Systematization of data sources with spectral line parameters for the carbon dioxide molecule and its isotopologues in the W@DIS information system
A.V. Kozodoev1, A.I. Privezentsev1, A.Z. Fazliev1, N.N. Filippov2
1V.E. Zuev Institute of Atmospheric Optics of Siberian Branch of the Russian Academy of Science, 1, Academician Zuev square, Tomsk, 634021, Russia
2Saint Petersburg State University, 3, Ulyanovskaya str., Petrodvorets, St. Petersburg, 198504, Russia
Keywords: классификация контуров спектральных линий, профили спектральных линий диоксида углерода, информационная система W@DIS, line shapes classification, carbon dioxide line profiles, W@DIS information system
Abstract
Spectral line shapes are used to process experimental spectra when solving the inverse task of computing the collisional parameters of the line profiles. The difference in the shapes is due to different physical conditions (strong/weak collisions, large/small pressures, etc.). Numerous different line shapes are used in the study of the spectral line parameters of carbon dioxide, methane, methyl halides, and other molecules. The diversity of the line shapes used in the systematization of spectral line parameters adds complexity to the structures of data available in information systems and to the structures of individuals involved in ontological descriptions of the spectral line properties characterizing the line profiles. A brief classification of spectral line shapes and parameters is given, and the results of the systematization of spectral data relating to different line shapes used in processing of carbon dioxide spectra are presented. The line shapes available in the library are described, and an import system for spectral line parameters obtained from the solution of the direct and inverse tasks is built. Computer software for an automatic description of the properties of imported solutions was developed. The basic properties of the spectral data compiled in the W@DIS information system provide a description of the outcome of the imported data quality assessment analysis.
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