Modelling of stably-stratified, convective and transitional atmospheric boundary layers using the explicit algebraic Reynolds-stress model

The atmospheric boundary layer (ABL) is in continuous turbulent motion. The heating and cooling of the Earth’s surface drives mechanic and thermodynamic processes in the ABL through enhancing and damping of atmospheric turbulence. The surface forcing has a profound effect on the diurnal cycle of temperature,wind and related variables in the ABL. Efforts have been made to model atmospheric turbulence with linear algebraic relations such as the eddy-viscosity hypothesis. Modelling of atmospheric turbulence, however, still remains a great challenge and forms an important problem in the context of numerical weather prediction and climate models. In this thesis a recently developed non-linear turbulence model, the so-called explicit algebraic Reynolds-stress (EARS) model, implemented in the context of a single-column model is used to simulate dry, stratified ABLs. We propose a new boundary-condition treatment in the EARS model. The boundary conditions correspond to the relations for vanishing buoyancy effects that are valid close to the ground. In the simulation of an idealized diurnal cycle the solutions for the stratified surface layer is in agreement with the surface scaling physics and the Monin–Obukhov functions. We have carried out simulations of the ABL with varying levels of stratification using the EARS model implemented in the context of a single-column model. We use the same model formulation and coefficients in these simulations with different thermal stratifications of the ABL. Even in the SCM formulation the EARS model solution produces a full Reynolds-stress tensor and heat flux vector. The set-up of the numerical experiments are taken from previously published large-eddy simulation (LES) studies of ABL. Simulations of stably-stratified ABL show that the EARS model is able to accurately predict the development of a low-level jet and wind turning for different levels of stratification. In addition to first-order statistics, the model also predicts more intricate features of the turbulent ABL such as the ...