Volume 517, July 2010
|Number of page(s)||4|
|Published online||10 August 2010|
Typical duration of good seeing sequences at Concordia
Fizeau Laboratory, University of Nice Sophia Antipolis, CNRS, Observatoire Côte d'Azur, Parc Valrose, 06108 Nice Cedex, France e-mail: firstname.lastname@example.org
Accepted: 16 March 2010
Context. The winter seeing at Concordia is bimodal, i.e. either excellent or quite poor, depending on the altitude above the snow surface. We study the temporal behavior of the good seeing sequences. Efficient exploitation of extremely good seeing conditions with an adaptive optics system requires long integrations.
Aims. We examine the temporal distribution of time intervals providing excellent seeing at Concordia.
Methods. We create temporal windows of good seeing by applying a simple binary process: good or bad. We correct the autocorrelations of these windows for those of the existing data sets, since these are not continuous, often being interrupted by technical problems in addition to the adverse weather gaps. We infer the typical duration of good seeing sequences from these corrected autocorrelations. This study has to be a little detailed as its results depend on the season, summer or winter.
Results. When we adopt a threshold of 0.5 arcsec to define “good seeing”, we find that three characteristic numbers describe the temporal evolution of the good seeing windows. The first number is the mean duration of an uninterrupted good seeing sequence, which is τ0 = 7.5 h at 8 m above the ground and 15 h at 20 m. These sequences are randomly distributed in time, following a negative exponential law of damping time τ1 = 29 h (at elevation 8 m and 20 m), which represents our second number. The third number is the mean time between two 29 h episodes, which is T = 10 days at 8 m high (5 days at 20 m).
Conclusions. There is certainly no other site on Earth, except for the few other high altitude Domes on the Antarctic plateau, at which we can achieve these exceptionally high quality seeing conditions.
Key words: site testing / atmospheric effects / methods: statistical
© ESO, 2010
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