Advanced-Canopy-Atmosphere-Soil Algorithm (ACASA Model) for Estimating Mass and Energy Fluxes

There is a recognized need to improve land surface models that simulate mass and energy fluxes between terrestrial ecosystems and atmosphere. In particular, long-term land planning strategies at local and regional scales require better understanding of agricultural ecosystem capacity to exchange CO2 and water. One of the more elaborate models for flux modelling is the Advanced Canopy-Atmosphere- Soil Algorithm (ACASA) model (Pyles et al., 2000), which provides micro-scale and regional-scale fluxes. The ACASA model allows for characterization of energy and carbon fluxes. It is a higher-order closure model used to estimate fluxes and profiles of heat, water vapor, carbon and momentum within and above canopy using third-order closure equations. It also estimates turbulent profiles of velocity, temperature, humidity within and above canopy. The ACASA model estimates CO2 fluxes using a combination of Ball-Berry and Farquhar equations. In addition, the effects of water stress on stomata, transpiration and CO2 assimilation are considered. The model was mainly used over dense canopies (Pyles et al. 2000, 2003) in the past, so the aim of this work was to test the ACASA model over a sparse canopy for estimating mass and energy fluxes, comparing model output with field measurements taken over a vineyard located in Montalcino, Tuscany, Italy.