Ian Baker Colorado State University Department of Atmospheric Science/GDPE

1. Is There Utility in Simulating Ecosystem-Level Fluxes as a Collection of Fluxes from Individual Species? Ian Baker Colorado State University Department of Atmospheric Science/GDPE With help from: Ken Davis; PSU Vince Gutschick, Connie Maxwell, Mario Montes-Helu, Erika Mortenson, Alonzo Soto, Felicia Najera, and Erik Jackson; NMSU Joe Berry, Bob Haxo, Carnegie Institute of Washington A. Scott Denning, Neil Suits, Niall Hanan; CSU

2. Motivation/Background • Comparison of model results (SiB) to observations • Ewers et al (2002) - transpiration calculated from sap flux data • Vince Gutshick – observations (LI-6200) at the leaf level (i.e. stomatal control, carboxylation capacity) • Joe Berry – provided a suite of programs that can derive SiB-type vegetation parameters from leaf-level observations

3. The Model: SiB2 • Simple Biosphere Model, version 2 (SiB2) • Sellers et al. 1996 • Biophysical land surface model • Describes heat, water and carbon transfers • in the soil, vegetation, atmosphere continuum • Developed for general circulation models • Useful at many scales, globe to point • Single canopy layer scheme • Highly non-linear • Large number of input parameters

4. SiB Vegetation Params: • 20 time-invariant biome-specific variables • 13 soil properties (moisture, thermal and respiration) • 8 NDVI-derived time-varying phenological variables (heterogeneous in space) In SiB, WLEF site is ‘mixed forest’-biome 3. All biome 3 sites are parameterized identically wrt time-invariant properties

5. SiB Time-Invariant Parameters • Canopy height • Vegetation fractional cover • Leaf angle distribution • Transmittance/reflectance • Rubisco velocity of sun-leaf • Quantum efficiency (C3/C4) • BB slope/intercept • Coupling parameters for eqn A=min(ωc,ωe,ωs) • Low-and high-temperature inhibition functions • Canopy respiration factors • Respiration fraction of Vmax • These are the variables that we can adjust • Vmax0 • BB slope • BB intercept • respcp • hhti • atheta

6. PROCEDURE • Sort Vince Gutschick’s leaf-level obs by species • Obtain species-specific values of • Vmax0 – maximum rubisco velocity • binter – BB intercept • gradm – BB slope • respcp – autotrophic respiration component • hhti – ½ point high-temp inhibition function • atheta – rubisco/light coupling factor • Create a new SiB vegetation parameter file using these new values • Run SiB

7. Sugar maple Trembling aspen Balsam fir Data from Ewers et al, 2002 Red pine Jack pine White cedar Balsam fir Speckled alder

8. Obs data asymptotes slightly above 3.0 OBS: trembling aspen, balsam fir MODEL: trembling aspen, balsam fir Comparison looks quite good

9. Obs data asymptotes near 2.0 OBS: red pine, Jack pine MODEL: Balsam fir, spruce

10. Obs data asymptotes near 2.0 OBS: dominated by white cedar, also balsam fir, speckled alder MODEL: balsam fir, speckled alder

11. Obs asymptote near 1.0 OBS: sugar maple MODEL: sugar maple

12. SOME QUESTIONS • Is it reasonable to create species-specific model vegetation for certain parameters, when a number of them, including • aparc-canopy absorbed PAR • LAI • roughness length • leaf projection • are determined from canopy-level NDVI observations? • Are the values I obtained internally consistent for each of the species I investigated?

13. SOME MORE QUESTIONS • Does this approach have the potential to lead to better simulation of fluxes of carbon, heat and moisture? • Is there potential to utilize this approach in coupling SiB to mesoscale model(s) (RAMS)? • Will higher-resolution information (both on the species and spatial/satellite scale) make species-specific land-atmosphere modeling more attractive? • Is the technique I’ve outlined adequate, or do the SiB parameters need to be made more fully self-consistent by including more parameters for each species?