The Detection, Genesis, and Modeling of Turbulence Intermittency in the Stable Atmospheric Surface Layer

Abstract

Intermittent transitions between turbulent and nonturbulent states are ubiquitous in the stable atmospheric surface layer (ASL). Data from two field experiments in Utqiaġvik, Alaska, and from direct numerical simulations are used to probe these state transitions so as to (i) identify statistical metrics for the detection of intermittency, (ii) probe the physical origin of turbulent bursts, and (iii) quantify intermittency effects on overall fluxes and their representation in closure models. The analyses reveal three turbulence regimes, two of which correspond to weakly turbulent periods accompanied by intermittent behavior (regime 1: intermittent; regime 2: transitional), while the third is associated with a fully turbulent flow. Based on time series of the turbulence kinetic energy (TKE), two nondimensional parameters are proposed to diagnostically categorize the ASL state into these regimes; the first characterizes the weakest turbulence state, while the second describes the range of turbulence variability. The origins of intermittent turbulence activity are then investigated based on the TKE budget over the identified bursts. While the quantitative results depend on the height, the analyses indicate that these bursts are predominantly advected by the mean flow, produced locally by mechanical shear, or lofted from lower levels by turbulent ejections. Finally, a new flux model is proposed using the vertical velocity variance in combination with different mixing length scales. The model provides improved representation (correlation coefficients with observations of 0.61 for sensible heat and 0.94 for momentum) compared to Monin–Obukhov similarity (correlation coefficients of 0.0047 for sensible heat and 0.49 for momentum), thus opening new pathways for improved parameterizations in coarse atmospheric models.