and globally would capture the spatial variability of land surface processes across the landscape. To address this growing need, DOE scientists at Pacific Northwest National Laboratory developed a high resolution, gridded dataset at 0.05 degree resolution for the Community Land Model (CLM). This dataset includes Plant Functional Types (PFTs), Leaf Area Index (LAI), Stem Area Index (SAI), and non-vegetated land cover composition derived from the most recent, fully validated Moderate Resolution Imaging Spectroradiometer (MODIS) satellite data for 2005. When they compared the new surface parameters with those currently used in CLM4 at 0.5 degree resolution, the researchers found that the new parameters resolve more diverse subgrid PFTs within each 0.5 degree grid cell. The new dataset also shows more contributions from shrub, grass, and crop as opposed to bare soil, compared to the current CLM4.0 data. Their research also found a global decrease in LAI in boreal forests, but a large increase in LAI in tropical forests. This study demonstrated the use of the new high resolution data in a coupled land-atmosphere model based on the Weather Research and Forecasting (WRF) model coupled to CLM at 12 km resolution over the western United States. This shows important spatial details in surface fluxes being resolved by the high resolution modeling.