HR: 0800h
AN: B51A-0923    [Abstracts]
TI: Assimilation Modeling of CO$_{2}$ Fluxes at Niwot Ridge, Colorado, and Strategy for Scaling up to the Region
AU: * Sacks, W J
EM: sacks@ucar.edu
AF: National Center for Atmospheric Research, Climate and Global Dynamics Division 1850 Table Mesa Drive, Boulder, CO 80307 United States
AU: Schimel, D S
EM: schimel@ucar.edu
AF: National Center for Atmospheric Research, Climate and Global Dynamics Division 1850 Table Mesa Drive, Boulder, CO 80307 United States
AU: Monson, R K
EM: Russell.Monson@colorado.edu
AF: University of Colorado, Department of Ecology and Evolutionary Biology, Boulder, CO 80309 United States
AU: Braswell, B H
EM: Rob.Braswell@unh.edu
AF: University of New Hampshire, Complex Systems Research Center, Durham, NH 03824 United States
AB: The net ecosystem exchange of CO$_{2}$ (NEE) is the small difference between two large fluxes: photosynthesis and ecosystem respiration. Consequently, separating NEE into its component fluxes, and determining the process-level controls over these fluxes, is a difficult problem. In this study, we used a data assimilation approach with the SIPNET flux model to extract process-level information from five years of eddy covariance data at an evergreen forest in the Colorado Rocky Mountains. SIPNET runs at a half-daily time step, and has two vegetation carbon pools, a single aggregated soil carbon pool, and a soil moisture sub-model that models both evaporation and transpiration. By optimizing the model parameters before evaluating model-data mismatches, we were able to probe the model structure independently of any arbitrary parameter set. In doing so, we were able to learn about the primary controls over NEE in this ecosystem. We also used this parameter optimization, coupled with a formal model selection criterion, to investigate the effects of making hypothesis-driven changes to the model structure. These experiments lent support to the hypotheses that (1) photosynthesis, and possibly foliar respiration, are down-regulated when the soil is frozen, and (2) the metabolic processes of soil microbes vary in the summer and winter, possibly because of the existence of distinct microbial communities at these two times. Finally, we present a strategy for scaling the modeled fluxes up to the region. This scaling approach incorporates data from multiple eddy covariance flux towers and from the satellite-based MODIS sensor to derive NEE estimates for the entire coniferous forest biome of Colorado.
DE: 1694 Instruments and techniques
DE: 1615 Biogeochemical processes (4805)
DE: 0315 Biosphere/atmosphere interactions
SC: Biogeosciences [B]
MN: 2004 AGU Fall Meeting