Towards Better Carbon Budget Estimates for North America
Janusz
Eluszkiewicz, Atmospheric and Environmental Research, Inc., jel@aer.com
(Presenting)
Thomas
Nehrkorn, Atmospheric and Environmental Research, Inc., tnehrkor@aer.com
John
Lin, University of Waterloo, jci@waterloo.ca
Christopher
Gerbig, Max Planck Institute, Jena, cgerbig@bgc-jena.mpg.de
Saulo
Freitas, CPTEC, Brazil, sfreitas@cptec.inpe.br
Steven
Wofsy, Harvard University, wofsy@fas.harvard.edu
Daniel
Matross, Harvard University, matross@fas.harvard.edu
Pathmathevan
Mahadevan, Harvard University, mahadev@fas.harvard.edu
Marcos
Longo, Harvard University, mlongo@fas.harvard.edu
A data fusion and analysis system in which aircraft, ground, and potentially satellite data are used to infer the magnitude of terrestrial carbon fluxes over North America on seasonal and inter-annual timescales is being developed. The system is based on a "receptor-oriented" analysis framework that links concentrations at measurement locations to surface fluxes in upwind regions. The framework incorporates three main components: 1. The Stochastic Time-Inverted Lagrangian Transport (STILT) model, 2. An observation-based lateral boundary condition for CO2, and 3. A parameterization for biosphere-atmosphere fluxes that uses observations from the AmeriFlux network. In the course of the research carried out so far, it has become apparent that transport uncertainties associated with the meteorological fields used to compute STILT trajectories are the dominant source of error in CO2 budget estimates for North America (this is also likely to be the case for other regions and globally). In order to reduce these uncertainties, we have developed customized runs with the Weather Research and Forecast (WRF) model to drive STILT. We have developed an interface for the WRF/STILT coupling, including a treatment of parameterized convective fluxes. Special care has been devoted to the mass conservation properties of the resulting trajectories. Initial results from the WRF/STILT runs to simulate measured CO2 concentrations at the Argyle tower have been promising. In particular, when coupled with the Vegetation Photosynthesis and Respiration Model (VPRM), the WRF/STILT-calculated footprints lead to a realistic simulation of nocturnal CO2 measurements. Ultimately, we hope that the employment of WRF/STILT/VPRM, especially when constrained with satellite data, will bring NWP-like realism into the resulting carbon budget estimates.