Many processes and interactions in the atmosphere and the biosphere influence the rate of carbon dioxide exchange between these two systems. However, it is difficult to estimate the carbon dioxide flux over regions with diverse ecosystems and complex terrains, such as California. Traditional carbon dioxide measurements are sparse and limited to specific ecosystems. Therefore, accurately estimating carbon dioxide flux on a regional scale remains a major challenge.

In this study, we couple the Weather Research and Forecasting Model (WRF) with the Advanced Canopy-Atmosphere-Soil Algorithm (ACASA), a high complexity land surface model. Although WRF is a state-of-the-art regional atmospheric model with high spatial and temporal resolutions, the land surface schemes available in WRF lack the capability to simulate carbon dioxide. ACASA is a complex multilayer land surface model with interactive canopy physiology and full surface hydrological processes. It allows microenvironmental variables such as air and surface temperatures, wind speed, humidity, and carbon dioxide concentration to vary vertically. Carbon dioxide, sensible heat, water vapor, and momentum fluxes between the atmosphere and land surface are estimated in the ACASA model through turbulence equations with a third order closure scheme. It therefore permits counter-gradient transports that low-order turbulence closure models are unable to simulate.

A new CO₂ tracer module is introduced into the model framework to allow the atmospheric carbon dioxide concentration to vary according to terrestrial responses. In addition to the carbon dioxide simulation, the coupled WRF-ACASA model is also used to investigate the interactions of neighboring ecosystems in their response to atmospheric carbon dioxide concentration. The model simulations with and without the CO₂ tracer for WRF-ACASA are compared with surface observations from the AmeriFlux network.