Turbulent structure and scaling of the inertial subrange in a stratocumulus-topped boundary layer observed by a Doppler lidar

Abstract

Abstract. The turbulent structure of a stratocumulus-topped marine boundary layer over a 2-day period is observed with a Doppler lidar at Mace Head in Ireland. Using profiles of vertical velocity statistics, the bulk of the mixing is identified as cloud driven. This is supported by the pertinent feature of negative vertical velocity skewness in the sub-cloud layer which extends, on occasion, almost to the surface. Both coupled and decoupled turbulence characteristics are observed. The length and timescales related to the cloud-driven mixing are investigated and shown to provide additional information about the structure and the source of the mixing inside the boundary layer. They are also shown to place constraints on the length of the sampling periods used to derive products, such as the turbulent dissipation rate, from lidar measurements. For this, the maximum wavelengths that belong to the inertial subrange are studied through spectral analysis of the vertical velocity. The maximum wavelength of the inertial subrange in the cloud-driven layer scales relatively well with the corresponding layer depth during pronounced decoupled structure identified from the vertical velocity skewness. However, on many occasions, combining the analysis of the inertial subrange and vertical velocity statistics suggests higher decoupling height than expected from the skewness profiles. Our results show that investigation of the length scales related to the inertial subrange significantly complements the analysis of the vertical velocity statistics and enables a more confident interpretation of complex boundary layer structures using measurements from a Doppler lidar.

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

“…We use µ = 1.5, which provides a good match with our experimental spectra, as also found in previous studies (Lothon et al, 2009;Tonttila et al, 2015). The parameter a can be expressed as a function of µ as…”

“…Following the approach in Tonttila et al (2015), we estimate the timescale corresponding to this transition wavelength by To compare the results from this approach with what we obtain from the comparison with dissipation rates from the sonic anemometer data, we apply this technique to the data from the Halo Stream Line for the whole period of XPIA and calculate the average timescales for different stability conditions at 100 m a.g.l. We obtain an average timescale of 32 s in stable conditions and 73 s in unstable conditions.…”

Offshore Wind Turbines Will Encounter Very Low Atmospheric Turbulence

“…This approach derives by integrating the turbulence spec- trum 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 (Tonttila et al, 2015;Bodini et al, 2018). 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).…”

Response to Anonymous Referee #1

“…where k is the wave number, σ z is the standard deviation of the vertical component of the wind speed used to compute the spectrum, l z is the integral scale of the vertical velocity along the horizontal flow trajectory, and the parameter µ controls the curvature of the spectrum. We use µ = 1.5, which provides a good match with our experimental spectra, as also found in previous studies (Lothon et al, 2009;Tonttila et al, 2015). The parameter a can be expressed as a function of µ as a(µ) = π µ 5 6µ 1 2µ 1 3µ…”

“…Following the approach in Tonttila et al (2015), we estimate the timescale corresponding to this transition wavelength by Figure 10. Time series from 6 April 00:00 UTC to 10 April 2015 00:00 UTC comparing from sonic anemometers and the Halo Stream Line lidars at 100 m a.g.l., where the timescales for the lidars have been determined with both the proposed approaches (comparison with from sonic anemometers and fit with spectral models).…”