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arXiv · 1701.02624

Turbulence velocity profiling for high sensitivity and vertical-resolution atmospheric characterization with Stereo-SCIDAR

J. Osborn·T. Butterley·M. J. Townson·A. P. Reeves·T. J. Morris·R. W. Wilson
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Abstract

As telescopes become larger, into the era of ~40 m Extremely Large Telescopes, the high- resolution vertical profile of the optical turbulence strength is critical for the validation, optimization and operation of optical systems. The velocity of atmospheric optical turbulence is an important parameter for several applications including astronomical adaptive optics systems. Here, we compare the vertical profile of the velocity of the atmospheric wind above La Palma by means of a comparison of Stereo-SCIntillation Detection And Ranging (Stereo- SCIDAR) with the Global Forecast System models and nearby balloon-borne radiosondes. We use these data to validate the automated optical turbulence velocity identification from the Stereo-SCIDAR instrument mounted on the 2.5 m Isaac Newton Telescope, La Palma. By comparing these data we infer that the turbulence velocity and the wind velocity are consistent and that the automated turbulence velocity identification of the Stereo-SCIDAR is precise. The turbulence velocities can be used to increase the sensitivity of the turbulence strength profiles, as weaker turbulence that may be misinterpreted as noise can be detected with a velocity vector. The turbulence velocities can also be used to increase the altitude resolution of a detected layer, as the altitude of the velocity vectors can be identified to a greater precision than the native resolution of the system. We also show examples of complex velocity structure within a turbulent layer caused by wind shear at the interface of atmospheric zones.

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J. Osborn, T. Butterley, M. J. Townson, A. P. Reeves, T. J. Morris, R. W. Wilson. 2017-01-10. Turbulence velocity profiling for high sensitivity and vertical-resolution atmospheric characterization with Stereo-SCIDAR. https://doi.org/10.1093/mnras%2Fstw2685

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