Numerical Experiments of Atmospheric Boundary Layer flows

Anthropogenic emissions of greenhouse gases due to human activity is causing global warming and inducing climate change. A major implication of global warming is the decreasing ice mass in the polar regions resulting in sea-level rise. It is now known that sublimation of drifting and blowing snow is one of the dominant terms of the mass balance of Antarctica. There are various efforts underway to curtail greenhouse gas emissions and mitigate the impact of global warming. One of the most promising solutions involves using non-polluting renewable sources of electricity. Global wind energy estimates have been shown to be far in excess of current and projected energy requirements. From a fluid dynamics perspective, turbulence in the lowest region of the atmosphere, known as the Atmospheric boundary layer (ABL) exerts significant control on both wind energy extraction systems as well as drifting and blowing snow particles, both of which can be considered as distributed drag elements that act as a sink of momentum.

The first part of the thesis is concerned with large-eddy simulations (LES) of the turbulent, time-varying ABL with an immersed wind farm. First, a new time-adaptive wind turbine model for LES is introduced that enables the wind turbines to yaw and realign with the incoming wind vector, similar to real wind turbines. The performance of the new model is tested with in a neutrally-stratified ABL forced with a time varying geostrophic wind as well as a synthetic time-changing thermal ABL. Next, the effect of extensive terrestrial wind farms on the spatio-temporal structure of the diurnally-evolving ABL is explored. It is shown that extensive wind farms substantially perturb the vertical structure of the stable boundary layer and the dynamics of the `morning' transition. The effect of these perturbations on the potential power output of an extensive wind farm output is also analysed. Finally, flow characteristics through finite-sized wind farms and the influence of the wind-farm configuration on modulating this evolution is explored using LES. The principal aim for this part of the thesis is to identify regions of flow-adjustment and flow equilibrium within the wind farm. Three diagnostic variables, namely, the wind-farm induced effective surface roughness, the wake viscosity and the wake-expansion coefficient are also computed using the LES-generated database and are used to characterize the flow.

In the second part of the thesis, LES of drifting and blowing snow are performed with the aim of calculating sublimation of saltating snow grains. The Thorpe and Mason [1966] model for calculating the mass lost from a sublimating snow grain is the basis of all existing estimates of drifting snow sublimation. This model is revisited to test its validity for saltating snow grains. It is shown that residence times for saltating snow grains are such that using the steady-state model of sublimation losses by the Thorpe and Mason (TM) approach is questionable. Furthermore, the residence times were found to be independent of the imposed pressure gradient and buoyancy. The relaxation time needed for the unsteady mass loss rate to reconcile with the TM solution is found to be comparable to typical residence times for saltating grains and the resulting errors due to use of the TM approach are quantified.