[P-EM12] Study of coupling processes in solar-terrestrial system

[PEM12-04] Estimation of Turbulence Kinetic Energy dissipation rate from MST radar and Wind profiler data using in-situ UAV measurements and a Weak Stratification Model

*Hubert LUCE¹, Hiroyuki Hashiguchi¹, Laskhmi Kantha², Abhiram Doddi³, Dale Lawrence², Masanori Yabuki¹ (1.Research Institute for Sustainable Humanosphere, 2.Department of Aerospace Engineering Sciences, University of Colorado Boulder, 3.Global Atmospheric Technologies and Sciences, Boulder)

Keywords:Doppler radar, wind profiler, atmospheric turbulence, energy dissipation rate, shear flow instabilities, convective boundary layers

The increasingly fine spatial-resolution of Numerical Weather and Climate Prediction Models require a better parameterization of the intensity of mixing in the atmospheric column, represented by Turbulence Kinetic Energy (TKE) dissipation rate ε. Consequently, better quantification of ε from observations is important. The potential ability of VHF mesosphere-stratosphere-troposphere (MST) radars and UHF wind profilers to measure ε from Doppler spectrum width (SW) is a major asset of these instruments, because of the possibility of continuous monitoring. Several models have been proposed over past decades to relate ε to σ (equal to 1/2 SW, corrected for non-turbulent effects). We tested their performance from comparisons with in-situ estimates of ε, obtained from high resolution Pitot tube sensors onboard Unmanned Aerial Vehicles (UAVs) at Shigaraki MU Observatory (Shigaraki UAV Radar Experiment, ShUREX 2016-2017, Kantha et al., 2017). The comparisons with the VHF Middle and Upper atmosphere (MU) radar and a UHF (1.357 GHz) LQ7 wind profiler revealed that the most commonly used radar model fails to reproduce the UAV-derived ε estimates. This radar model predicts σ²N dependence (ε_N~0.5σ²N, N is the buoyancy frequency) and is therefore not valid for a neutrally stratified turbulent layer. Instead, we found a σ³ dependence (ε_R=σ³/L) was observed with L~50-70 m (Luce et al., 2018). From derivations by Basu and Holtslag (2021) based on the TKE budget, an alternative model whose asymptotic form for weak stratification (Ri→0) is ε_S=0.64σ²S (S=|dV/dz| is the shear) was tested. While this model is strictly valid for neutral stratification (N=0), it may also be valid for weak stratification when the buoyancy effects on turbulence are small, i.e., for low Richardson numbers, up to ~ 0.2 at least, according to Direct Numerical Simulations by Basu et al., (2021). ε_N model is likely valid for only strong stratification (Ri→1). By estimating S from radar data for a deep turbulent layer, generated by KH instability and sampled several times by the UAV, we found good agreement of in-situ ε data with both ε_R and ε_S models (but not with ε_N) . This agreement suggests that σ/L~0.64 S, or equivalently, L is equal to L_H/0.64 where L_H=σ/S is the Hunt scale defined for neutral turbulence. From statistical analysis made on multiple cases of KH layers identified from 11 years of LQ7 wind profiler data, L was found to be slightly variable and dependent on the depth D of the KH layers (L~0.1 D). This slight variability in L could not be detected from the MU and LQ7 radars, due to lack of precision and sensitivity of the radars, especially for low ε values. This explains the observed σ³ dependence by Luce et al. (2018). Interestingly, an equivalence between mean values of ε_R and ε_S was also found for convective boundary layers (CBL), where non-zero mean shears were observed, with L~0.1 D (D is the depth of the CBL). An attempt at interpretation will be given.

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S. Basu, P. He, A. W. DeMarco, Parametrizing the energy dissipation rate in stably stratifiedflows, Boundary-Layer Meteorol 178, 167-184, 2021.
L. Kantha, D. Lawrence, H. Luce, H. Hashiguchi, T. Tsuda, R. Wilson, T. Mixa, and M. Yabuki, Shigaraki UAV-Radar Experiment (ShUREX 2015): An overview of the campaign with some preliminary results. Prog. Earth Planet Sci., 4, 19, 2017.
H. Luce, L. Kantha, H. Hashiguchi, D. Lawrence, and A. Doddi, Turbulence Kinetic Energy Dissipation Rates Estimated from Concurrent UAV and MU Radar Measurements, Earth Planets Sci., 70, 207, 2018.