Wavelet analysis of downslope flows in Materhorn 2012 experiment

In the last years, increasing attention has been devoted to the study of complex terrain flows, with the specific goal in achieving a better understanding of air circulation which usually develops over mountainous regions. Progress in this field of research is fundamental for improvements of numerical weather prediction models for irregular topography areas, which are commonplace in human settlements across the world. Mountainous regions are often characterized by the diurnal mountain wind system, a thermally driven circulation involving winds following the shape of the underlying surface, such as, for example, downslope flows which originate during nighttime and travel down the mountain slopes. Nocturnal downslope flows are investigated in this work, using a subset of experimental data collected at Granite Mountain, in Utah, during MATERHORN campaign. The dataset consists of data measured by sonic anemometers as well as slow sensors mounted up to seven levels on 4 towers deployed along a main lower slope (angle about 2-3°) of Granite Mountain. The study is performed through the Wavelet Transform method, a mathematical tool which improves the classical Fourier Transform, as it provides the location in time and/or space in addition to frequencies of physical phenomena. The final purpose of the present thesis is to evaluate the ability of Wavelet Analysis of detecting relevant flow features in the flow dynamics and to characterize their behavior. Wavelet Transform resulted to be an appropriate method to perform this type of study. In particular, it was proved capable of detecting transitions between flow regimes, as well as the presence of flow oscillations at different frequencies. Moreover, it has been efficient in highlighting specific events such as collisions between wind fronts and abrupt variations in measured signals.