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

Abstract

Area-averaged estimates of C n 2 from high-resolution numerical weather prediction (NWP) model output are produced from local estimates of the spatial structure functions of refractive index with corrections for the inherent smoothing and filtering effects of the underlying NWP model. The key assumptions are the existence of a universal statistical description of small-scale turbulence and a locally universal spatial filter for the NWP model variables. Under these assumptions, spatial structure functions of the NWP model variables can be related to the structure functions of the atmospheric variables and extended to the smaller underresolved scales. The shape of the universal spatial filter is determined by comparisons of model structure functions with the climatological spatial structure function determined from an archive of aircraft data collected in the upper troposphere and lower stratosphere. This method of computing C n 2 has an important advantage over more traditional methods that are based on vertical differences because the structure function-based estimates avoid reference to the turbulence outer length scale. To evaluate the technique, NWP model-derived structure-function estimates of C n 2 are compared with nighttime profiles of C n 2 derived from temperature structure-function sensors attached to a rawinsonde (thermosonde) near Holloman Air Force Base in the United States.

Satellite-based links for quantum key distribution: beam effects and weather dependence

“…to-ground communication, so the atmospheric effects kick-in only for z>(L−h) (final section of the propagation), while for up-links it is limited to z<h. We remark that some models for the altitude-dependence of the optical quantities, like C n 2 , are available in the literature [33][34][35][36][37], but they are correct only in the geographical site and in the atmospheric conditions in which they had been experimentally extracted (more details in appendix E). Additional extinction losses due to back-scattering and absorption in the atmosphere are modeled by a parameter χ ext , as described in appendix A.…”

“…We chose h=20 km, as a layer around the Earth with this thickness contains on average 95% of the total mass of the atmosphere. As already stated in the main text, some models for the altitude-dependence of the refractive index structure constant C n 2 are available in the literature [34][35][36][37]. The widely used parametric fit due to Hufnagel =´-and v=21 m s −1 , although v=57 m s −1 is sometimes used for stronger wind conditions.…”

The Use of Weather Forecasts to Characterise Near-Surface Optical Turbulence

“…A number of studies have been proposed to diagnose the optical turbulence rate in the troposphere, e.g. Bougeault et al (1995), Masciadri et al (1999), Cherubini et al (2008) and Frehlich et al (2010). The idea of using a NWP model to reveal the meteorological variations of wave propagation diagnostics has also been followed in other contexts.…”

Variational Multiscale based dissipation models for the estimation of atmospheric seeing

“…In [22] a weather forecasting model was used together with the statistical parametrization of the refraction index structure constant C 2 n presented in [35] in order to forecast the seeing conditions in the Roque de Los Muchachos, Canary Islands, Spain. A numerical weather prediction tool was used in [1] to compute various turbulence parameters which allow to characterise C 2 n in the islands of Maui and the Big Island, Hawaii, and a similar methodology was presented in [21].…”