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{html}<center><font size="4">&quot;There is no forgiveness in nature.&quot; - Ugo Betti</font></center>{/html} {html}<a name="ABL"></a>{/html} !! Atmospheric Boundary Layer [./abl_u.jpg|right] The atmospheric boundary layer (ABL) is the lowest part of the atmosphere which is in direct interaction with the Earth’s surface and responds to surface forcing with time scales of one hour or less. It is a highly turbulent boundary-layer flow with a Reynolds number of order ~ 10{html}<sup>9</sup>{/html}. As a result, the ABL flow has a huge continuous range of turbulent eddy scales, ranging from the integral scale, on the order of the boundary-layer depth ~ O(1 km), down to the Kolmogorov viscous dissipation scale ~ O(1 mm). Prediction of ABL flow is complicated by the often strong temporal and spatial variability of the land-surface characteristics (e.g., surface temperature and aerodynamic roughness). The real ABL is strongly influenced by temporal variability of buoyancy (positive and negative) effects associated with the diurnal cycle of net radiation at the land surface. For an interactive simulation of a typical diurnal cycle evolution of the ABL, the reader is referred to an [Atmospheric Boundary Layer Simulator|http://eddycation.safl.umn.edu]. Moreover, land surfaces are often characterized by complex topography, which is in many cases multifractal, as well as spatial heterogeneity of aerodynamic roughness and temperature associated with different land-cover types. This leads to highly non-linear interactions between the complexity of the land surfaces and the ABL turbulence. Modeling ABL turbulent fluxes of momentum and scalars (heat, water vapor and pollutants) is of great importance to forecast weather, climate, air pollution, wind loads on structures, and wind energy resources. Indeed the need for accurate weather prediction has provided much of the impetus for the development of numerical methods in turbulence research. Prediction of these fluxes at regional scales, which is required in most atmospheric models, is a challenging task due to the highly non-linear interactions between ABL turbulence and the complex multi-scale structure of the land surface. In the last decades, large-eddy simulation (LES) has become a powerful tool to study turbulent transport and mixing in the ABL. Numerical simulations have been used to investigate the impact of different surface types (homogeneous, heterogeneous, flat, complex topography) on turbulent fluxes of momentum and scalars, such as temperature, water vapor and pollutants. Recently, LES studies of the interaction between ABL turbulence and wind turbines, and the interference effects among wind turbines have been carried out, in order to understand the impact of wind farms on local meteorology as well as to optimize the design (turbine siting) of wind energy projects. However, there are still some open issues that need to be addressed in order to make LES a more accurate tool for simulations of ABL flows. The main weakness of LES of the ABL is associated with our limited ability to accurately account for the dynamics that are not explicitly resolved in the simulations (because they occur at scales smaller than the grid size). The purpose of our studies is to improve subgrid-scale parameterizations and, thus, to make LES a more reliable tool to study land-atmosphere interactions. {html}<a name="WindEnergy"></a>{/html} !! Wind Energy Application [./mcf.jpg|right][./tipvortex.jpg|link=./windturbine.gif|right] With the fast growth of the wind-energy sector worldwide, the interaction between atmospheric boundary layer (ABL) flow and wind turbines, and the cumulative effects of turbine wakes, have become important issues in both the wind energy and the atmospheric science communities. Accurate prediction of ABL flow and of its interactions with wind turbines is critical for optimizing the siting of wind turbines and the layout of wind farms. In particular, flow prediction can potentially provide the kind of high-resolution spatial and temporal information needed to maximize wind energy production and minimize fatigue loads in wind farms. Numerical simulations, specifically large-eddy simulations (LESs), can also provide valuable quantitative insight into the potential impacts of wind farms on local meteorology. These are associated with the significant role of wind turbines in slowing down the wind and enhancing vertical mixing of momentum, heat, moisture, and other scalars. However, the accuracy of LESs of ABL flow with wind turbines hinges on our ability to parameterize subgrid-scale turbulent fluxes as well as turbine-induced forces. This study focuses on recent research efforts to develop and validate an LES framework for wind energy applications. Futher, we use this framework to simulate ABL flow through idealized wind farms and operational wind farms for better understanding wind turbine wakes.
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