No Arabic 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).
The advent of a new generation of Adaptive Optics systems called Wide Field AO (WFAO) mark the beginning of a new era. By using multiple Guide Stars (GSs), either Laser Guide Stars (LGSs) or Natural Guide Stars (NGSs), WFAO significantly increases the field of view of the AO-corrected images, and the fraction of the sky that can benefit from such correction. Different typologies of WFAO have been studied over the past years. They all require multiple GSs to perform a tomographic analysis of the atmospheric turbulence. One of the fundamental aspects of the new WFAO systems is the knowledge of the spatio-temporal distribution of the turbulence above the telescope. One way to get to this information is to use the telemetry data provided by the WFAO system itself. Indeed, it has been demonstrated that WFAO systems allows one to derive the Cn2 and wind profile in the main turbulence layers (see e.g. Cortes et al. 2012). This method has the evident advantage to provide information on the turbulence stratification that effectively affects the AO system, property more difficultly respected by independently vertical profilers. In this paper, we compare the wind speeds profiles of GeMS with those predicted by a non-hydrostatical mesoscale atmospherical model (Meso-NH). It has been proved (Masciadri et al., 2013), indeed, that this model is able to provide reliable wind speed profiles on the whole troposphere and stratosphere (up to 20-25 km) above top-level astronomical sites. Correlation with measurements revealed to be very satisfactory when the model performances are analyzed from a statistical point of view as well on individual nights. Such a system appears therefore as an interesting reference to be used to quantify the GeMS wind speed profiles reliability.
Wide Field Adaptive Optics (WFAO) systems are among the most sophisticated AO systems available today on large telescopes. The knowledge of the vertical spatio-temporal distribution of the wind speed (WS) and direction (WD) are fundamental to optimize the performance of such systems. Previous studies already proved that the Gemini Multi-Conjugated AO system (GeMS) is able to retrieve measurements of the WS and WD stratification using the SLODAR technique and to store measurements in the telemetry data. In order to assess the reliability of these estimates and of the SLODAR technique applied to such a kind of complex AO systems, in this study we compared WS and WD retrieved from GeMS with those obtained with the atmospherical model Meso-Nh on a rich statistical sample of nights. It has been previously proved that, the latter technique, provided an excellent agreement with a large sample of radiosoundings both, in statistical terms and on individual flights. It can be considered, therefore, as an independent reference. The excellent agreement between GeMS measurements and the model that we find in this study, proves the robustness of the SLODAR approach. To by-pass the complex procedures necessary to achieve automatic measurements of the wind with GeMS, we propose a simple automatic method to monitor nightly WS and WD using the Meso-Nh model estimates. Such a method can be applied to whatever present or new generation facilities supported by WFAO systems. The interest of this study is, therefore, well beyond the optimization of GeMS performance.
We present in this study a mapping of the optical turbulence (OT) above different astronomical sites. The mesoscale model Meso-NH was used together with the Astro-Meso-Nh package and a set of diagnostic tools allowing for a full 3D investigation of the Cn2. The diagnostics implemented in the Astro-Meso-Nh, allowing for a full 3D investigation of the OT structure in a volumetric space above different sites, are presented. To illustrate the different diagnostics and their potentialities, we investigated one night and looked at instantaneous fields of meteorologic and astroclimatic parameters. To show the potentialities of this tool for applications in an Observatory we ran the model above sites with very different OT distributions: the antarctic plateau (Dome C, Dome A, South Pole) and a mid-latitude site (Mt. Graham, Arizona). We put particular emphasis on the 2D maps of integrated astroclimatic parameters (seeing, isoplanatic angles) calculated in different slices at different heights in the troposhere. This is an useful tool of prediction and investigation of the turbulence structure. It can support the optimization of the AO, GLAO and MCAO systems running at the focus of the ground-based telescopes.From this studies it emerges that the astronomical sites clearly present different OT behaviors. Besides, our tool allowed us for discriminating these sites.
We present a new automatic tool for time-domain astronomy - the Cambridge Photometric Calibration Server 2.0 - developed under OPTICON H2020 programme. It has been designed to respond to the need of automated rapid photometric data calibration and dissemination for transient events, primarily from Gaia space mission. CPCS has been in operation since 2013 and has been used to calibrate around 130 000 observations of hundreds of transients. We present the status of this tools development and demonstrate improvements made in the second version. The tests present the ability to combine CCD imaging data from multiple telescopes and a whole variety of instruments. New tool provides science-ready photometric data within minutes from observations in the automatic manner.
Accurate short-term wind speed forecasting is needed for the rapid development and efficient operation of wind energy resources. This is, however, a very challenging problem. Although on the large scale, the wind speed is related to atmospheric pressure, temperature, and other meteorological variables, no improvement in forecasting accuracy was found by incorporating air pressure and temperature directly into an advanced space-time statistical forecasting model, the trigonometric direction diurnal (TDD) model. This paper proposes to incorporate the geostrophic wind as a new predictor in the TDD model. The geostrophic wind captures the physical relationship between wind and pressure through the observed approximate balance between the pressure gradient force and the Coriolis acceleration due to the Earths rotation. Based on our numerical experiments with data from West Texas, our new method produces more accurate forecasts than does the TDD model using air pressure and temperature for 1- to 6-hour-ahead forecasts based on three different evaluation criteria. Furthermore, forecasting errors can be further reduced by using moving average hourly wind speeds to fit the diurnal pattern. For example, our new method obtains between 13.9% and 22.4% overall mean absolute error reduction relative to persistence in 2-hour-ahead forecasts, and between 5.3% and 8.2% reduction relative to the best previous space-time methods in this setting.