Temporal variability of the seeing of TMT sites

Abstract

Seeing stability is an important criterion of site characterization. Two sites, with the same seeing statistics, could in principle differ in their temporal stability and hence have their observatories perform differently. Temporal variability can, however, be defined in several ways, all of which may determine the performance of the observatories in different manner. In this paper, we propose three methods to measure variability each focusing on different applications: Selection (maximization of observation time), Image quality (seeing variation within a given integration time) and finally Scheduling (prediction of seeing fluctuation on a given time scale). We apply these methods to the seeing of the TMT candidate sites to determine their stability properties.

Thirty Meter Telescope Site Testing VI: Turbulence Profiles

“…The only site where the agreement is worse is SPM. This can be attributed to the increased acoustic noise due to the trees surrounding the site, which affect the SODAR measurements (see Travouillon et al 2009a for details).…”

“…But this τ 0;MASS has to be properly calibrated to obtain the real τ 0 and is generally unreliable for τ 0 ≳ 5 ms in the case of the TMT MASS systems (Els et al 2008). A thorough investigation of the τ 0 measurements obtained by the TMT site testing is given by Travouillon et al (2009b). Here, we make use of the uncalibrated τ 0;MASS data but only for data selection purposes for specific analyses within § 3.…”

Twilight observations with MASS-DIMM

“…In principle this is expectable -free atmosphere changes slower than ground layer because of larger scales. This point is closely related to temporal characteristics of seeing discussed by Travouillon, 2008 3 and can be considered as another way to describe the seeing variability because it can be applied not only to twilight observations but to any moment during night.…”

Efficient Minimization of Servo Lag Error in Adaptive Optics Using Data Stream Mining

“…There are two important extrapolation parameters that decide the prediction accuracy. The temporal variability of the turbulence parameters are also site dependent [9]. The parameters n and τ pf are called the data stream parameters and obviously depend on τ d and the spatial coherence length represented by Fried parameter, r 0 .…”