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Machine learning-based seeing estimation and prediction using multi-layer meteorological data at Dome A,Antarctica
Hou X(侯旭); Du FJ(杜福嘉)
2023-04-08
Source PublicationAstronomy and Computing
Volume100710Issue:43Pages:1-12
Abstract

Atmospheric seeing is one of the most important parameters for evaluating and monitoring an astronomical site.Moreover,being able to predict the seeing in advance can guide observing decisions and significantly improve the efficiency of telescopes.However,it is not always easy to obtain long term and continuous seeing measurements from a standard instrument such as differential image motion monitor(DIMM),especially for those unattended observatories with challenging environments such as Dome A,Antarctica.In this paper,we present a novel machine learning-based framework for estimating and predicting seeing at a height of 8 m at Dome A,Antarctica,using only the data from a multi-layer automated weather station(AWS).In comparison with DIMM data,our estimate has a root mean square error(RMSE)of 0.18 arcsec,and the RMSE of predictions 20 min in the future is 0.12 arcsec for the seeing range from 0 to 2.2 arcsec.Compared with the persistence,where the forecast is the same as the last data point,our framework reduces the RMSE by 37 per cent.Our method predicts the seeing within a second of computing time,making it suitable for real-time telescope scheduling.

MOST Discipline Catalogue天文技术与方法
Document Type期刊论文
Identifierhttp://ir.niaot.ac.cn/handle/114a32/2120
Collection中国科学院南京天文光学技术研究所知识成果
期刊论文
Affiliation南京天文光学技术研究所
Recommended Citation
GB/T 7714
Hou X,Du FJ. Machine learning-based seeing estimation and prediction using multi-layer meteorological data at Dome A,Antarctica[J]. Astronomy and Computing,2023,100710(43):1-12.
APA Hou X,&Du FJ.(2023).Machine learning-based seeing estimation and prediction using multi-layer meteorological data at Dome A,Antarctica.Astronomy and Computing,100710(43),1-12.
MLA Hou X,et al."Machine learning-based seeing estimation and prediction using multi-layer meteorological data at Dome A,Antarctica".Astronomy and Computing 100710.43(2023):1-12.
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