Towards stochastic modeling of turbulence in the stable atmospheric boundary layer

• Applicant: Professor Dr.-Ing. Rupert Klein, since 4/2021
• Subject Area: Atmospheric Science
• Term: from 2015 to 2022
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 310574835

Turbulence in stably stratified conditions is characterised by an unsteady behaviour caused by the interactions of processes at multiple scales. Formulating accurate parameterisation schemes represents an ongoing challenge for atmospheric models. While weakly stable conditions can be represented through adaptations of Monin-Obukhov Similarity Theory, very stable or weak wind situations are still poorly understood. When the wind is too weak to sustain turbulence, the flow becomes controlled mainly by gravity waves, density currents or other types of motions leading to localised shear acceleration on the so-called sub-mesoscales. The unsteady forcing results in intermittent turbulent bursts that can be decoupled from the surface, thus breaking down assumptions that form the basis of surface-based modelling. Challenges to accurately describe SBL dynamics are twofold. On the one hand, a better understanding and representation of transitions between flow regimes exhibiting different dynamical properties is required. On the other hand, intermittent turbulence and interactions with sub-mesoscale motions that dominate the flow in very stable regimes need to be characterised and considered in parameterisations. This project aims at deriving a stochastic model of turbulence that can effectively represent non-stationary turbulence enhancement mechanisms. Since the start of the funding period, we devised a framework to systematically classify flow regimes distinguished by their scale interaction and energy transfer properties. We provided statistical evidence of a lack of equilibrium of turbulent observables in very stable flow regimes, resulting in the necessity to model the very stable boundary layer by using high order stochastic processes. The lack of equilibrium was also evidenced by the predominance of highly anisotropic turbulence occurring in flow regimes under the influence of sub-mesoscale motions. Additionally, we provided statistics of non-turbulent or hybrid flow structures in classified flow regimes.Equipped with knowledge from data-analyses, developing and testing models representing non-stationary turbulence and SBL regime transitions is the challenge foreseen for the project extension. Stochastic inflows will be generated to represent sub-mesoscale shear enhancement in a Large Eddy Simulation (LES) tool. By controlling the topology and scale of the inflow structures, we will be able to analyse the adaptation of turbulence to unsteady, stochastic forcing in numerical simulations. The novel stochastically forced LES framework will be used to investigate regime transitions in the presence of random forcing by sub-mesoscale motions, and to quantify the random impact of the forcing on turbulent kinetic energy, which is key to parameterisation development. Finally, dynamical properties of experimental data will be quantified as a way to test the performance of a recently introduced conceptual model of regime transitions.

• DFG Programme: Research Grants
• International Connection: France, Sweden, USA
• Cooperation Partners: Dr. Danijel Belusic; Professor Dr. Elie Bou-Zeid; Privatdozent Dr. Davide Faranda
• Ehemalige Antragstellerin: Professorin Dr. Nikki Vercauteren, until 3/2021