T. A. Khabarova, P. M. Zemlyanukha, E. M. Dombek, A. S. Marukhno, V. F. Vdovin
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引用次数: 0
Abstract
This paper presents a method for estimating precipitable water vapor from radiometric data using machine learning methods. The results of a study of precipitated water vapor for the territory of Chirag (Dagestan), Terskol peak (Elbrus region), Badary observatory (Buryatia) and the Spitsbergen archipelago are presented. A comparative analysis of the assessment of precipitable water vapor for the territory of ‘‘Badary’’ was carried out using GNSS, MERRA-2, water vapor radiometer data and predicting values using machine learning methods based on data from the MIAP-2 microwave radiometer.
期刊介绍:
Astrophysical Bulletin is an international peer reviewed journal that publishes the results of original research in various areas of modern astronomy and astrophysics, including observational and theoretical astrophysics, physics of the Sun, radio astronomy, stellar astronomy, extragalactic astronomy, cosmology, and astronomy methods and instrumentation.