Effects of Dynamic Vegetation on Global Climate Simulation Using the NCEP GFS and SSiB4/TRIFFID

Abstract

Two global experiments were carried out to investigate the effects of dynamic vegetation processes on numerical climate simulations from 1948 to 2008. The NCEP Global Forecast System (GFS) was coupled with a biophysical model, the Simplified Simple Biosphere Model (SSiB) version 2 (GFS/SSiB2), and it was also coupled with a biophysical and dynamic vegetation model, SSiB version 4/Top-down Representation of Interactive Foliage and Flora Including Dynamics (TRIFFID) (GFS/SSiB4/TRIFFID). The effects of dynamic vegetation processes on the simulation of precipitation, near-surface temperature, and the surface energy budget were identified on monthly and annual scales by assessing the GFS/SSiB4/TRIFFID and GFS/SSiB2 results against the satellite-derived leaf area index (LAI) and albedo and the observed land surface temperature and precipitation. The results show that compared with the GFS/SSiB2 model, the temporal correlation coefficients between the globally averaged monthly simulated LAI and the Global Inventory Monitoring and Modeling System (GIMMS)/Global Land Surface Satellite (GLASS) LAI in the GFS/SSiB4/TRIFFID simulation increased from 0.31/0.29 (SSiB2) to 0.47/0.46 (SSiB4). The correlation coefficients between the simulated and observed monthly mean near-surface air temperature increased from 0.50 (Africa), 0.35 (Southeast Asia), and 0.39 (South America) to 0.56, 0.41, and 0.44, respectively. The correlation coefficients between the simulated and observed monthly mean precipitation increased from 0.19 (Africa), 0.22 (South Asia), and 0.22 (East Asia) to 0.25, 0.27, and 0.28, respectively. The greatest improvement occurred over arid and semiarid areas. The spatiotemporal variability and changes in vegetation and ground surface albedo modeled by the GFS with a dynamic vegetation model were more consistent with the observations. The dynamic vegetation processes contributed to the surface energy and water balance and in turn, improved the annual variations in the simulated regional temperature and precipitation. The dynamic vegetation processes had the greatest influence on the spatiotemporal changes in the latent heat flux. This study shows that dynamic vegetation processes in earth system models significantly improve simulations of the climate mean status.