Anisotropic Non-Kolmogorov Turbulence Spectrum with Anisotropic Tilt Angle

With the in-depth study of atmospheric turbulence, scholars have identified that the anisotropy of turbulence cells should not be forgotten. The anisotropic non-Kolmogorov turbulence model can better characterize the actual situation of atmospheric turbulence. However, the results of recent experiments by Wang et al. and Beason et al. demonstrate that the turbulence cell has an anisotropic tilt angle, i.e., the long axis of turbulence cell may not be horizontal to the ground but has a certain angle with the ground. In this paper, we derive the anisotropic non-Kolmogorov turbulence spectra for the horizontal and satellite links with anisotropic tilt angle. Then by use of these spectra, the analytical expressions of scintillation index in the horizontal and satellite links are derived for the weak fluctuation condition. The calculation results display that the scintillation index for the horizontal and satellite links vary with the changes of anisotropic tilt angle and azimuth angle. Therefore, the anisotropic tilt angle is indispensable in the horizontal and satellite links.

Modelling the Spectral Shape of Continuous-Wave Lidar Measurements in a Turbulent Wind Tunnel

This paper describes the development of a model for the turbulence spectrum measured by a short-range, continuous-wave lidar. The lidar performance was assessed by measurements conducted with two WindScanners in an open jet wind tunnel equipped with an active grid, for a range of different turbulent wind conditions. A one-dimensional hot wire anemometer was used as a reference for characterising the lidar turbulence measurement. In addition to addressing the statistics, the correlation between the time series and the mean error on the wind speed, the lidar measurement turbulence spectrum is compared with a theoretical spectrum using Taylor's frozen turbulence hypothesis. A theoretical model for the probe length averaging effect is applied in the frequency domain, using a Lorentzian filter in combination with generated white noise, and evaluated by qualitatively matching the lidar measurement spectrum. High goodness of fit coefficients and low mean absolute errors between hot wire and WindScanner were observed for the measured time series. The correlation showed an inverse relationship with the prevalent turbulence intensity in the flow for cases with a comparable power spectrum shape. Larger flow structures can be captured more accurately by the lidar, whereas small-scale turbulent flow structures are partly filtered out as a result of the lidars' probe volume averaging. It is demonstrated that an accurate way to define the frequency at which the lidar power spectrum starts to deviate from the hot wire reference spectrum is the point at which the coherence drops below 0.5. This coherence-based cut-off frequency increases linearly with the mean wind speed and is generally an order of magnitude lower than the probe length cut-off frequency, estimated according to a simple model based on Taylor's frozen turbulence hypothesis. A convincing match between the modelled and the actual WindScanner power spectrum was found for various different cases, which confirmed that the deviation of the lidar measurement power spectrum in the higher frequency range can be analytically explained and modelled as a combination of a Lorentzian probe length averaging effect and white noise in the lidar measurement.

The impact of turbulence parameterization in high-resolution inverse modeling of synthetic greenhouse gases with the Lagrangian particle dispersion model FLEXPART-COSMO

<p>Synthetic greenhouse gases contribute currently about 10% to anthropogenic radiative forcing, and their future impact depends on the replacement of compounds with long lifetimes by compounds with short lifetimes and negligible global warming potential (GWP). Furthermore, chlorine and bromine-containing synthetic gases are the drivers of stratospheric ozone destruction. Therefore, observing the atmospheric abundance of synthetic gases and quantifying their emission sources is critical for predicting their related future impacts and assuring successful regulation.</p><p>Regional-scale atmospheric inverse modeling can provide observation-based estimates of greenhouse gas emissions at a country and continental scale and, consequently, support the process of forecasting and regulation. Inverse modeling is based on three main components: Source sensitivities derived from atmospheric transport models, observations, and an inversion framework. Within the Swiss National Science Foundation project IHALOME (Innovation in Halocarbon Measurements and Emission Validation) we increase the spatial resolution of the Lagrangian particle dispersion model FLEXPART-COSMO from 7 km to 1 km in order to enhance localization of Swiss halocarbon emissions based on newly available observations from the Swiss Plateau at the Beromünster tall tower. The transport model is driven by the meteorological fields of the regional numerical weather prediction model (NWP) COSMO run at MeteoSwiss.</p><p>The higher-resolution model exhibits increased three-dimensional dispersion, and as a result, is unable to reproduce the variability seen in the observations and in the 7 km model at the tall tower site Beromünster for a well-studied validation tracer (methane). Because the TKE (Turbulent Kinetic Energy) values do not differ significantly between the two model versions, head-to-head comparisons of parameterized turbulence cannot fully explain the concentration discrepancies. Comparisons of wind fluctuations resolved on the grid-scale suggest that the dispersion differences may originate from a duplication of turbulent transport, on the one hand, covered by the high-resolution grid of the Eulerian model and, on the other hand diagnosed by FLEXPART's turbulence scheme. In an attempt to tune FLEXPART-COSMO’s turbulence scheme at high resolution, we scale FLEXPART's parameterized turbulence so it matches the TKE computed in COSMO. Test simulations with the scaled FLEXPART turbulence show remarkable improvements in the high-resolution model's ability to predict the observed tracer variability and concentration at the Beromünster tall tower. We further introduce new equations in FLEXPART's turbulence scheme for each component of the variations of the winds in order to mimic the TKE produced by the turbulence scheme of COSMO and hence resolve the part of the turbulence spectrum which is unresolved by the high-resolution model. Compared to the coarse resolution simulations, simulations with scaled turbulence result in a more realistic and pronounced diurnal cycle of the tracer and overall improved correlation with observations.</p><p>Concluding, the increasing resolution of NWP models may lead to the representation of the part of the turbulence spectrum by the models themselves. In these models, big eddies (most likely related to convection) are partly resolved and do not require additional parameterization. The turbulence schemes of the past, developed for coarse resolution models, should be revisited to include this effect.</p>

Inverse Energy Cascade of Fast Magnetosonic Turbulence in the Heliosheath

<p>The solar wind in the heliosheath beyond the termination shock (TS) is a non-equilibrium collisionless plasma consisting of thermal solar wind ions, suprathermal pickup ions (PUI) and electrons. In such multi-ion plasma, two fast magnetosonic wave modes exist: the low-frequency fast mode that propagates in the thermal ion component and the high-frequency fast mode that propagates in the suprathermal PUI component [<em>Zieger et al.</em>, 2015]. Both fast modes are dispersive on fluid and ion scales, which results in nonlinear dispersive shock waves. In this talk, we briefly review the theory of dispersive shock waves in multi-ion collisionless plasma. We present high-resolution three-fluid simulations of the TS and the heliosheath up to 2.2 AU downstream of the TS. We show that downstream propagating nonlinear magnetosonic waves grow until they steepen into shocklets (thin current sheets), overturn, and start to propagate backward in the frame of the downstream propagating wave, as predicted by theory <em>[McKenzie et al</em>., 1993; <em>Dubinin et al.</em>, 2006]. The counter-propagating nonlinear waves result in fast magnetosonic turbulence far downstream of the shock. Since the high-frequency fast mode is positive dispersive on fluid scale, energy is transferred from small scales to large scales (inverse energy cascade). Thermal solar wind ions are preferentially heated by the turbulence. Forward and reverse shocklets in the heliosheath can efficiently accelerate both ions and electrons to high energies through the shock drift acceleration mechanism. We validate our three-fluid simulations with in-situ high-resolution Voyager 2 magnetic field and plasma observations at the TS and in the heliosheath. Our simulations reproduce the magnetic turbulence spectrum with a spectral slope of -5/3 observed by Voyager 2 in frequency domain [<em>Fraternale et al</em>., 2019]. However, since Taylor’s hypothesis is not true for fast magnetosonic perturbations in the heliosheath, the inertial range of the turbulence spectrum is not a Kolmogorov spectrum in wave number domain. </p>