Estimation of turbulence dissipation rate and its variability from sonic anemometer and wind Doppler lidar during the XPIA field campaign

Abstract

Abstract. Despite turbulence being a fundamental transport process in the boundary layer, the capability of current numerical models to represent it is undermined by the limits of the adopted assumptions, notably that of local equilibrium. Here we leverage the potential of extensive observations in determining the variability in turbulence dissipation rate ( ). These observations can provide insights towards the understanding of the scales at which the major assumption of local equilibrium between generation and dissipation of turbulence is invalid. Typically, observations of require time-and labor-intensive measurements from sonic and/or hot-wire anemometers. We explore the capability of wind Doppler lidars to provide measurements of . We refine and extend an existing method to accommodate different atmospheric stability conditions. To validate our approach, we estimate from four wind Doppler lidars during the 3-month XPIA campaign at the Boulder Atmospheric Observatory (Colorado), and we assess the uncertainty of the proposed method by data intercomparison with sonic anemometer measurements of . Our analysis of this extensive dataset provides understanding of the climatology of turbulence dissipation over the course of the campaign. Further, the variability in with atmospheric stability, height, and wind speed is also assessed. Finally, we present how increases as nocturnal turbulence is generated during low-level jet events.

U.S. East Coast Lidar Measurements Show Offshore Wind Turbines Will Encounter Very Low Atmospheric Turbulence

“…In contrast, in winter minima occur in the morning at ∼200 m ASL. Average differences throughout the day in are smaller than 1 order of magnitude, whereas the diurnal cycle of onshore, in both flat (Bodini et al, 2018) and complex (Bodini et al, 2019) terrain, shows a larger amplitude, with differences of at least 1 order of magnitude between larger daytime values and smaller nighttime values. Moreover, average values of are smaller (in some cases by more than an order of magnitude) than onshore (Bodini et al, 2018(Bodini et al, , 2019.…”

“…Turbulence dissipation rate can be estimated from the variance of the line-of-sight velocity measured by profiling lidars following the approach proposed by O' Connor et al (2010) and refined in Bodini et al (2018), assuming locally homogeneous and isotropic turbulence. This approach derives by integrating the turbulence spectrum within the inertial subrange.…”

“…This approach derives by integrating the turbulence spectrum within the inertial subrange. To do so, the maximum length scale (and thus the sample size) to include in the calculation must be accurately chosen (Bodini et al, 2018;Tonttila et al, 2015). Here we use a local regression of the spectrum of the line-of-sight velocity to estimate the extension of the inertial subrange, as described and tested in Bodini et al (2019).…”

“…where 2 e is defined as in equation (2) in Pearson et al (2009; see the supporting information). More details of this method are available in Bodini et al (2018Bodini et al ( , 2019.…”

“…Despite the potential drawback of their inherent volume averaging (Frehlich & Cornman, 2002;Wang et al, 2016), the ease of deployment and extended measurement range of remote sensing instruments have fueled research to derive methods to Geophysical Research Letters 10.1029/2019GL082636 retrieve from lidars (Banakh et al, 1996;Frehlich, 1994;O'Connor et al, 2010;Wulfmeyer et al, 2016) and radars (McCaffrey et al, 2017;Shaw & LeMone, 2003). The extension and application of these techniques have led to a systematic assessment of the variability of in both flat (Bodini et al, 2018) and complex terrain (Bodini et al, 2019). However, to the authors' knowledge, no comprehensive analysis of the variability of turbulence dissipation rate in the offshore environment has been completed.…”