Characterization of atmospheric optical turbulence for laser propagation

Abstract

The performance of imaging or transmission systems is limited by atmospheric inhomogeneities and fluctuations. Temperature and pressure variations associated with turbulent eddies cause random fluctuations of the refractive index structure constant (C 2 n ), which distort optical waves. The distortions may lead to significant blurring, scintillations, broadening and wander of the laser beam. High resolution nested numerical simulations are used to predict and characterize Optical Turbulence (OT) induced by jet streams and gravity waves under various local atmospheric conditions. Non-homogeneous, anisotropic, non-Kolmogorov patchy shear-stratified turbulence in the Upper Troposphere and Lower Stratosphere (UTLS) requires that a fine mesh be used to resolve stiff velocity and temperature gradient profiles. Computational approach is based on nesting and refined vertical gridding in nested mesoscale/microscale codes. This methodology is applied to the analysis of field data from observations. Local distributions of simulated optical turbulence in the UTLS are obtained using very high resolution explicit simulations and parametrization formula. They show strongly laminated structures with thin layers of high values of the refractive index. These optical layers are characterized by steep vertical gradients of potential temperature and are located at the edges of relatively well mixed regions produced by shear instabilities and wave breaking.Streamwise-altitude and spanwise-altitude cross-sections for C 2 n from high resolution simulations. Z is the altitude.

Estimates of Cn2 from Numerical Weather Prediction Model Output and Comparison with Thermosonde Data

“…The major difficulty in applying Eqs. (2.6) and (2.7) to compute C n 2 from soundings or NWP model output is the lack of a rigorous basis for the computation of the outer length scale L o Therefore, L o is typically prescribed by some empirical function that relates it to stability and vertical wind shear (Hufnagel 1978;van Zandt et al 1981;Dewan et al 1993;Masciadri et al 1999;Mahalov and Moustaoui 2010). For example, the Air Force Geophysics Laboratory (AFGL) model proposed by Dewan et al (1993) Dewan et al (1993) model will be compared with the structure-function approach outlined below.…”

“…However, this model is based on high-resolution (;300 m vertically) rawinsonde measurements and shear/turbulence observations of rocket trails and may perform differently when applied to lower-resolution numerical model output. Note that modifications to the basic formulation have been proposed to improve the estimates of L o for different stability regimes and model parameterizations (Masciadri et al 1999;Mahalov and Moustaoui 2010), but in practice they require very high vertical resolution for actual implementation.…”

A numerical study of mountain waves in the upper troposphere and lower stratosphere

“…Dornbrack, 1998;Bacmeister and Schoeberl, 1989;Prusa et al, 1996;Satomura and Sato, 1999), upper tropospheric jet streams (i.e. Mahalov and Moustaoui, 2010; gravity wave-critical level interactions (Lott and Teitelbaum, 1992;Teitelbaum et al, 1999;Moustaoui et al, 2004), shear instability induced by non-parallel flows ) and nonlinear wave-wave interactions (Danielsen et al, 1992;Moustaoui et al, 1999Moustaoui et al, , 2010.…”

Near-infrared open-path measurement of CO_2 concentration in the urban atmosphere

“…Although the DOAS equipment was operated continuously, the occurrence of morning haze sometimes interrupted the measurement because of the large extinction along the optical path. The acquisition duration of a single data point was 60-300 s, depending on the atmospheric conditions including the effect of atmospheric turbulence [20]. Below, the analysis is based on the spectrum averaged over 1 h. The values for atmospheric pressure and temperature were obtained from the JMA station data.…”