Improving Land Surface Temperature Simulation in CoLM Over the Tibetan Plateau Through Fractional Vegetation Cover Derived From a Remotely Sensed Clumping Index and Model-Simulated Leaf Area Index

Parameterizations of fractional vegetation cover (FVC) in land surface models have important effects on simulations of surface energy budget, especially in arid and semiarid regions. This study uses a FVC scheme in which FVC is derived from leaf area index and a remotely sensed clumping index. The performance of the new scheme (SMFVC) is evaluated against Moderate Resolution Imaging Spectroradiometer (MODIS) land surface temperature (LST) and in situ soil temperature observations, together with two other FVC schemes, a general FVC scheme (CTL) based on land cover map and a climatology-based FVC scheme (RSFVC) that uses long-term remotely sensed Normalized Difference Vegetation Index of MODIS. The three FVC schemes were implemented in the Common Land Model (CoLM) and applied in the Tibetan Plateau using the same forcing data and default parameters. Our results demonstrate that FVC schemes have significant influence on the CoLM performance: (1) the RSFVC and SMFVC schemes significantly reduce the LST biases found in CTL, particularly in grassland and during summer; (2) soil temperature evaluation by in situ observations from three networks on the Tibetan Plateau corroborates the LST results; and (3) the improvements are mainly related to representing temporal (seasonal) variability and subgrid heterogeneity of FVC, which improves surface albedo and surface energy balance. In other words, by including more vegetation characteristics, such as using a clumping index, land surface models may better simulate surface vegetation condition and further better represent the land surface energy budget over the Tibetan Plateau.