The vertical distributions of optical turbulence ( C n 2 profiles) are a major factor in defining the capabilities of ground-based telescopes and interferometers. As site-testing campaigns are extremely expensive and instruments only provide the local atmospheric parameter, atmospheric modeling might represent an advance prediction result in astronomical sites. The key meteorological parameters and the integrated astroclimatic parameters (Fried parameter r₀, seeing ɛ, isoplanatic angle θ_AO and wavefront coherence time τ_AO) related to the C n 2 profiles above the Tibetan Plateau are investigated for astronomical applications by using the Weather Research and Forecasting (WRF) model. Radiosonde measurements from a field campaign at Lhasa station above the Tibetan Plateau are used to quantify the ability of this model. The results show that the C n 2 profile decreases rapidly in the surface layer, increasing with height from the boundary layer to low stratosphere, and decreases gradually in the high free atmosphere. From the whole campaign measurements above the Tibetan Plateau, the mean r₀ is 8.64 cm, the mean ɛ is 1.55′′, the mean θ_AO is 0.42′′ and the mean τ_AO is 1.89 ms, and the comparison with the other world’s leading observatory sites have been presented. In addition, such as the bias and the root-mean-squared error are used to quantify the performance of the WRF model. In spite of the model performance in reconstructing the meteorological parameters is reasonable in general, the uncertainty in quantifying the C n 2 profiles and the integrated parameters are not negligible in some cases. The main results of this study tell us that the WRF model could provide a useful resource to design, monitor the performance of, and even optimize the operation of sophisticated Adaptive Optics (AO) systems.

Optical turbulence strongly affects different types of optoelectronic and adaptive optics systems. Systematic direct measurements of optical turbulence profiles [$C_n^2\left(h\right)$] are lacking for many climates and seasons, particularly in marine environments, because it is impractical and expensive to deploy instrumentation. Here, a backpropagation neural network optimized using a genetic algorithm (GA-BP) is developed to estimate atmospheric turbulence profiles in marine environments which is validated against corresponding [$C_n^2\left(h\right)$] profile datasets from a field campaign of balloon-borne microthermal measurements at the Haikou marine environment site. Overall, the trend and magnitude of the GA-BP model and measurements agree. The [$C_n^2\left(h\right)$] profiles from the GA-BP model are generally superior to those obtained by BP and the physically-based (HMNSP99) models. Several statistical operators were used to quantify the GA-BP model performance on reconstructing the optical turbulence profiles in marine environments. The characterization of vertical distributions of optical turbulence profiles and the main integral parameters derived from [$C_n^2\left(h\right)$] profiles are presented. The median Fried parameter, isoplanatic angle, and coherence time are 9.94 cm, ${0.69}^{″}$, and 2.85 ms, respectively, providing independent optical turbulence parameters for adaptive optics systems. The proposed approach exhibits potential for implementation in ground-based optical applications in marine environments.

Since systematic direct measurements of refractive index structure constant ( $C_n^2$) for many climates and seasons are not available, an indirect approach is developed in which $C_n^2$ is estimated from the mesoscale atmospheric model outputs. In previous work, we have presented an approach that a state-of-the-art mesoscale atmospheric model called Weather Research and Forecasting (WRF) model coupled with Monin-Obukhov Similarity (MOS) theory which can be used to estimate surface layer $C_n^2$ over the ocean. Here this paper is focused on surface layer $C_n^2$ over snow and sea ice, which is the extending of estimating surface layer $C_n^2$ utilizing WRF model for ground-based optical application requirements. This powerful approach is validated against the corresponding 9-day $C_n^2$ data from a field campaign of the 30th Chinese National Antarctic Research Expedition (CHINARE). We employ several statistical operators to assess how this approach performs. Besides, we present an independent analysis of this approach performance using the contingency tables. Such a method permits us to provide supplementary key information with respect to statistical operators. These methods make our analysis more robust and permit us to confirm the excellent performances of this approach. The reasonably good agreement in trend and magnitude is found between estimated values and measurements overall, and the estimated $C_n^2$ values are even better than the ones obtained by this approach over the ocean surface layer. The encouraging performance of this approach has a concrete practical implementation of ground-based optical applications over snow and sea ice.

A seeing model based on the Tatarskii equation, which uses wind shear and temperature gradient as inputs, has been proposed for Dome A in our previous study. It has been shown that the seeing was correctly reproduced statistically. In this paper, in order to investigate the ability of the Polar version of the Weather Research and Forecasting (PWRF) model to forecast the seeing, we have tried three different PWRF-simulated wind shear and temperature gradient combinations of two levels for the near-ground. The three combinations all give good performance with the correlation coefficients being higher than 0.75, when compared with the seeing measured by the Kunlun Differential Image Motion Monitor at Dome A during the summer of 2019. Besides this, the gradient Richardson number (Ri), which was also simulated by the PWRF model, basically behaved as expected as the Ri is generally large when the measured seeing is small. These results suggest that the PWRF model can be used to forecast the astronomical seeing above Dome A.

The distribution of optical turbulence ( C n 2 profiles) is the fundamental parameter closely related to the design and application of optoelectronic systems. Since systematic direct measurements of optical turbulence for many climates and seasons are not available, it is useful to estimate C n 2 effectively from the routine meteorological parameters. The C n 2 profiles are estimated by routine meteorological parameters based on the Tatarskii model, and the estimated results are compared with the corresponding radiosonde measurements from the field campaigns at Rongcheng ( 122.37 ∘ E , 37.15 ∘ N ), Taizhou ( 121.42 ∘ E , 28.62 ∘ N ), and Dachaidan ( 95.35 ∘ E , 37.74 ∘ N ) in China. The agreement between the estimation model and the measurement is very close, except for a portion of the atmosphere where it showed considerable difference. Additionally, statistical operators are used to quantify the performance of the estimated model, and the statistical results also show that the estimated and measured C n 2 profiles are consistent well. Furthermore, the integrated parameters (such as the Fried parameter, r 0 ) from radiosonde measurement are 7.92 cm, 5.39 cm, and 3.68 cm at Rongcheng, Taizhou, and Dachaidan, respectively. Therefore, the C n 2 profiles and their characteristics in these typical climate sites provide useful information to assess the effect of laser transmission in the atmosphere, which are usually used in the design of optoelectronic systems and astronomical site testing.

An optical turbulence ( C n 2 ) was found to be concentrated predominantly in the thin surface layer (SL) above the Antarctic Plateau. We present an estimation of the behavior of the SL C n 2 during the summer time over the entire Antarctic Plateau, using the polar-optimized version of the Weather Research and Forecast model (Polar WRF) coupled with the Monin–Obukhov similarity theory. The results show that the C n 2 is affected by the sunlight direction and terrain height. The C n 2 minimum occurs sometime around the morning and evening transitions, when the condition of neutral stability is achieved inside the SL. These C n 2 minima may be attributed to the relatively weaker thermal convection resulting from a small temperature difference. The simulated C n 2 data coincide well with the measurements taken at the Antarctic Taishan Station using a micro-thermometer and sonic anemometer; the data are also in agreement with the seeing values obtained from a differential image motion monitor. In addition, the Polar WRF captured the C n 2 minimum more precisely compared to the standard WRF.