HR: 09:45h
AN: B31E-08    [Abstracts]
TI: The use of Fluxnet to improve processes and parameters in land surface models: a case study with the NCAR Community Land Model
AU: Oleson, K W
EM: oleson@cgd.ucar.edu
AF: National Center for Atmospheric Research, Terrestrial Sciences Section, Boulder, CO 80305, United States
AU: * Stockli, R
EM: stockli@atmos.colostate.edu
AF: Colorado State University, Department of Atmospheric Science, Fort Collins, CO 80523, United States
AU: * Stockli, R
EM: stockli@atmos.colostate.edu
AF: ETH Zurich, Institute for Atmospheric and Climate Sciences, Zurich, ZH 8092, Switzerland
AU: * Stockli, R
EM: stockli@atmos.colostate.edu
AF: NASA Earth Observatory, Goddard Space Flight Center, Greenbelt, MD 20771, United States
AU: Lawrence, D M
EM: dlawren@ucar.edu
AF: National Center for Atmospheric Research, Terrestrial Sciences Section, Boulder, CO 80305, United States
AU: Niu, G
EM: niu@speer.geo.utexas.edu
AF: Universtity of Texas at Austin, Department of Geological Sciences, Austin, TX 78712, United States
AU: Thornton, P E
EM: thornton@ucar.edu
AF: National Center for Atmospheric Research, Terrestrial Sciences Section, Boulder, CO 80305, United States
AU: Yang, Z
EM: liang@mail.utexas.edu
AF: Universtity of Texas at Austin, Department of Geological Sciences, Austin, TX 78712, United States
AU: Bonan, G
EM: bonan@cgd.ucar.edu
AF: National Center for Atmospheric Research, Terrestrial Sciences Section, Boulder, CO 80305, United States
AU: Denning, S
EM: denning@atmos.colostate.edu
AF: Colorado State University, Department of Atmospheric Science, Fort Collins, CO 80523, United States
AU: Leuning, R
EM: Ray.Leuning@csiro.au
AF: Commonwealth Scientific and Industrial Research Organisation, Marine and Atmospheric Research, Canberra, ACT 2601, Australia
AU: Richardson, A
EM: andrew.richardson@unh.edu
AF: University of New Hampshire, Complex Systems Research Center, Durham, NH 03824, United States
AU: Running, S W
EM: swr@ntsg.umt.edu
AF: University of Montana, Numerical Terradynamics Simulation Group, Missoula, MT 59812, United States
AU: Seneviratne, S I
EM: sonia.seneviratne@env.ethz.ch
AF: ETH Zurich, Institute for Atmospheric and Climate Sciences, Zurich, ZH 8092, Switzerland
AB: The Community Land Model version 3 (CLM3) simulates land-atmosphere exchanges in response to climatic forcings. CLM3 has known biases in the surface energy partitioning as a result of deficiencies in its parameterizations. Such models however need to be robust for multi-decadal global climate simulations. Fluxnet now provides an extensive data source for investigating land processes since it encompasses a global range of ecosystem-climate interactions. Data from 22 Fluxnet sites are used to identify model deficiencies. Process-based knowledge from these observations can help to improve (a) physical processes and (b) reduce uncertainty of empirical parameters in the model. Including a prognostic aquifer and a new bare soil evaporation resistance formulation results in a significantly improved soil hydrology and energy partitioning. Terrestrial water storage increased by up to 300 mm in warm climates and decreased in cold climates. Nitrogen control of photosynthesis is revealed as another missing process in the model. These improvements increase the correlation coefficient of latent heat fluxes from a range of 0.5-0.6 to the range of 0.7-0.9. Additionally, RMSE of the simulated sensible heat fluxes decrease by 20-50 %. Remaining deficiencies (such as overestimated primary production during the wet season in the tropics) might be attributed to model parameter uncertainties once processes are reasonably well constrained. A flux tower data assimilation framework for land surface models based on the Ensemble Kalman Filter may be used at this point in order to reduce model parameter uncertainty. First results from using such an approach are presented as an outlook and should serve as a starting point for discussion of Fluxnet synthesis efforts in this direction. In summary, Fluxnet has proven to be a valuable tool to develop and validate land surface models prior to their application. Such a model inherits a realistic representation of ecosystem-climate relationships for many ecosystems and climate zones and it will therefore be more suitable for computationally expensive coupled global climate simulations.
DE: 0426 Biosphere/atmosphere interactions (0315)
DE: 0434 Data sets
DE: 0480 Remote sensing
DE: 1847 Modeling
DE: 3315 Data assimilation
SC: Biogeosciences [B]
MN: 2007 Fall Meeting