Linking Forest Biomass and Carbon Flux: Toward a Landscape-Scale Evaluation of Bottom-Up Flux Estimates Using Airborne Eddy Covariance Observations

A robust carbon monitoring system requires a comprehensive understanding of terrestrial carbon stocks and the underlying processes that connect vegetation metabolism to biomass change and integrated carbon flux. Terrestrial biosphere models that predict carbon storage and exchange typically have large uncertainties. In addition, discrepancies persist between biosphere- and atmosphere-based methods to quantify the terrestrial carbon budget. We are developing a framework that combines LiDAR derived forest canopy structure and direct carbon flux observations from the NASA Carbon Airborne Flux Experiment (CARAFE) to empirically constrain the relationship between forested biomass and net ecosystem exchange (NEE) over forested sites in Maryland. This framework will provide a first landscape-scale evaluation of the high-resolution Ecosystem Demography (ED) biophysical process model that estimates carbon stocks, fluxes, and carbon sequestration potential. This work will yield improved error quantification and characterization of carbon flux estimates for policy and decision-making intrinsic to carbon monitoring, reporting, and verification (MRV) efforts and will provide refined estimates and uncertainties for forest carbon sequestration potential and fluxes in support of the Maryland Regional Greenhouse Gas Initiative.