Use of thermal signal for the investigation of near-surface turbulence

Organised motion of air in the roughness sublayer of the atmosphere was investigated using novel temperature sensing and data science methods. Despite accuracy drawbacks, current fibre-optic distributed temperature sensing (DTS) and thermal imaging (TIR) instruments offer frequent, moderately precise and highly localised observations of thermal signal in a domain geometry suitable for micrometeorological applications near the surface. The goal of this study was to combine DTS and TIR for the investigation of temperature and wind field statistics. Horizontal and vertical cross-sections allowed a tomographic investigation of the spanwise and streamwise evolution of organised motion, opening avenues for analysis without assumptions on scale relationships. Events in the temperature signal on the order of seconds to minutes could be identified, localised, and classified using signal decomposition and machine learning techniques. However, small-scale turbulence patterns at the surface appeared difficult to resolve due to the heterogeneity of the thermal properties of the vegetation canopy, which are not immediately evident visually. The results highlight a need for physics-aware data science techniques that treat scale and shape of temperature structures in combination, rather than as separate features.

A Turbulent Heliosheath Driven by the Rayleigh–Taylor Instability

The heliosphere is the bubble formed by the solar wind as it interacts with the interstellar medium (ISM). The collimation of the heliosheath (HS) flows by the solar magnetic field in the heliotail into distinct north and south columns (jets) is seen in recent global simulations of the heliosphere. However, there is disagreement between the models about how far downtail the two-lobe feature persists and whether the ambient ISM penetrates into the region between the two lobes. Magnetohydrodynamic simulations show that these heliospheric jets become unstable as they move down the heliotail and drive large-scale turbulence. However, the mechanism that produces this turbulence had not been identified. Here we show that the driver of the turbulence is the Rayleigh–Taylor (RT) instability produced by the interaction of neutral H atoms streaming from the ISM with the ionized matter in the HS. The drag between the neutral and ionized matter acts as an effective gravity, which causes an RT instability to develop along the axis of the HS magnetic field. A density gradient exists perpendicular to this axis due to the confinement of the solar wind by the solar magnetic field. The characteristic timescale of the instability depends on the neutral H density in the ISM and for typical values the growth rate is ∼3 years. The instability destroys the coherence of the heliospheric jets and magnetic reconnection ensues, allowing ISM material to penetrate the heliospheric tail. Signatures of this instability should be observable in Energetic Neutral Atom maps from future missions such as the Interstellar Mapping and Acceleration Probe (IMAP). The turbulence driven by the instability is macroscopic and potentially has important implications for particle acceleration.

Statistical Measurements of Dispersion Measure Fluctuations of FRBs

Extragalactic fast radio bursts (FRBs) have large dispersion measures (DMs) and are unique probes of intergalactic electron density fluctuations. By using the recently released First CHIME/FRB Catalog, we reexamined the structure function (SF) of DM fluctuations. It shows a large DM fluctuation similar to that previously reported in Xu & Zhang, but no clear correlation hinting toward large-scale turbulence is reproduced with this larger sample. To suppress the distortion effect from FRB distances and their host DMs, we focus on a subset of CHIME catalog with DM < 500 pc cm−3. A trend of nonconstant SF and nonzero correlation function (CF) at angular separations θ less than 10° is seen, but with large statistical uncertainties. The difference found between SF and that derived from CF at θ ≲ 10° can be ascribed to the large statistical uncertainties or the density inhomogeneities on scales on the order of 100 Mpc. The possible correlation of electron density fluctuations and inhomogeneities of density distribution should be tested when several thousands of FRBs are available.

Turbulence of Landward and Seaward Wind during Sea-Breeze Days within the Lower Atmospheric Boundary Layer

Reynolds stress anisotropy is estimated from the stress spheroids, based on 20 Hz ultrasonic anemometer measurements, performed in the coastal area of northern France, over a 1.5-year long period. Size and shape variation (i.e., prolate, oblate, disk, rod, etc.) of stress spheroids are used for the characterization of energy redistribution by turbulent eddies. The sea-breeze (SB) events were identified using a change in wind direction from seaward (SWD) to landward (LWD) during the day time. We found that the LWD wind creates more turbulent anisotropic states than SWD wind. The prolate-shaped stress spheroids correspond to small-scale turbulence observed during LWD wind, while oblate spheroids are found during SWD winds. Moreover, it was found that during LWD winds, large turbulence kinetic energy (TKE) in the flow field produces large stress spheroids. On the contrary, during SWD winds, a smaller level of TKE is responsible for small-size stress spheroid formation. The average volume of the corresponding Reynolds stress spheroids during the LWD is 13% larger than that of during SWD wind.

Assessment of local and non–local turbulent flow components on turbulence–flame interaction

In the framework of turbulence-flame interaction, the flame is characterized by the gradient of a reactive scalar such as the progress variable, whereas the turbulence is represented by the vorticity and the strain rate. Quantitative assessment of this interaction is performed trough the study of the coupled transport between these quantities that are subject to the effects of heat release and chemical reactions. The present analysis aims at improving the understanding of the small scale turbulence – flame interaction properties, through the introduction of an additive decomposition of the strain rate and vorticity fields into their local and non-local components. The respective role of the local and non-local effects is studied for a broad range of Karlovitz numbers, by virtue of direct numerical simulations (DNS) of turbulent, premixed, lean, and statistically planar flames of methane-air. In the conditions of the present study, the alignment between flame front normals and the strain rate is found to be dominated by the local contribution from the strain rate tensor.

Emergence of optimal disturbances in a stratified turbulent shear flow under the stochastic forcing

Large-scale inclined organized structures in stably stratified turbulent shear flows were revealed in the numerical simulation and indirectly confirmed by the field measurements in the stable atmospheric boundary layer. Spatial scales and forms of these structures coincide with those of the optimal disturbances of a simplified linear model. In this paper, we clarify the relation between the organized structures and the optimal disturbances, analyzing a time series of turbulent fields obtained by the RANS model with eddy viscosity/diffusivity and stochastic forcing generating the small-scale turbulence.

Impact of Pointing Errors on the Performances of Double Rician FSO Channels

In this paper we will propose new analytically traceable probability density function (PDF) model for free space optics (FSO) turbulence, obtained as a generalization of double Ricean turbulence model, that encompasses both large-scale and small-scale turbulence eddy effects along by taking into account performance decreasing influence of misalignment introduced through boresight pointing error model. Consequently, after delivering the closed-form expressions for the newly introduced double FSO model, we obtain the analytical expressions for the bit error rate (BER) performance for the Double Rician distribution affected by misalignment. Numerical results will show the impact of system parameters on FSO link performance and we will provide full performance analysis. © 2021.