Influence of Canopy Seasonal Changes on Turbulence Parameterization within the Roughness Sublayer over an Orchard Canopy

Abstract

In this observational study, the role of tree phenology on the atmospheric turbulence parameterization over 10-m-tall and relatively sparse deciduous vegetation is quantified. Observations from the Canopy Horizontal Array Turbulence Study (CHATS) field experiment are analyzed to establish the dependence of the turbulent exchange of momentum, heat, and moisture, as well as kinetic energy on canopy phenological evolution through widely used parameterization models based on 1) dimensionless gradients or 2) turbulent kinetic energy (TKE) in the roughness sublayer. Observed vertical turbulent fluxes and gradients of mean wind, temperature, and humidity, as well as velocity variances, are used in combination with empirical dimensionless functions to calculate the turbulent exchange coefficient. The analysis shows that changes in canopy phenology influence the turbulent exchange of all quantities analyzed in this study. The turbulent exchange coefficients of those quantities are twice as large near the canopy top for a leafless canopy than for a full-leaf canopy under unstable and near-neutral conditions. This turbulent exchange coefficient difference is related to the differing penetration depths of the turbulent eddies organized at the canopy top, which increase for a canopy without leaves. The TKE and dissipation analysis under near-neutral atmospheric conditions additionally shows that TKE exchange increases for a leafless canopy because of reduced TKE dissipation efficiency relative to that when the canopy is in full-leaf stage. The study closes with discussion surrounding the implications of these findings for parameterizations used in large-scale models.

Turbulent exchange of energy, momentum, and reactive gases between high vegetation and the atmospheric boundary layer

“…3.7 is β, which indicates the ratio between the friction velocity and the mean wind speed at canopy top (β = u * |U| ). Based on our CHATS analysis (Shapkalijevski et al 2016), we find that under weakly-unstable, near-neutral and weakly-stable atmospheric conditions β has constant value of 0.3, consistent with Harman and Finnigan (2007;2008). Under stronglyunstable conditions, this variable increases up to 0.4, while under strongly-stable conditions it decreases to nearly 0.25.…”

“…In consequence, the soil-related fluxes of sensible and latent heat were relatively important for the turbulent exchange processes within and above the canopy (Dupont and Patton 2012b;Shapkalijevski et al 2016). The CHATS dataset is used in our study to initialise and constrain our soil-vegetation and atmosphere modelling system.…”

“…The canopy adjustment length scale (Eq. 3.8) is defined as a measure of the distance over which an internal boundary layer with no prior knowledge of a tall canopy would need to equilibrate (adjust) to the presence of a canopy (Belcher et al 2003;Harman and Finnigan 2007) For the given CHATS experiment, Shapkalijevski et al (2016) have shown that L c =16m under near-neutral and weakly-unstable conditions. Under strongly-unstable conditions L c ≈10m, while under strongly-stable conditions L c >20m.…”

“…These structures are responsible for majority of the momentum and turbulent kinetic energy exchange between canopy and atmosphere Finnigan 2000; Finnigan et al 2009). Dependent on canopy density and height, as well as atmospheric diabatic stability, the vertical extent of the RSL is estimated to reach up to 2-3 canopy heights (Dupont and Patton 2012a;Shapkalijevski et al 2016). Representing the ABL dynamics, considering the RSL turbulence within the system, may be of importance in numerical weather prediction models (NWP) (Physick and Garratt 1995;Harman 2012).…”

“…This turbulent exchange coefficient difference is related to different penetration depth of the turbulent eddies organized at the canopy top, which increases for a canopy without leaves. The This chapter is published as Shapkalijevski et al (2016) …”