Atmospheric Stability Influences on Coupled Boundary Layer and Canopy Turbulence

Abstract

Large-eddy simulation of atmospheric boundary layers interacting with a coupled and resolved plant canopy reveals the influence of atmospheric stability variations from neutral to free convection on canopy turbulence. The design and implementation of a new multilevel canopy model is presented. Instantaneous fields from the simulations show that organized motions on the scale of the atmospheric boundary layer (ABL) depth bring high momentum down to canopy top, locally modulating the vertical shear of the horizontal wind. The evolution of these ABL-scale structures with increasing instability and their impact on vertical profiles of turbulence moments and integral length scales within and above the canopy are discussed. Linkages between atmospheric turbulence and biological control impact horizontal scalar source distributions. Decreasing spatial correlation between momentum and scalar fluxes with increasing instability results from ABL-scale structures spatially segregating momentum and scalar exchange at canopy top. In combination, these results suggest the need for roughness sublayer parameterizations to incorporate an additional length or time scale reflecting the influence of ABL-scale organized motions.

Explaining the convector effect in canopy turbulence by means of large-eddy simulation

“…The representation of the canopy in the LES follows the standard distributed drag parameterization (Shaw and Schumann, 1992;Watanabe, 2004;Patton et al, 2015) by adding an additional term in the momentum budget equations as…”

“…This SGS-TKE scheme after Deardorff (1980) is deemed to be an improvement over the more traditional Smagorinsky (1963) parameterization since the SGS-TKE allows for a much better estimation for the velocity scale corresponding to the subgrid-scale fluctuations (Maronga et al, 2015). Further details of the LES model can be found in the literature and are not discussed here (Shaw and Schumann, 1992;Watanabe, 2004;Maronga et al, 2015;Patton et al, 2015). For our simulation, the number of grid points in the x, y, and z directions are 320, 320, and 640, respectively, with grid resolutions of 3.91, 3.91, and 1.95 m in the respective directions.…”

“…A recent publication by Patton et al (2015) studied the influence of different atmospheric instability classes on coupled boundary layer-canopy turbulence. In this work, those same instability classes are simulated to put our hypothesis to the test.…”

Revisiting Kelvin Helmholtz Instabilities and von Kármán Vortices in Canopy Turbulence

“…The representation of the canopy in the LES follows the standard distributed drag parameterization (Shaw and Schumann, 1992;Watanabe, 2004;Patton et al, 2016) by adding an additional term in the mo-5 mentum budget equations as F di = C d a |u|u i where a is a one sided frontal plant area density (PAD), C d is a dimensionless drag coefficient assumed to be 0.3 (Katul et al, 2004;Banerjee et al, 2013), |u| is the resolved wind speed and u i is the resolved velocity component (i = 1, 2, 3, i.e. u, v and w), i.e.…”

“…This SGS-TKE scheme after Deardorff (1980) is deemed to be an improvement over the more traditional Smagorinsky (1963) parameterization since the SGS-TKE allows for a much better estimation for the velocity scale corresponding to the subgrid scale fluctuations 15 (Maronga et al, 2015). Further details of the LES model can be found in the literature and are not discussed here (Shaw and Schumann, 1992;Watanabe, 2004;Maronga et al, 2015;Patton et al, 2016). Each simulation is run for 8200 s with a time step of 0.1s, while the output of first 6400 s are discarded to achieve computational equilibrium.…”