Canopy profile sensitivity on surface layer simulations evaluated by a multiple canopy layer higher order closure land surface model

The canopy structural and functional impacts on land surface modeling of energy and carbon fluxes were investigated by a series of simulations conducted at AmeriFlux eddy covariance sites. Canopy structures were described by different degrees of complexity of Leaf Area Index (LAI) datasets. The monthly climatological LAI datasets applied in the Weather Research and Forecasting (WRF) Model and the Community Earth System Model (CESM) were used to represent static ecological conditions. The LAI remotely sensed by the Moderate Resolution Imaging Spectroradiometer (MODIS) was used to represent time-varying ecological conditions with natural variability. To investigate the sensitivity of different canopy profile representations, all of these LAI datasets were used to assign the necessary ecological information for single and multiple canopy layer land surface models to simulate a seven-year period across a variety of vegetation covers. The results show that a more realistic canopy profile representation (i.e., multiple layers), both in terms of structural and functional treatments, improves biogeophysical and biogeochemical simulations. The root mean square errors for the simulated evapotranspiration and Net Ecosystem Exchange are reduced by 10% and 15%, respectively when the ecological information is represented by a more realistic time-varying LAI dataset instead of a static LAI dataset with no geographical sensitivity. A land surface model with multiple canopy layers and a realistic ecological dataset, which can better represent ecosystem structural and functional responses to microclimate conditions, is thus recommended for long-term climate projections.