The mean flow profile within and above a tall canopy is well known to violate the standard boundary-layer flux-gradient relationships. Here we present a theory for the flow profile that is comprised of a canopy model coupled to a modified surface-layer model. The coupling between the two components and the modifications to the surface-layer profiles are formulated through the mixing layer analogy for the flow at a canopy top. This analogy provides an additional length scale-the vorticity thickness-upon which the flow just above the canopy, within the so-called roughness sublayer, depends. A natural form for the vertical profiles within the roughness sublayer follows that overcomes problems with many earlier forms in the literature. Predictions of the mean flow profiles are shown to match observations over a range of canopy types and stabilities.The unified theory predicts that key parameters, such as the displacement height and roughness length, have a significant dependence on the boundary-layer stability. Assuming one of these parameters a priori leads to the incorrect variation with stability of the others and incorrect predictions of the mean wind speed profile. The roughness sublayer has a greater impact on the mean wind speed in stable than unstable conditions. The presence of a roughness sublayer also allows the surface to exert a greater drag on the boundary layer for an equivalent value of the near-surface wind speed than would otherwise occur. This characteristic would alter predictions of the evolution of the boundary layer and surface states if included within numerical weather prediction models.

Forest canopies are important components of the terrestrial carbon budget, which has motivated a worldwide effort, FLUXNET, to measure CO2 exchange between forests and the atmosphere. These measurements are difficult to interpret and to scale up to estimate exchange across a landscape. Here we review the effects of complex terrain on the mean flow, turbulence, and scalar exchange in canopy flows, as exemplified by adjustment to forest edges and hills, including the effects of stable stratification. We focus on the fundamental fluid mechanics, in which developments in theory, measurements, and modeling, particularly through large-eddy simulation, are identifying important processes and providing scaling arguments. These developments set the stage for the development of predictive models that can be used in combination with measurements to estimate exchange at the landscape scale.

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.

Turbulence above and within canopies has characteristics distinct from that over rough surfaces. The vertical transport of momentum and scalars is dominated by coherent structures whose origin is now thought to be the result of the unstable inflexion in the profile of the mean wind speed established by the application of canopy drag. This distinctive property leads to the failure of the standard Monin-Obukhov flux-profile relationships over homogeneous canopies, relationships that are assumed in many surface exchange schemes within numerical weather prediction and general circulation models. A modification of the flux-profile relationships is presented that incorporates the effects of the canopy turbulence. The subsequent impacts on the evolution of the surface energy balance and boundary-layer state are investigated within a simple numerical model for the evolution of the boundary layer and canopy state. By comparing cases with and without the modification it is shown that canopy-generated turbulence can lead, not only to the alteration of the flux-profile relationships above the canopy, but also to a different evolution of the surface energy balance and differences in near-surface conditions that would be significant in numerical weather prediction. More fundamentally, the modifications to the flux-profile relationships imply that parameters such as the roughness length and displacement height for canopies should not be considered as invariant properties, but rather as properties that depend on the flow and hence vary systematically with the diabatic stability of the boundary layer.

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The land surface component of the Australian Community Climate and Earth System Simulator (ACCESS) is one difference between the two versions of ACCESS used to run simulations for the Coupled Model Intercomparison Project (CMIP5). The Met Office Surface Exchange Scheme (MOSES) and the Community Atmosphere Biosphere Land Exchange (CABLE) model are described and compared. The impact on the simulated present day land surface climatology is assessed, in both atmosphere only and coupled model cases. Analysis is focused on seasonal mean precipitation and screen-level temperature, both globally and for Australia. Many of the biases from observations are common across both ACCESS versions and both atmosphere only and coupled cases. Where the simulations from the two versions differ, the choice of land surface model is often only a small contributor with changes to the cloud simulation also important. Differences that can be traced to the land surface model include warm biases with CABLE due to underestimation of surface albedo, better timing of northern hemisphere snowmelt and smaller seasonal and diurnal temperature ranges with CABLE than MOSES.

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Abstract.A primary goal of Earth system modelling is to improve understanding of the interactions and feedbacks between human decision making and biophysical processes. The nexus of land use and land cover change (LULCC) and the climate system is an important example. LULCC contributes to global and regional climate change, while climate affects the functioning of terrestrial ecosystems and LULCC. However, at present, LULCC is poorly represented in global circulation models (GCMs). LULCC models that are explicit about human behaviour and decision-making processes have been developed at local to regional scales, but the principles of these approaches have not yet been applied to the global scale level in ways that deal adequately with both direct and indirect feedbacks from the climate system. In this article, we explore current knowledge about LULCC modelling and the interactions between LULCC, GCMs and dynamic global vegetation models (DGVMs). In doing so, we propose new ways forward for improving LULCC representations in Earth system models. We conclude that LULCC models need to better conceptualise the alternatives for upscaling from the local to global scale. This involves better representation of human agency, including processes such as learning, adaptation and agent evolution, formalising the role and emergence of governance structures, institutional arrangements and policy as endogenous processes and better theorising about the role of teleconnections and connectivity across global networks. Our analysis underlines the importance of observational data in global-scale assessments and the need for coordination in synthesising and assimilating available data. Published by Copernicus