Leaf area index (LAI) is an important agrometeorological index and a key variable which is influenced by many physical, biological and physiological processes in plant communities. This study evaluates the ability of RegCM model in simulating LAI using CLM land surface model in two states of static and dynamic vegetation cover for the period of 1991–2005. Two GCM models (CanESM2 and EC-Earth) are applied to determine the boundary conditions. The temperature at 2 m above ground and precipitation data were collected from 106 synoptic stations (Iran). Also, the ERA5 reanalysis data were implemented as the reference to evaluate the simulated LAI data. To identify the climate types of the selected sites, De Martonne climate classification was used. The results show the highest correlation coefficient (0.78) between simulated LAI of CLM (by CanESM2-RegCM-CLM model) versus reference LAI of ERA5. For the sites located in arid and Mediterranean climate regions, the LAI simulated by CanESM2-RegCM-CLM model presented the least deviations compared to the reference ERA5 data. Model results showed that for both CanESM2 and EC-Earth models, the static vegetation cover tends to overestimate the simulated LAI; but, the activation of carbon-nitrogen feedback within the models leads to underestimation of vegetation cover in the region. Future work is suggested for evaluating other agrometeorological indices (e.g. NDVI, EVI) to detect the dynamic feedback of carbon-nitrogen cycle.
