Abstract
A new method for isolating the quasi-periodic component of a time series based on the description of its form is proposed. This form is set by alternating convex up and convex down sections, the inflection points are the form parameters. The quasi-periodic component is isolated by solving the problem of the best approximation of the presented series by quasi-periodic signals. This approach makes it possible to distinguish a component with a variable period in the time series. After morphological filtration of the component of the series modeling the daily variability, the remainder of the series becomes stationary, which allows using methods of mathematical statistics and Fourier analysis for its further study. Verification of the obtained results was carried out by comparison with the results of Fourier analysis. The effectiveness of the approach is illustrated by results of decomposition of a time series of CO2 concentration in the atmosphere.
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The work were obtained within the Russian Foundation for Basic Research grant (project No. 19-29-09044).
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All authors contributed to the study conception and design. The statement was performed by AIC and SNK. The development of methods for morphological analysis was carried out by AIC. Algorithms and programs for morphological filtering were created by VSA and DAT. Measurements of CO2 concentration were performed by VKA under the guidance of YVK. The results of the computational experiment were analyzed by VAG and NES. The first draft of the manuscript was written by AIC, and all authors commented on parallel versions of the manuscript. All authors have read and approved the final manuscript.
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Chulichkov, A.I., Aleshnovskii, V.S., Avilov, V.K. et al. Mathematical Methods for Investigation of Quasi-Periodic Time Series of Atmosphere Parameters. Pure Appl. Geophys. 179, 4627–4637 (2022). https://doi.org/10.1007/s00024-022-03171-0
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DOI: https://doi.org/10.1007/s00024-022-03171-0