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[1] Previous papers by Franke et al. (2011) and Fritts et al. (2011) described the computation of radar backscatter power and vertical velocities from numerical simulations of turbulence arising due to Kelvin-Helmholtz (KH) shear instability. Comparisons of backscatter power and inferred velocities with the distributions of turbulence and the true velocities revealed biases in the identification of active or intense turbulence and in the inferred Doppler spectrum and vertical velocities throughout the flow evolution. This paper extends these analyses to off-zenith viewing angles typical of multiple-beam MF, HF, and VHF radars. These reveal similar biases in the identification of turbulence occurrence, Doppler spectra, and inferred radial velocities, with additional sensitivity to the off-zenith angle relative to the mean shear across the turbulence layer. Radial velocities are typically underestimated during turbulence generation and breakdown of the KH billows, except where turbulence refractive index gradients are strong. Doppler spectra are biased toward regions retaining strong refractive index gradients, implying strong aspect sensitivity at later stages in the evolution. Persistent tilted structures at late stages of the evolution contribute to radial velocity measurement biases that also are functions of off-zenith angle and time.

[1] An outstanding question about the dynamics of the mesosphere is the temporal and spatial distribution of nonlinear events such as wave-breaking, wave saturation, and wave-critical layer interactions. A climatology of these events will help us understand how the mesoscale dynamical features, such as gravity waves, interact with the background mean wind and temperature structure. New lidar systems have the resolution to show us a height versus time ''picture'' of the dynamics so that identifying individual events within the observation window of the instrument is now possible. At the Starfire Optical Range (SOR) a sodium resonance lidar provides simulataneous sodium density, temperature, and three components of the winds. In this paper we present ''pictures'' of individual wave events apparent in the lidar data using the temperature (plotted as potential temperature and spectra) to show the time evolution of the wave structure.

Multiple‐receiver MF radar returns from the mesosphere are used to investigate the relationship between spaced antenna (SA), radar interferometry (RI), and imaging Doppler interferometry (IDI) wind estimation techniques. Our results show that frequency‐domain (RI and IDI) and time‐domain (SA) techniques yield almost identical results under high SNR conditions suitable for SA full correlation analysis (FCA).

[1] Franke et al. (2011) describe a numerical simulation of the instability and turbulent breakdown of Kelvin-Helmholtz (KH) billows at a high Reynolds number, numerical assessment of radar backscatter, and accuracies of inferred Doppler spectral moments for one test volume. Those results suggest a potential for significant measurement biases for radars that obtain backscatter from refractive index fluctuations. We present in this paper the morphology of computed radar moments throughout the KH instability lifecycle for two radar configurations in order to reveal the evolving character of radar backscatter and compare the radar velocity estimates with true velocities throughout the evolution, and to provide guidance, and cautions, for the interpretation of these dynamics in observational data. Results reveal strong variations in backscatter moments and character, and dependence on radar measurement parameters, that should be beneficial in the interpretation of such measurements in the atmosphere. Backscatter power predictions agree reasonably with observations of such events and their temporal evolutions. Our results also reveal a potential for significant measurement or sensitivity biases, some of which were predicted previously. Examples include a lack of significant backscatter power in well-mixed billow cores, suggesting possibly weak turbulence where in fact it may be strongest, maximum backscatter power in the billow exteriors, where refractive index fluctuations are large but turbulence is weak, underestimated vertical velocities within the KH billows at early times, and inferred significant vertical velocities where true vertical velocities are near zero at late stages of restratification, especially in the edge regions of the turbulence layer.

[1] A numerical simulation of secondary instability and turbulence accompanying Kelvin-Helmholtz shear instability and a numerical algorithm computing radar backscatter from these turbulence volumes are employed to examine the validity of routine assumptions employed in radar studies of atmospheric dynamics that rely on backscatter from refractive index fluctuations. The numerical simulation of KH instability describes turbulence dynamics and character from the onset of instability, through fully developed turbulence, to turbulence decay and restratification at late times. Radar backscatter computations employing the Born approximation and the turbulence fields at multiple times are performed for representative radar frequencies, beam widths, and pulse lengths. Vertical velocities obtained from the Doppler spectra are compared with the true velocities evaluated with the same weighting of the true velocity distributions. Results reveal departures of simulated radar velocity estimates that depend on how many scatterers are included in the scattering volume, how their contributions are weighted in space and time, and the morphology of the turbulence field. Biases include underestimates of vertical velocities where velocities and refractive index fluctuations are correlated, apparent velocities due to advection of tilted scatterers, and an inability to define Doppler velocities with precision where turbulence is strong, but backscatter is weak due to mixing and eradication of refractive index gradients. A companion paper employs these procedures to describe the backscatter power and Doppler velocities for two canonical radars throughout the life cycle of the KH instability. Both studies suggest systematic measurement biases that appear to account for a number of reported measurements.

The recent extension of the finite difference time domain (FDTD) method to frequency‐dependent media [Nickisch and Franke, 1992] allows FDTD to now be applied to ionospheric propagation. The FDTD method solves the Maxwell equations directly in the time domain by temporal integration. No approximations beyond that of finite differencing are necessary, although the direct enforcement of certain approximations is possible. By doing so the method can be used to explore the effect of many standard propagation approximations. We consider certain approximations typically applied to the problem of propagation in randomly structured ionization, such as the neglect of polarization coupling and the assumption of small‐angle scattering.