Modeling canopy-induced turbulence in the Earth system: a unified parameterization of turbulent exchange within plant canopies and the roughness sublayer (CLM-ml v0)

Abstract

Abstract. Land surface models used in climate models neglect the roughness sublayer and parameterize within-canopy turbulence in an ad hoc manner. We implemented a roughness sublayer turbulence parameterization in a multilayer canopy model (CLM-ml v0) to test if this theory provides a tractable parameterization extending from the ground through the canopy and the roughness sublayer. We compared the canopy model with the Community Land Model (CLM4.5) at seven forest, two grassland, and three cropland AmeriFlux sites over a range of canopy heights, leaf area indexes, and climates. CLM4.5 has pronounced biases during summer months at forest sites in midday latent heat flux, sensible heat flux, gross primary production, nighttime friction velocity, and the radiative temperature diurnal range. The new canopy model reduces these biases by introducing new physics. Advances in modeling stomatal conductance and canopy physiology beyond what is in CLM4.5 substantially improve model performance at the forest sites. The signature of the roughness sublayer is most evident in nighttime friction velocity and the diurnal cycle of radiative temperature, but is also seen in sensible heat flux. Within-canopy temperature profiles are markedly different compared with profiles obtained using Monin–Obukhov similarity theory, and the roughness sublayer produces cooler daytime and warmer nighttime temperatures. The herbaceous sites also show model improvements, but the improvements are related less systematically to the roughness sublayer parameterization in these canopies. The multilayer canopy with the roughness sublayer turbulence improves simulations compared with CLM4.5 while also advancing the theoretical basis for surface flux parameterizations.

A Comparison of the Diel Cycle of Modeled and Measured Latent Heat Flux During the Warm Season in a Colorado Subalpine Forest

“…In general, it appears that CLM u ∗ has a low‐bias relative to the observed u ∗ of around 0.1 m s −1 . Many flux observations sites show a similar u ∗ bias with CLM4.5 (e.g., Bonan et al, ). Because u ∗ is such an important variable, we circumvented this issue by using observed u ∗ as an input to CLM4.5 (see Table for specific configurations).…”

Simulation of Longwave Enhancement in Boreal and Montane Forests

“…Improvements to SNOWPACK by Gouttevin et al () and this study focused mainly on the impact of radiation. However, Bonan et al () found turbulence parameterizations having a substantial impact on, among other variables, radiative temperature and reduced overestimation of diurnal ranges by implementing a roughness sublayer and subdividing the vegetation layer.…”

Dry Deposition of Ozone Over Land: Processes, Measurement, and Modeling

“…The multilayer canopy model described by Bonan et al () with the Harman and Finnigan (, ) analytic roughness sublayer mixing scheme shows potential for prognostic simulation of canopy vertical exchange. While the Harman and Finnigan (, ) scheme relies on K‐theory, its introduction of a length scale associated with the turbulent eddies produced by wind shear at the canopy top incorporates the influence of countergradient transport.…”

“…While the Harman and Finnigan (, ) scheme relies on K‐theory, its introduction of a length scale associated with the turbulent eddies produced by wind shear at the canopy top incorporates the influence of countergradient transport. Bonan et al () find that the Harman and Finnigan (, ) scheme improves simulation of friction velocity and ambient temperature at several forest and grassland sites. With a multilayer canopy large eddy simulation (LES) model explicitly resolving turbulence above and in a forest canopy, Patton et al () show atmospheric stability exerts a control on vertical exchange at the top of the canopy through the structure of the atmospheric boundary layer, suggesting roughness sublayer parameterizations consider the effect.…”

“…However, near-field parameterizations are designed for neutral stability conditions, and their utility hinges on whether observed wind profiles and turbulence statistics can be prescribed (Harman & Finnigan, 2008). The multilayer canopy model described by Bonan et al (2018) with the Finnigan (2007, 2008) analytic roughness sublayer mixing scheme shows potential for prognostic simulation of canopy vertical exchange. While the Finnigan (2007, 2008) scheme relies on K-theory, its introduction of a length scale associated with the turbulent eddies produced by wind shear at the canopy top incorporates the influence of countergradient transport.…”