An Examination of the Lagrangian Length Scale in Plant Canopies using Field Measurements in an Analytical Lagrangian Equation

Brown, Shannon E
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University of Guelph

Studies of trace gas fluxes have advanced the understanding of bulk interactions between the atmosphere and ecosystems. Micrometeorological instrumentation is currently unable to resolve vertical scalar sources and sinks within plant canopies. Inverted analytical Lagrangian equations provide a non-intrusive method to calculate source distributions. These equations are based on Taylor's (1921) description of scalar dispersion, which requires a measure of the degree of correlation between turbulent motions, defined by the Lagrangian length scale (L). Inverse Lagrangian (IL) analyses can be unstable, and the uncertainty in L leads to uncertainty in source predictions. A review of the literature on studies using IL analysis with various scalars in a multitude of canopy types found that parameterizations where L reduces to zero at the ground produce better results in the IL analysis than those that increase closer to the ground, but no individual L parameterization gives better results than any other does. The review also found that the relationship between L and the measurable Eulerian length scale (Le) may be more complex in plant canopies than the linear scaling investigated in boundary layer flows. The magnitude and profile shape of L was investigated within a corn and a forest canopy using field measurements to constrain an analytical Lagrangian equation. Measurements of net CO2 flux, soil-to-atmosphere CO2 flux, and in-canopy profiles of CO2 concentrations provided the information required to solve for L in a global optimization algorithm for half hour intervals. For dates when the corn was a strong CO2 sink, and for the majority of dates for the forest, the optimization frequently located L profiles that follow a convex shape. A constrained optimization then smoothed the profile shape to a sigmoidal equation. Inputting the optimized L profiles in the forward and inverse Lagrangian equations leads to strong correlations between measured and calculated concentrations (corn canopy: C_{calc} = 1.00C_{meas} +52.41 mumol m^{-3}, r^2 = 0.996; forest canopy: C_{calc} = 0.98C_{meas} +276.5 mumol m^{-3}, r^2 = 0.99) and fluxes (corn canopy: F_{soil} = 0.67F_{calc} - 0.12 mumol m^{-2}s^{-1}, r^2 = 0.71, F_{net} = 1.17F_{calc} + 1.97mumol m^{-2}s^{-1}, r^2 = 0.85; forest canopy: F_{soil} = 0.72F_{calc} - 1.92 mumol m^{-2}s^{-1}, r^2 = 0.18, F_{net} = 1.24F_{calc} + 0.65 mumol m^{-2}s^{-1}, r^2 = 0.88). In the corn canopy, coefficients of the sigmoidal equation were specific to each half hour and did not scale with any measured variable. Coefficients of the optimized L equation in the forest canopy scaled weakly with variables related to the stability above the canopy. Plausible L profiles for both canopies were associated with negative bulk Richardson number values.

micrometeorology, carbon fluxes, analytical Lagrangian equations, nonlinear parameter estimation, canopy turbulence, agrometeorology, length scale