Variability of Sub-Canopy Flow, Temperature, and Horizontal Advection in Moderately Complex Terrain

Abstract

We examine the space–time structure of the wind and temperature fields, as well as that of the resulting spatial temperature gradients and horizontal advection of sensible heat, in the sub-canopy of a forest with a dense overstorey in moderately complex terrain. Data were collected from a sensor network consisting of ten stations and subject to orthogonal decomposition using the multiresolution basis set and stochastic analyses including two-point correlations, dimensional structure functions, and various other bulk measures for space and time variability. Despite some similarities, fundamental differences were found in the space–time structure of the motions dominating the variability of the sub-canopy wind and temperature fields. The dominating motions occupy similar spatial, but different temporal, scales. A conceptual space–time diagram was constructed based on the stochastic analysis that includes the important end members of the spatial and temporal scales of the observed motions of both variables. Short-lived and small-scale motions govern the variability of the wind, while the diurnal temperature oscillation driven by the surface radiative transfer is the main determinant of the variability in the temperature signal, which occupies much larger time scales. This scale mismatch renders Taylor’s hypothesis for sub-canopy flow invalid and aggravates the computation of meaningful estimates of horizontal advective fluxes without dense spatial information. It may further explain the ambiguous and inconclusive results reported in numerous energy and mass balance and advection studies evaluating the hypothesis that accounting for budget components other than the change in storage term and the vertical turbulent flux improves the budget closure when turbulent diffusion is suppressed in plant canopies. Estimates of spatial temperature gradients and advective fluxes were sensitive to the network geometry and the spatial interpolation method. The assumption of linear spatial temperature gradients was not supported by the results, and leads to increased spatial and temporal variability of inferred spatial gradients and advection estimates. A method is proposed to estimate the appropriate minimum network size of wind and temperature sensors suitable for an evaluation of energy and mass balances by reducing spatial and temporal variability of the spatially sampled signals, which was estimated to be on the order of 200 m at the study site.