The reliable prediction of turbulent non-equilibrium flows is of high academic and industrial interest in several engineering fields. Most turbulent flows are often predicted using single-time-scale Reynolds-Averaged-Navier-Stokes (RANS) turbulence models which assume the flows can be modelled through a single time or length scale which is an admittedly incorrect assumption. Therefore they are not expected to capture the lag in the response of the turbulence in non-equilibrium flows. In attempts to improve prediction of these flows, by taking into consideration some features of the turbulent kinetic energy spectrum, the multiple-time-scale models arose. A number of two-scale models have been proposed, but so far their use has been rather limited.This work thus focusses on the development of two-time-scale approaches. Two two-time-scale linear-eddy-viscosity models, referred to as NT1 and NT2 models, have been developed and the initial stages of the development of two-time-scale non-linear-eddy-viscosity models are also reported. The models' coefficients have been determined through asymptotic analysis of decaying grid turbulence, homogeneous shear flows and the flow in a boundary layer in local equilibrium. Three other important features of these models are that there is consistent partition of the large and the small scales for all above limiting cases, model sensitivity to the partition and production rate ratios and sensitivity of the eddy viscosity sensitive to the mean strain rates.The models developed have been tested through computations of a wide range of flows such as homogeneous shear and normally strained flows, fully developed channel flows, zero-pressure-gradient, adverse-pressure-gradient, favourable-pressure-gradient and oscillatory boundary layer flows, fully developed oscillatory and ramp up pipe flows and steady and pulsated backward-facing-step flows.The proposed NT1 and NT2 two-scale models have been shown to perform well in all test cases, being, among the benchmarked models tested, the models which best performed in the wide range of dimensionless shear values of homogeneous shear flows, the only linear-eddy-viscosity models which predicted well the turbulent kinetic energy in the normally strained cases and the only models which showed satisfactory sensitivity in predicting correctly the reattachment point in the unsteady backward facing step cases with different forcing frequencies. Although the development of the two-time-scale non-linear-eddy-viscosity models is still in progress, the interim versions proposed here have resulted in predictions of the Reynolds normal stresses similar to those of much more complex models in all test cases studied and in predictions of the turbulent kinetic energy in normally strained flows which are better than those of the other models tested in this study.

In this thesis, three improved analysis techniques for scatterometer wind estimation are presented. These techniques build upon previous methods that help validate scatterometer data. This thesis examines the theory connecting the 1D and 2D kinetic energy spectra and uses QuikSCAT data to measure the 2D kinetic energy spectrum of ocean winds. The measured 2D kinetic energy spectrum is compared to the traditional 1D kinetic energy spectrum. The relationship between the 2D kinetic energy spectra and the 1D kinetic energy spectra confirms findings from previous studies that ocean winds modeled in 2D are isotropic and nondivergent. The 1D and 2D kinetic energy spectra also confirm the known conclusion that the zonal and meridional components of ocean winds are uncorrelated. Through simulation, the wind response function (WRF) is calculated for three different QuikSCAT processing algorithms. The WRF quantifies the contribution that the wind at each point of the surface makes to a given wind estimate. The spatial resolution of the different processing algorithms is estimated by their WRFs. The WRFs imply that the spatial resolution of ultrahigh resolution (UHR) processing is finer than the spatial resolution of conventional drop-in-the-bucket (DIB) processing; the spatial resolution of UHR processing is ~5-10 km while the spatial resolution of DIB slice processing is ~12-15 km and the spatial resolution of coarse resolution DIB egg processing is ~30 km. Simulation is used to analyze the effectiveness of various wind retrieval and ambiguity selection algorithms. To assist in the simulation, synthetic wind fields are created through extrapolating the 2D Fourier transform of a numerical weather prediction wind field. These synthetic wind fields are sufficiently realistic to evaluate ambiguity selection algorithms. The simulation employs the synthetic wind fields to compare wind estimation with and without direction interval retrieval (DIR) applied. Both UHR and DIB wind estimation processes are performed in the simulation and UHR winds are shown to resolve finer resolution wind features than DIB winds at the cost of being slightly noisier. DIR added to standard QuikSCAT UHR wind estimation drops the wind direction root-mean-squared error by ~10° to ~24.74° in the swath sweet spot.