Sensitivity of surface drag predictions using Monin–Obukhov similarity theory in non-ideal flow conditions

Abstract

Turbulent flux measurements in the atmospheric surface layer (ASL), acquired from a vertical tower of sonic anemometers, are used to investigate the transient behavior of the drag coefficient over a relatively flat, homogeneous, desert playa surface. The goal of the study is to quantify the extent to which Monin–Obukhov similarity theory (MOST) successfully predicts the empirical drag coefficient when the data are not necessarily restricted to idealized conditions. Here, “idealized” refers to the conditions under which MOST is assumed to be valid, namely that the ASL exhibits statistically stationary behavior and stresses are constant with height. In order to quantify the agreement between the empirical and theoretical drag coefficients, uncertainty bands as a function of time of day were calculated for each. These uncertainty bands account for random errors and nonstationarity effects in the momentum flux, horizontal wind velocity, and stability parameter, as well as uncertainties associated with the model parameters appearing in MOST, i.e., the von Karman constant and aerodynamic roughness length. Results show that the average uncertainties in the empirical and theoretical drag coefficients are about $$\pm \,30\%$$ and $$\pm \,20\%$$ , respectively. In the case of the former, the major contribution lies from uncertainty in the momentum flux measurements; while, the latter is dominated by uncertainty in the von Karman constant. Joint probability density functions reveal that large differences between the empirical and theoretical drag coefficient have a high probability of occurrence when the ASL is nonstationary and/or exhibits a non-constant stress layer.