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arXiv · 1608.06489

Towards an automatic system for monitoring of CN2 and wind speed profiles with GeMS

Abstract

Wide Field Adaptive Optics (WFAO) systems represent the more sophisticated AO systems available today at large telescopes. A critical aspect for these WFAO systems in order to deliver an optimised performance is the knowledge of the vertical spatiotemporal distribution of the CN2 and the wind speed. Previous studies (Cortes et al., 2012) already proved the ability of GeMS (the Gemini Multi-Conjugated AO system) in retrieving CN2 and wind vertical stratification using the telemetry data. To assess the reliability of the GeMS wind speed estimates a preliminary study (Neichel et al., 2014) compared wind speed retrieved from GeMS with that obtained with the atmospherical model Meso-Nh on a small sample of nights providing promising results. The latter technique is very reliable for the wind speed vertical stratification. The model outputs gave, indeed, an excellent agreement with a large sample of radiosoundings (~ 50) both in statistical terms and on individual flights (Masciadri et al., 2013). Such a tool can therefore be used as a valuable reference in this exercise of cross calibrating GeMS on-sky wind estimates with model predictions. In this contribution we achieved a two-fold results: (1) we extended analysis on a much richer statistical sample (~ 43 nights), we confirmed the preliminary results and we found an even better correlation between GeMS observations and the atmospherical model with basically no cases of not-negligible uncertainties; (2) we evaluate the possibility to use, as an input for GeMS, the Meso-Nh estimates of the wind speed stratification in an operational configuration. Under this configuration these estimates can be provided many hours in advanced with respect to the observations and with a very high temporal frequency (order of 2 minutes or less).

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BibTeXRIS

E. Masciadri, B. Neichel, A. Guesalaga, A. Turchi. 2016-08-23. Towards an automatic system for monitoring of CN2 and wind speed profiles with GeMS. https://doi.org/10.1117/12.2231887

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