The conceptual framework for modeling the inertial subrange is strongly influenced by the Kolmogorov cascade phenomena, which is nowadays the subject of significant reinterpretation. It has been argued that the effects of boundary conditions influence large-scale motion and direct interaction between large and small scales is possible by means other than passing sequentially through the full cascade. Using longitudinal (u) and vertical (w) velocity and temperature (T) time series measurements collected in the atmospheric surface layer (ASL), we evaluate walphahether the inertial subrange multifractral function (f(a)) of all three flow variables is influenced by atmospheric stability (xi), which is a bulk measure of the effect of boundary conditions on large scale flow properties for ASL turbulence. This study is the first to demonstrate that xi significantly influences f(alpha) for all three flow variables. Here, statistical significance is evaluated using a novel wavelet-based Functional Analysis of Variance (FANOVA) approach that explicitly considers different classes of xi, the flow variable type, and possible interactions between xi and the three flow variables.