Profiling the Molecular Destruction Rates of Temperature and Humidity as well as the Turbulent Kinetic Energy Dissipation in the Convective Boundary Layer

Abstract. A simultaneous deployment of Doppler, temperature, and water-vapor lidars is able to provide profiles of molecular destruction rates and turbulent kinetic energy (TKE) dissipation in the convective boundary layer (CBL). Horizontal wind profiles and profiles of vertical wind, temperature, and moisture fluctuations are combined for deriving the dissipation and molecular destruction rates by determining the transversal temporal autocovariance functions (ACFs). These ACFs are fitted to their theoretical shapes and coefficients in the inertial subrange. Error bars are estimated by a propagation of noise errors. Sophisticated analyses of the ACFs are performed in order to choose the correct range of lags of the fits for fitting their theoretical shapes in the inertial subrange as well as for minimizing systematic errors due to temporal and spatial averaging and micro- and mesoscale circulations. We demonstrate that we achieve very consistent results of the derived profiles of turbulent variables regardless whether 1-s or 10-s time resolutions are used. We also show that the temporal and spatial length scales of the fluctuations of vertical wind, moisture, and potential temperature are similar with a spatial integral scale of ≈ 160 m at least in the mixed layer (ML). The profiles of the molecular destruction rates show a maximum in the interfacial layer (IL) and reach values of ε_m 7 ⋅ 10^-4 g² kg^-2 s^-1 for mixing ratio and ε_θ 1.6 ⋅ 10^-3 K² s^-1 or potential temperature. In contrast, the maximum of the TKE dissipation is reached in the ML and amounts epsilon 10^-2 m² s^-3. We also demonstrate that the vertical wind ACF coefficient and the TKE dissipation . For the molecular destruction rates we show that and . These equations can be used for parameterizations of ε, ε_m, and ε_θ. All noise errors bars are derived by error propagation and are small enough to compare the results with previous observations and large eddy simulations. The results agree well with previous observations but show more detailed structures in the IL. Consequently, the synergy resulting from this new combination of active remote sensors enables the profiling of turbulent variables such as integral scales, variances, TKE dissipation, and the molecular destruction rates as well as deriving relationships between them. The results can be used for the parameterization of turbulent variables, TKE budget analyses, and the verification of large eddy simulations.