Hannun (CMS 2020): Linking Forest Biomass and Carbon Exchange Using LiDAR-Derived Forest Structure and Airborne Flux Observations
Reem Aida Hannun, University of Pittsburgh, reem.a.hannun@nasa.gov (Presenter)
A robust carbon monitoring system (CMS) 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 propose to quantify the relationship between forested biomass and net ecosystem exchange (NEE) using previously acquired remote sensing maps of forested structure and direct flux observations and to use these results to evaluate the Ecosystem Demography (ED) biophysical process model. Our research plan entails two main objectives, focused on closing the gap between biosphere and atmosphere-based approaches for quantifying carbon exchange:
I) We will employ a novel combination of datasets to constrain the relationship between biomass and NEE over forested sites in Maryland. This work will combine high-resolution LiDAR-derived forest structure measurements (Dubayah, CMS 2011) with in-situ fluxes of CO2, CH4, sensible heat, and latent heat acquired from the Carbon Airborne Flux Experiment (CARAFE) (Kawa, CMS 2015) to explore questions at the flux-biomass interface: How does NEE vary with forest biomass and canopy height? How do meteorological parameters such as evapotranspiration, photosynthetically active radiation, and temperature influence the observed relationship?
II) We will use observation-based constraints to evaluate the Ecosystem Demography (ED) biophysical process model, a current CMS prototype (Hurtt, CMS 2016) that projects forest carbon sequestration potential. The ED model is initialized with LiDAR canopy height measurements, and we will extract model-estimated NEE and other relevant output to assess the degree to which the model does, or does not, capture observed relationships. This will enable us to refine underlying model processes that link forest biomass and carbon flux, better quantify the uncertainties in the ED carbon storage projections, and identify future measurement priorities.
This work directly targets several CMS goals by synergizing previous CMS activities, including remote sensing maps of forest biomass, model projections of forest carbon storage, and airborne flux measurements. This work will further refine remote-sensing methods for carbon stocks and fluxes by providing an independent evaluation to reduce uncertainty in the current ED data products. We will engage stakeholders from the Maryland Department of Environment and Department of Natural Resources to identify uncertainties and target validation efforts to benefit the state’s Regional Greenhouse Gas Initiative. With the advent of global forest structure measurements from satellites such as GEDI, direct validation of ED will establish reliability in biomass approaches to carbon flux as model-assisted prototypes scale up to global applications.
Associated Project(s):
Poster Location ID: 36
Presentation Type: Poster
Session: Poster Session 1
Session Date: Wednesday (9/27) 1:15 PM