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Characterization of the ground layer of turbulence at Paranal using a robotic SLODAR system.

Butterley, Timothy and Wilson, Richard and Sarazin, Marc and Dubbeldam, Marc and Osborn, James and Clark, Paul (2020) 'Characterization of the ground layer of turbulence at Paranal using a robotic SLODAR system.', Monthly notices of the Royal Astronomical Society., 492 (1). pp. 934-949.

Abstract

We describe the implementation of a robotic SLODAR instrument at the Cerro Paranal observatory. The instrument measures the vertical profile of the optical atmospheric turbulence strength, in 8 resolution elements, to a maximum altitude ranging between 100 and 500 m. We present statistical results of measurements of the turbulence profile on a total of 875 nights between 2014 and 2018. The vertical profile of the ground layer of turbulence is very varied, but in the median case most of the turbulence strength in the ground layer is concentrated within the first 50 m altitude, with relatively weak turbulence at higher altitudes up to 500 m. We find good agreement between measurements of the seeing angle from the SLODAR and from the Paranal DIMM seeing monitor, and also for seeing values extracted from the Shack–Hartmann active optics sensor of Very Large Telescope (VLT) Unit Telescope 1 (UT1), adjusting for the height of each instrument above ground level. The SLODAR data suggest that a median improvement in the seeing angle from 0.689 to 0.481 arcsec at wavelength 500 nm would be obtained by fully correcting the ground-layer turbulence between the height of the UTs (taken as 10 m) and altitude 500 m.

Item Type:Article
Full text:(AM) Accepted Manuscript
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Status:Peer-reviewed
Publisher Web site:https://doi.org/10.1093/mnras/stz3498
Publisher statement:This article has been accepted for publication in the Monthly notices of the Royal Astronomical Society ©: 2020 The Author(s). Published by Oxford University Press on behalf of the Royal Astronomical Society. All rights reserved.
Date accepted:09 December 2019
Date deposited:14 January 2020
Date of first online publication:12 December 2019
Date first made open access:14 January 2020

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