Similarity of wind speed in the Roughness Sublayer above vegetation

In fluid dynamics, the theory of similarity states that, under certain conditions, the statistical characteristics of turbulent flows remain invariant when normalized by dimensionless parameters. Above irregular surfaces, an atmospheric layer called the Roughness Sublayer (RS) is formed. Various measurements of turbulent fluxes are made within the RS. However, there is still no unified similarity theory that properly captures the turbulence characteristics in this layer. Contextually, we propose using characteristic scales defined at the inflection point of the vertical wind speed profile as normalization parameters, enabling the formulation of a similarity theory for wind speed over dense vegetation. These scales are: the height of the inflection point in the wind profile (zi), the wind speed at that point (ui), and the shear length scale (Ls). Wind speed profiles measured in three dense forest areas in the Brazilian Amazon and in a cornfield in the United States were used. The results indicated that the normalization of wind profiles using zi, ui and Ls showed significantly lower statistical errors compared to normalization by "classical" parameters, such as wind speed at canopy height (uh) and average canopy height (h). In addition, this normalization made it possible to model the vertical wind speed profile using the equation U/ui = 1 + arctan[(z - zi)/Ls], which can be applied even with a limited number of measurement heights, provided that ui, zi and Ls are properly parameterized. Moreover, this model performs better than exponential models in simulating wind in the air layer between h/2 and h, which is critically important for accurately representing turbulent exchanges between vegetated surfaces and the atmosphere. These findings represent an advance in the formulation of more realistic parameterizations of turbulent exchange processes in the RS and constitute an essential step towards the development of a similarity theory specific to this layer.