HR: 10:40h
AN: B22A-02    [Abstracts]
TI: Diagnosis of the North American Carbon Cycle Using Data and Models
AU: * Denning, S
EM: denning@atmos.colostate.edu
AF: Colorado State University, Department of Atmospheric Science, Fort Collins, CO 80523-1371 United States
AU: Uliasz, M
EM: marek@atmos.colostate.edu
AF: Colorado State University, Department of Atmospheric Science, Fort Collins, CO 80523-1371 United States
AU: Zupanski, D
EM: Zupanski@cira.colostate.edu
AF: Colorado State University, Cooperative Institute for Research in the Atmosphere, Fort Collins, CO 80523 United States
AU: Collatz, J
EM: jcollatz@biome.gsfc.nasa.gov
AF: NASA Goddard Space Flight Center, Code 923, Greenbelt, MD 20771 United States
AU: Kawa, R
EM: kawa@maia.gsfc.nasa.gov
AF: NASA Goddard Space Flight Center, Code 923, Greenbelt, MD 20771 United States
AU: Gurney, K R
EM: keving@atmos.colostate.edu
AF: Colorado State University, Department of Atmospheric Science, Fort Collins, CO 80523-1371 United States
AU: Conner-Gausepohl, S
EM: sheri@atmos.colostate.edu
AF: Colorado State University, Department of Atmospheric Science, Fort Collins, CO 80523-1371 United States
AU: Andrews, A
EM: Arlyn.Andrews@noaa.gov
AF: NOAA Climate Monitoring and Diagnostics Laboratory, 325 Broadway, Boulder, CO 80303 United States
AU: Baker, I
EM: baker@atmos.colostate.edu
AF: Colorado State University, Department of Atmospheric Science, Fort Collins, CO 80523-1371 United States
AB: Estimation of spatial and temporal variations of carbon sources and sinks with their associated uncertainties has previously been limited by the representativeness of local measurements and by the sparsity of atmospheric data. Anticipating much denser coverage of both in-situ and remotely sensed carbon data later in this decade, it will be feasible to obtain much more detailed and credible information about sources and sinks. Previous experience with global inverse modeling from atmospheric trace gas observations indicates that one of the most difficult challenges regional efforts will face is the quantitative specification of temporal and spatial patterns in CO$_{2}$ exchanges and their covariance structure. This will be particularly important over the continents where the variance in atmospheric observations is dominated by diurnal, synoptic, and seasonal changes and spatial heterogeneity of sources and sinks is severe. We are developing a method for estimation of carbon sources, sinks, and uncertainties across North America at high spatial resolution by combining satellite imagery, in-situ sampling of the atmosphere, and deterministic models of weather, transport, and emissions in an optimization system. The method relies on temporal decomposition of sources and sinks processes into "fast" ecophysiology driven primarily by radiation, temperature, and moisture, and "slow" variations that control the time-mean distribution. Mesoscale weather, fast carbon cycling (photosynthesis, biological carbon allocation, and biogeochemical transformations), and atmospheric transport will be simulated using a coupled regional modeling system. Time-mean sources and sinks resulting from slow processes will then be inferred from atmospheric CO$_{2}$ observations, and will be constrained using detailed emissions estimates and fire data. Lateral boundary conditions for atmospheric CO$_{2}$ and weather and their uncertainties will be prescribed from a global model. Selected model parameters and state variables will be optimized using an Ensemble Kalman Filter method that includes formal estimation of model error. Preliminary evaluation suggests that the lateral boundary problem is tractable, and that anticipated atmospheric observing systems will provide strong constraint on twice-monthly fluxes at regional resolution.
UR: http://biocycle.atmos.colostate.edu
DE: 1615 Biogeochemical processes (4805)
DE: 0300 ATMOSPHERIC COMPOSITION AND STRUCTURE
DE: 0315 Biosphere/atmosphere interactions
DE: 0322 Constituent sources and sinks
SC: Biogeosciences [B]
MN: 2004 AGU Fall Meeting