论文标题
过滤技术可在短时间内增强光学湍流预测性能
Filtering techniques to enhance optical turbulence forecast performances at short time scales
论文作者
论文摘要
自适应光学(AO)支持的顶级地面天文设施的管理效率取决于我们预测光学湍流(OT)的能力和一组相关的大气参数。实际上,尽管AO目前能够达到极好的波前校正(在H频段中最高90%)的事实,但其性能在很大程度上取决于大气条件。事先了解湍流条件可以优化AO的使用。已经证明,第二天晚上可以提供可靠的光学湍流预测(CN2轮廓和集成的星形气候参数,例如观察,异闪角,波前连贯时间,...)。在本文中,我们证明,可以使用过滤技术在较短的时间尺度(一两个小时)上提高预测性能(一两个小时)(2至8)。这使我们能够实现以前从未获得过的预测准确性,并达到天文应用的基本里程碑。对于AO支持的地面望远镜的有效管理,一个或两个小时的时间尺度是最关键的时间。因此,此处显示的结果是对该领域的重要革命开放的。我们在大型双筒望远镜的操作预测系统中实施了这种方法,据我们所知,该中心被称为Alta Center,这是第一个在短时间内提供湍流和大气参数预测的操作系统,以支持科学操作。
The efficiency of the management of top-class ground-based astronomical facilities supported by Adaptive Optics (AO) relies on our ability to forecast the optical turbulence (OT) and a set of relevant atmospheric parameters. Indeed, in spite of the fact that the AO is able to achieve, at present, excellent levels of wavefront corrections (a Strehl Ratio up to 90% in H band), its performances strongly depend on the atmospheric conditions. Knowing in advance the turbulence conditions allows an optimization of the AO use. It has already been proven that it is possible to provide reliable forecasts of the optical turbulence (CN2 profiles and integrated astroclimatic parameters such as seeing, isoplanantic angle, wavefront coherence time, ...) for the next night. In this paper we prove that it is possible to improve the forecast performances on shorter time scales (order of one or two hours) with consistent gains (order of 2 to 8) using filtering techniques. This has permitted us to achieve forecasts accuracies never obtained before and reach a fundamental milestone for the astronomical applications. The time scale of one or two hours is the most critical one for an efficient management of the ground-based telescopes supported by AO. Results shown here open, therefore, to an important revolution in the field. We implemented this method in the operational forecast system of the Large Binocular Telescope, named ALTA Center that is, at our knowledge, the first operational system providing forecasts of turbulence and atmospheric parameters at short time scales to support science operations.