A simple time-stepping scheme to simulate leaf area index, phenology, and gross primary production across deciduous broadleaf forests in the eastern United States
Terrestrial plants play a key role in regulating the exchange of energy and materials between the land surface and the atmosphere. Robust models that simulate both leaf dynamics and canopy photosynthesis are required to understand vegetation–climate interactions. This study proposes a simple time-stepping scheme to simulate leaf area index (LAI), phenology, and gross primary production (GPP) when forced with climate variables. The method establishes a linear function between steady-state LAI and the corresponding GPP. The method applies the established function and the MOD17 algorithm to form simultaneous equations, which can be solved together numerically. To account for the time-lagged responses of plant growth to environmental conditions, a time-stepping scheme is developed to simulate the LAI time series based on the solved steady-state LAI. The simulated LAI time series is then used to derive the timing of key phenophases and simulate canopy GPP with the MOD17 algorithm. The developed method is applied to deciduous broadleaf forests in the eastern United States and is found to perform well for simulating canopy LAI and GPP at the site scale as evaluated using both flux tower and satellite data. The method also captures the spatiotemporal variation of vegetation LAI and phenology across the eastern United States compared with satellite observations. The developed time-stepping scheme provides a simplified and improved version of our previous modeling approach to simulate leaf phenology and can potentially be applied at regional to global scales in future studies.