The Interactions Between SiBCASA-simulated Surface Fluxes, Carbon Pools, Biomass, and North American Climate Variability
Lixin
Lu, Department of Atmospheric Science, Colorado State University, and CIRES/ATOC, University of Colorado, lixin@atmos.colostate.edu
(Presenting)
Kevin
Schaefer, NSIDC/CIRES, University of Colorado, kevin.schaefer@nsidc.org
Tingjun
Zhang, NSIDC/CIRES, University of Colorado, tzhang@nsidc.org
Ian
Baker, Department of Atmospheric Science, Colorado State University, baker@atmos.colostate.edu
Scott
Denning, Department of Atmospheric Science, Colorado State University, denning@atmos.colostate.edu
Simple Biosphere model (SiB2.5) is coupled with Carnegie-Ames-Stanford Approach model (CASA) to form a new model, SiBCASA, which is capable of simulating diurnal to interannual variations of terrestrial carbon fluxes and biomass at plot to global scales. While prescribing leaf biomass derived from remotely sensed Normalized Difference Vegetation Index (NDVI), SiBCASA can dynamically allocate carbon to leaf, root, and wood pools, and explicitly calculate autotrophic respiration. To improve winter-process simulations, Schaefer et al [2008b] introduced Sturm et al. [1995] snow classification system, Lawrence and Slater [2005] organic soil model, and extended the soil column depth to 15 m.
Nine eddy covariance flux tower sites (include Barrow, Bondville, Boreas old black spruce, Harvard Forest, Howland Forest, Lethbridge, Niwot Ridge, Park Falls, and Winder River) across a range of the climate-ecosystem zones are selected for initial evaluations of SiBCASA-simulated biophysical and biogeochemical processes. The meteorological forcings are derived from 32-km grid-spacing North American Regional Reanalysis product spanning 1979 through 2003 at 3-hourly time-step. Modeled surface fluxes and biomass at these sites are evaluated against tower-observed values. A suite of sensitivity experiment is performed by perturbing the atmospheric forcing variables one at a time. Maximum and minimum temperatures are increased and decreased 2 deg Celsius, while precipitations are increased and decreased 25% of their original values. SiBCASA-simulated surface fluxes and biomass are also sensitive to the initial conditions of soil moisture and temperature, snow depth, and initial woody pool size. Statistical analyses are being carried out to understand how these climate variations and changes in initial conditions interact with the flux and biomass predictions. These experiments, by artificially manipulating the input data to imitate possible future scenarios, will enable us to assess and quantify the sensitivity of North American carbon cycle to large-scale climate change.
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