Spectral and Coherence Analyses of wind-LiDAR measurements collected in the Atmospheric Surface Layer for detecting the k^-1 spectral region

In the realm of wall-bounded turbulence, the k^-1  law of the streamwise-velocity spectrum ( is the wavenumber) has been ascribed to the statistical presence of wall-attached eddies. However, previous investigations have shown puzzling results for the identification of the spectral boundaries of the k^-1 region, and their flow-based definition is still elusive. Investigations of coherent turbulent structures present in turbulent boundary-layer flows require a large scale-separation, and, thus, a high-Reynolds number flow, which makes the atmospheric surface layer (ASL) a unique environment to investigate wind-generated turbulence. In this work, wind-LiDAR measurements collected within the ASL are leveraged to estimate the spectral boundaries of the k^-1 region with two approaches: the first one is based on piece-wise modeling of the streamwise-velocity spectrum, while the second one is based on the coherence analysis of the streamwise velocity. The findings of this work include a generalized modeling of the linear coherence of the streamwise velocity, the estimate of the maximum height where the k^-1 region is detectable, and the vertical profiles of attached- and detached-eddy contributions to the streamwise turbulence intensity.