Probabilistic-statistical models of the dynamics of climatic changes in the Altai Mountains

Abstract

A probabilistic-statistical parameterization of time series characterizing geological and climatic processes allows determining some regularities by an autocorrelation analysis of signals which differ in nature. The use of the autocorrelation method for analyzing data related to solar and tectonic activity and characterizing the level of stratospheric ozone (total ozone content), hydrothermal regimes (De Martonne aridity index), and wood structure (maximum density of annual rings) allows us to find regularities in time series of various natural processes. Data on the maximum density of Siberian larch trees growing in the Altai Mountains made it possible to calculate the past changes in total ozone content and the aridity index in the Altai Mountains from 1900 to 2014 based on some similarities in the series and a separation of a dendrochronological signal into its main components.

Original language	English
Article number	012025
Journal	IOP Conference Series: Earth and Environmental Science
Volume	211
Issue number	1
DOIs	https://doi.org/10.1088/1755-1315/211/1/012025
Publication status	Published - 17 Dec 2018
Event	International Conference and Early Career Scientists School on Environmental Observations, Modeling and Information Systems, ENVIROMIS 2018 - Tomsk, Russian Federation Duration: 5 Jul 2018 → 11 Jul 2018

ASJC Scopus subject areas

Environmental Science(all)
Earth and Planetary Sciences(all)

Access to Document

10.1088/1755-1315/211/1/012025

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Probabilistic-statistical models of the dynamics of climatic changes in the Altai Mountains. / Ustinova, V. N.; Zuev, V. V.; Bondarenko, S. L.; Ustinova, I. G.; Ovchinnikov, D. V.; Kirdjanov, A. V.

In: IOP Conference Series: Earth and Environmental Science, Vol. 211, No. 1, 012025, 17.12.2018.

Research output: Contribution to journal › Conference article › peer-review

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abstract = "A probabilistic-statistical parameterization of time series characterizing geological and climatic processes allows determining some regularities by an autocorrelation analysis of signals which differ in nature. The use of the autocorrelation method for analyzing data related to solar and tectonic activity and characterizing the level of stratospheric ozone (total ozone content), hydrothermal regimes (De Martonne aridity index), and wood structure (maximum density of annual rings) allows us to find regularities in time series of various natural processes. Data on the maximum density of Siberian larch trees growing in the Altai Mountains made it possible to calculate the past changes in total ozone content and the aridity index in the Altai Mountains from 1900 to 2014 based on some similarities in the series and a separation of a dendrochronological signal into its main components.",

author = "Ustinova, {V. N.} and Zuev, {V. V.} and Bondarenko, {S. L.} and Ustinova, {I. G.} and Ovchinnikov, {D. V.} and Kirdjanov, {A. V.}",

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AU - Ustinova, V. N.

AU - Zuev, V. V.

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AU - Ustinova, I. G.

AU - Ovchinnikov, D. V.

AU - Kirdjanov, A. V.

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AB - A probabilistic-statistical parameterization of time series characterizing geological and climatic processes allows determining some regularities by an autocorrelation analysis of signals which differ in nature. The use of the autocorrelation method for analyzing data related to solar and tectonic activity and characterizing the level of stratospheric ozone (total ozone content), hydrothermal regimes (De Martonne aridity index), and wood structure (maximum density of annual rings) allows us to find regularities in time series of various natural processes. Data on the maximum density of Siberian larch trees growing in the Altai Mountains made it possible to calculate the past changes in total ozone content and the aridity index in the Altai Mountains from 1900 to 2014 based on some similarities in the series and a separation of a dendrochronological signal into its main components.

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