Simulating the Unsteady Stable Boundary Layer With a Stochastic Stability Equation.

Turbulence in very stable boundary layers is typically unsteady and intermittent. The study implements a stochastic modeling approach to represent unsteady mixing possibly associated with intermittency of turbulence and with unresolved fluid motions such as dirty waves or drainage flows. The stochastic parameterization is introduced by randomizing the mixing lengthscale used in a Reynolds average Navier‐Stokes (RANS) model with turbulent kinetic energy closure, resulting in a stochastic unsteady RANS model. The randomization alters the turbulent momentum diffusion and accounts for sporadic events of possibly unknown origin that cause unsteady mixing. The paper shows how the proposed stochastic parameterization can be integrated into a RANS model used in weather‐forecasting and its impact is analyzed using neutrally and stably stratified idealized numerical case studies. The simulations show that the framework can successfully model intermittent mixing in stably stratified conditions, and does not alter the representation of neutrally stratified conditions. It could thus present a way forward for dealing with the complexities of unsteady flows in numerical weather prediction or climate models. Plain Language Summary: Limited computer resources lead to a simplified representation of unresolved small‐scale processes in weather forecasting and climate models, through parameterization schemes. Among the parameterized processes, turbulent fluxes exert a critical impact on the exchange of heat, water and carbon between the land and the atmosphere. Turbulence theory was, however, developed for homogeneous and flat terrain, with stationary conditions. At nighttime or in cold environment, turbulence is typically non‐stationary, weak and intermittent and the classical theory fails. Part of the intermittent mixing is due to turbulence enhancement by small‐scale wind variability. In the following, a random modeling approach is used to enhance turbulent mixing due to small‐scale wind variability and intermittency of mixing. The proposed approach is shown to be a viable approach to represent the effect of small‐scale variability of mixing for different atmospheric flow conditions. Key Points: A stochastic parameterization of turbulence is implemented in a Reynolds average Navier‐Stokes (RANS) model to represent unsteady mixingThe introduced stochastic perturbations of the mixing length enable the simulation of intermittent turbulence in the stable boundary layerThe stochastic unsteady RANS model does not alter the simulation of neutral conditions [ABSTRACT FROM AUTHOR]