An atmosphere monitoring system for the Sardinia radio telescope. (25th November 2016)

• Record Type: Journal Article
• Authors: Buffa, F; Bolli, P; Sanna, G; Serra, G
• Is Part Of: Measurement science & technology. Volume 28:Number 1(2017:Jan.)
• Publication Date: 2016-11-25
• Subjects: radio telescope -- water vapor -- numerical weather prediction model -- radiometer -- GPS; Physical measurements -- Periodicals; Scientific apparatus and instruments -- Periodicals; Equipment and Supplies -- Periodicals; Science -- instrumentation -- Periodicals; Technology -- instrumentation -- Periodicals; Mesures physiques -- Périodiques; Physical measurements; Scientific apparatus and instruments; Periodicals; 502.87
• DOI: 10.1088/1361-6501/28/1/014004
• Languages: English
• ISSNs: 0957-0233

Abstract

Abstract: The Sardinia radio telescope (SRT) is a new facility managed by the Italian National Institute for Astrophysics (INAF). SRT will detect the extremely faint radio wave signals emitted by astronomical objects in a wide frequency range from decimeter to millimeter wavelengths. Especially at high frequencies (>10 GHz), specific weather conditions and interactions between signal and atmospheric constituents (mainly water and oxygen molecules) affect the radio astronomic observation reducing the antenna performances. Thus, modern ground-based telescopes are usually equipped with systems able to examine in real-time several atmospheric parameters (opacity, integrated water vapor, etc.), and in some cases to forecast the weather conditions (wind, rain, snow, etc.), in order to ensure the antenna safety and support the schedule of the telescope observations. Here, we describe the atmosphere monitoring system (AMS) realized with the aim to improve the SRT operative efficiency. It consists of a network of different sensors such as radiometers, radiosondes, weather stations, GPS and some well-established weather models. After a validation of the scheme, we successfully tested the AMS in two real practical scenarios, comparing the AMS outcomes with those of independent techniques. In the first one we were able to detect an incoming storm front applying different techniques (GPS, radiometer and the weather forecast model), while in the last one we modeled the SRT antenna system temperature at 22 GHz processing the AMS data set.