Nourani, MehrdadIungo, Giacomo Valerio2024-03-142024-03-142022-12December 2December 2https://hdl.handle.net/10735.1/10054Light Detection And Ranging (LiDAR) technology has gained growing attention for research in the realm of atmospheric turbulence due to its capability to probe the atmospheric boundary layer (ABL) with high spatial and temporal resolution within a volume with height and horizontal extent comparable to the ABL thickness. In this work, several high Reynolds- number turbulent flows, such as ABL for onshore and marine environment, wakes generated by utility-scale wind turbines, have been probed with the LiDAR anemometry with the aim of investigating the variability of the mean kinetic energy, the spatial and spectral heterogeneity of the streamwise momentum resulting from the dynamics of various turbulent eddies. In the first part of this dissertation, the LiDAR spatial averaging process, which is the source for a reduced turbulence intensity measured though a wind LiDAR, has been systematically corrected through a novel data-driven procedure based on the quantification of the energy damping for the streamwise velocity spectra at high-frequencies owing to the inertial sub-range. This correction method has enabled reverting the low-pass filtering operated by the LiDAR measuring system on the turbulent velocity fluctuations, and obtain a corrected estimate of the second-order statistical moment of the streamwise velocity. Subsequently, LiDAR measurements collected for the ABL evolving over a very flat and homogeneous terrain are interrogated to investigate the distribution of the streamwise turbulence intensity associated with wall-attached eddies and larger coherent structures as a function of height. This work has culminated with the proposition of an analytical model for the prediction of the linear coherence spectrum, which is based on the Townsend’s attached eddy hypothesis. Finally, LiDAR experiments performed for marine ABL, ABL interacting with utility-scale wind turbines, and coupling LiDAR with snow particle image velocimetry to investigate atmospheric turbulence are presented.application/pdfEnglishEngineering, MechanicalThesis2024-03-14