Combining Cn2 Models To Forecast The Optical Turbulence At Paranal

ABSTRACT We applied a combination of models to improve the forecasts of refractive index structure coefficient ($C^{2}_{n}$) profiles and seeing at Paranal using high-temporal and spatial resolution simulations with the Weather Research and Forecasting model. We assessed our method with Stereo−SCIntillation Detection And Ranging observations from several nights between 2016 and 2018. The combined approach consists of the turbulent kinetic energy-based model to estimate the $C^{2}_{n}$ profile within the boundary layer and another model for the free atmosphere. We tested the Dewan, Jackson−Dewan, and Gladstone models. The implementation of the combined method gives better results than those obtained using each model separately for the whole atmospheric column. However, a much better agreement with observations is obtained when we use a calibration method to improve the results. Calibrated seeing forecasts at Paranal showed a root mean squared error of 0.30 arcsec and a bias around −0.1 arcsec for all the nights of 2017 and 2018, which are similar to previous results obtained at Paranal during the same nights. Due to its performance and rapid execution, the proposed methodology could be implemented as an operational tool to forecast the $C^{2}_{n}$ profiles and the seeing at Paranal and potentially over other astronomical sites around the world.