Predicting scalar source-sink and flux distributions within a forest canopy using a 2-D Lagrangian stochastic dispersion model

This study proposes a two-dimensional Lagrangian stochastic dispersion model for estimating spatial and temporal variation of scalar sources, sinks, and fluxes within a forest canopy. Carbon dioxide and heat dispersion experiments were conducted for field testing the model. These experiments also provided data for field testing a newly developed one-dimensional Lagrangian analytical dispersion model. It was found that these two models produce similar scalar source-sink and flux distribution patterns. Comparing with CO₂ flux measurements, the one-dimensional model performed as well as the two-dimensional model even when the fetch is short (≈100 m). To drive these Lagrangian models, velocity statistics through the canopy volume must be specified a priori. The sensitivity of the computed sources, sinks, and fluxes to the description of the flow statistics was further examined. All in all, we found good agreement between model predicted and eddy-correlation measured CO₂ and sensible heat fluxes.