5 research outputs found
X-ray imaging and computed tomography of conifer tree rings for climatological purposes
This paper presents images of wood structure for various measurement regimes of X-ray microtomography. This is done by obtaining tomographic slices (iSee, CTvox), averaging them with the help of a statistical script called Adobe Photoshop, converting the average images into multidimensional data sets, and then averaging the image profiles (OriginCalc) to finally obtain a two-dimensional array of dendrochronological series of tree-ring density. The results of measurements are checked by a weight method to confirm the reliability of the data processing algorithm. For dendrochronological measurements of the ring density, it is shown that, depending on the width, two modes can be used: 80-Β΅m (for wide rings) and 30-Β΅m (for narrow rings). A measurement mode of less than 10-Β΅m is used to display the structure of the wood inside a ring. The results of XCT-density measurements performed with an 8-Β΅m resolution are given to assess the daily changes in wood density during the growing season
Probabilistic-statistical models of the dynamics of climatic changes in the Altai Mountains
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
Trends of climatic changes in density of year rings
ΠΠΊΡΡΠ°Π»ΡΠ½ΠΎΡΡΡ ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΡ ΠΎΠ±ΡΡΠ»ΠΎΠ²Π»Π΅Π½Π° Π½Π΅ΠΎΠ±Ρ
ΠΎΠ΄ΠΈΠΌΠΎΡΡΡΡ ΡΠΎΡ
ΡΠ°Π½Π½ΠΎΡΡΠΈ Π»Π΅ΡΠ½ΡΡ
Π·ΠΎΠ½ ΠΈ ΡΠ°Π·Π²ΠΈΡΠΈΡ Π»Π΅ΡΠ½ΠΎΠΉ ΠΈΠ½Π΄ΡΡΡΡΠΈΠΈ Π² ΡΠ΅Π»ΠΎΠΌ. Π¦Π΅Π»Ρ: ΠΈΡΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°Π½ΠΈΠ΅ ΠΌΠ½ΠΎΠ³ΠΎΠ»Π΅ΡΠ½ΠΈΡ
ΡΡΠ΅Π½Π΄ΠΎΠ² ΠΈΡΡΠ»Π΅Π΄ΡΠ΅ΠΌΡΡ
Ρ
Π°ΡΠ°ΠΊΡΠ΅ΡΠΈΡΡΠΈΠΊ: ΠΏΠ»ΠΎΡΠ½ΠΎΡΡΠΈ Π³ΠΎΠ΄ΠΈΡΠ½ΡΡ
ΠΊΠΎΠ»Π΅Ρ, ΠΈΠ·ΠΌΠ΅Π½Π΅Π½ΠΈΠΉ ΠΎΠ±ΡΠ΅Π³ΠΎ ΡΠΎΠ΄Π΅ΡΠΆΠ°Π½ΠΈΡ ΠΎΠ·ΠΎΠ½Π° Π² Π°ΡΠΌΠΎΡΡΠ΅ΡΠ΅ ΠΈ ΠΈΠ½Π΄Π΅ΠΊΡΠ° Π°ΡΠΈΠ΄Π½ΠΎΡΡΠΈ Π΄Π΅ ΠΠΎΡΡΠΎΠ½Π° Π΄Π»Ρ ΠΎΡΠ΅Π½ΠΊΠΈ ΠΊΠ»ΠΈΠΌΠ°ΡΠΈΡΠ΅ΡΠΊΠΈΡ
ΠΈΠ·ΠΌΠ΅Π½Π΅Π½ΠΈΠΉ; ΡΠ°Π·Π»ΠΎΠΆΠ΅Π½ΠΈΠ΅ Π΄Π΅Π½Π΄ΡΠΎΡ
ΡΠΎΠ½ΠΎΠ»ΠΎΠ³ΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ ΡΠΈΠ³Π½Π°Π»Π° Π½Π° ΠΊΠΎΠΌΠΏΠΎΠ½Π΅Π½ΡΡ, ΡΠ²ΡΠ·Π°Π½Π½ΡΠ΅ Ρ ΠΎΡΠ΄Π΅Π»ΡΠ½ΡΠΌΠΈ ΡΠ°ΠΊΡΠΎΡΠ°ΠΌΠΈ. ΠΠ±ΡΠ΅ΠΊΡΡ: Π²ΡΠ΅ΠΌΠ΅Π½Π½ΡΠ΅ ΡΡΠ΄Ρ ΠΎΠ±ΡΠ΅Π³ΠΎ ΡΠΎΠ΄Π΅ΡΠΆΠ°Π½ΠΈΡ ΠΎΠ·ΠΎΠ½Π° Π² Π°ΡΠΌΠΎΡΡΠ΅ΡΠ΅, ΠΏΠ»ΠΎΡΠ½ΠΎΡΡΡ Π³ΠΎΠ΄ΠΈΡΠ½ΡΡ
ΠΊΠΎΠ»Π΅Ρ ΠΈ ΠΈΠ½Π΄Π΅ΠΊΡ Π°ΡΠΈΠ΄Π½ΠΎΡΡΠΈ Π΄Π΅ ΠΠΎΡΡΠΎΠ½Π°. ΠΠ΅ΡΠΎΠ΄Ρ: Π°Π½Π°Π»ΠΈΠ· Π²ΡΠ΅ΠΌΠ΅Π½Π½ΡΡ
ΡΡΠ΄ΠΎΠ², ΡΠΏΠ΅ΠΊΡΡΠ°Π»ΡΠ½ΡΠΉ ΡΠΈΠ½Π³ΡΠ»ΡΡΠ½ΡΠΉ Π°Π½Π°Π»ΠΈΠ· (ΠΌΠ΅ΡΠΎΠ΄ Β«ΠΡΡΠ΅Π½ΠΈΡΠ°Β», F-ΠΊΡΠΈΡΠ΅ΡΠΈΠΉ). Π Π΅Π·ΡΠ»ΡΡΠ°ΡΡ. ΠΡΠ» Π²ΡΠΏΠΎΠ»Π½Π΅Π½ Π°Π½Π°Π»ΠΈΠ· Π΄Π΅Π½Π΄ΡΠΎΡ
ΡΠΎΠ½ΠΎΠ»ΠΎΠ³ΠΈΡΠ΅ΡΠΊΠΈΡ
ΠΈ ΠΊΠ»ΠΈΠΌΠ°ΡΠΈΡΠ΅ΡΠΊΠΈΡ
Π΄Π°Π½Π½ΡΡ
Π² Π΄Π²ΡΡ
ΡΠΈΡΠ»Π΅Π½Π½ΡΡ
ΡΠΊΡΠΏΠ΅ΡΠΈΠΌΠ΅Π½ΡΠ°Ρ
(Data Mining). ΠΡΠΎ ΠΏΠΎΠ·Π²ΠΎΠ»ΠΈΠ»ΠΎ ΠΏΠΎΠ»ΡΡΠΈΡΡ ΠΈΠ½ΡΠΎΡΠΌΠ°ΡΠΈΡ Π΄Π»Ρ ΠΏΡΠΎΠ³Π½ΠΎΠ·Π° ΡΡΠ»ΠΎΠ²ΠΈΠΉ Π³ΠΎΠ΄ΠΈΡΠ½ΠΎΠ³ΠΎ ΠΏΡΠΈΡΠΎΡΡΠ° Ρ
Π²ΠΎΠΉΠ½ΡΡ
ΠΈ ΡΠ²ΡΠ·Π°ΡΡ ΠΎΡΠ΄Π΅Π»ΡΠ½ΡΠ΅ ΠΊΠΎΠΌΠΏΠΎΠ½Π΅Π½ΡΡ Π΄Π΅Π½Π΄ΡΠΎΡ
ΡΠΎΠ½ΠΎΠ»ΠΎΠ³ΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ ΡΠΈΠ³Π½Π°Π»Π° Ρ Π²ΠΎΠ·Π΄Π΅ΠΉΡΡΠ²ΠΈΠ΅ΠΌ ΠΎΠΏΡΠ΅Π΄Π΅Π»Π΅Π½Π½ΡΡ
ΡΠ°ΠΊΡΠΎΡΠΎΠ² (ΡΠ΅ΠΌΠΏΠ΅ΡΠ°ΡΡΡΠ°, ΠΎΡΠ°Π΄ΠΊΠΈ, ΡΠ»ΡΡΡΠ°ΡΠΈΠΎΠ»Π΅Ρ-B ΡΠ°Π΄ΠΈΠ°ΡΠΈΡ ΠΈΠ»ΠΈ Π£Π€-Π ΠΈ Π΄Ρ.). ΠΡΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°Π½ΠΈΠ΅ ΠΌΠ΅ΡΠΎΠ΄Π° Β«ΠΡΡΠ΅Π½ΠΈΡΠ°Β» Π² ΡΠΎΡΠ΅ΡΠ°Π½ΠΈΠΈ Ρ ΠΏΡΠ΅Π΄Π²Π°ΡΠΈΡΠ΅Π»ΡΠ½ΠΎ Π²ΡΠΏΠΎΠ»Π½Π΅Π½Π½ΡΠΌ ΡΠ°ΠΊΡΠΎΡΠ½ΡΠΌ Π°Π½Π°Π»ΠΈΠ·ΠΎΠΌ Π΄ΠΈΡΠΏΠ΅ΡΡΠΈΠΈ Π΄Π΅Π½Π΄ΡΠΎΡ
ΡΠΎΠ½ΠΎΠ»ΠΎΠ³ΠΈΡΠ΅ΡΠΊΠΈΡ
ΡΡΠ΄ΠΎΠ² ΠΏΠΎΠΌΠΎΠ³Π°Π΅Ρ Π²ΡΠ΄Π΅Π»ΠΈΡΡ ΠΊΠ»ΠΈΠΌΠ°ΡΠΈΡΠ΅ΡΠΊΡΡ ΠΈ Π£Π€-Π ΡΡΠ²ΡΡΠ²ΠΈΡΠ΅Π»ΡΠ½ΡΡ (ΡΠ°Π΄ΠΈΠ°ΡΠΈΠΎΠ½Π½ΡΡ) ΠΊΠΎΠΌΠΏΠΎΠ½Π΅Π½ΡΡ Π² ΠΎΡΠ΄Π΅Π»ΡΠ½ΡΠ΅ Π²ΡΠ΅ΠΌΠ΅Π½Π½ΡΠ΅ ΡΡΠ΄Ρ. ΠΡ ΠΌΠΎΠΆΠ΅ΠΌ ΠΈΡΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°ΡΡ ΠΏΠΎΠ»ΡΡΠ΅Π½Π½ΡΠ΅ ΠΊΠΎΠΌΠΏΠΎΠ½Π΅Π½ΡΡ Π΄Π»Ρ Π΄ΠΎΠ»Π³ΠΎΡΡΠΎΡΠ½ΠΎΠ³ΠΎ ΠΏΡΠΎΠ³Π½ΠΎΠ·ΠΈΡΠΎΠ²Π°Π½ΠΈΡ ΠΏΠ»ΠΎΡΠ½ΠΎΡΡΠΈ Π΄ΡΠ΅Π²Π΅ΡΠΈΠ½Ρ. Π‘ΠΈΠ³Π½Π°Π»Ρ Π£Π€-B ΡΠ°Π΄ΠΈΠ°ΡΠΈΠΈ (ΠΎΠ±ΡΠ΅Π³ΠΎ ΡΠΎΠ΄Π΅ΡΠΆΠ°Π½ΠΈΡ ΠΎΠ·ΠΎΠ½Π°) ΠΈ ΠΊΠ»ΠΈΠΌΠ°ΡΠΈΡΠ΅ΡΠΊΠΈΠΉ - Π΄Π»Ρ ΡΠ΅ΠΊΠΎΠ½ΡΡΡΡΠΊΡΠΈΠΈ ΠΈ ΠΏΡΠΎΠ³Π½ΠΎΠ·Π° Π°ΡΠΌΠΎΡΡΠ΅ΡΠ½ΡΡ
Ρ
Π°ΡΠ°ΠΊΡΠ΅ΡΠΈΡΡΠΈΠΊ (ΠΎΠ±ΡΠ΅Π³ΠΎ ΡΠΎΠ΄Π΅ΡΠΆΠ°Π½ΠΈΡ ΠΎΠ·ΠΎΠ½Π°, ΠΈΠ½Π΄Π΅ΠΊΡΠ° Π°ΡΠΈΠ΄Π½ΠΎΡΡΠΈ Π΄Π΅ ΠΠΎΡΡΠΎΠ½Π°). Π£ΡΠ°Π²Π½Π΅Π½ΠΈΡ Π½Π΅Π»ΠΈΠ½Π΅ΠΉΠ½ΡΡ
ΡΡΠ΅Π½Π΄ΠΎΠ² ΠΌΠ°ΠΊΡΠΈΠΌΠ°Π»ΡΠ½ΠΎΠΉ ΠΏΠ»ΠΎΡΠ½ΠΎΡΡΠΈ Π³ΠΎΠ΄ΠΈΡΠ½ΡΡ
ΠΊΠΎΠ»Π΅Ρ, ΠΎΠ±ΡΠ΅Π³ΠΎ ΡΠΎΠ΄Π΅ΡΠΆΠ°Π½ΠΈΡ ΠΎΠ·ΠΎΠ½Π°, ΠΈΠ½Π΄Π΅ΠΊΡΠ° Π°ΡΠΈΠ΄Π½ΠΎΡΡΠΈ Π΄Π΅ ΠΠΎΡΡΠΎΠ½Π° ΡΠ°ΠΊΠΆΠ΅ ΠΏΠΎΠ·Π²ΠΎΠ»ΡΡΡ ΠΏΠΎΠ»ΡΡΠΈΡΡ Π΄ΠΎΡΡΠΎΠ²Π΅ΡΠ½ΡΠΉ ΠΏΡΠΎΠ³Π½ΠΎΠ· ΡΡΠ»ΠΎΠ²ΠΈΠΉ ΡΠΎΡΠΌΠΈΡΠΎΠ²Π°Π½ΠΈΡ Π³ΠΎΠ΄ΠΈΡΠ½ΡΡ
ΠΊΠΎΠ»Π΅Ρ ΠΈ ΠΏΠ»ΠΎΡΠ½ΠΎΡΡΠΈ Π΄ΡΠ΅Π²Π΅ΡΠΈΠ½Ρ, Π½ΠΎ Π½Π° ΠΌΠ΅Π½ΡΡΠΈΠΉ ΠΏΠ΅ΡΠΈΠΎΠ΄, ΡΠ°ΠΊ ΠΊΠ°ΠΊ Π² Π½ΠΈΡ
Π½Π΅ ΡΡΠΈΡΡΠ²Π°Π΅ΡΡΡ ΡΠΈΠΊΠ»ΠΈΡΠ½ΠΎΡΡΡ ΠΊΠ»ΠΈΠΌΠ°ΡΠΈΡΠ΅ΡΠΊΠΈΡ
ΠΏΡΠΎΡΠ΅ΡΡΠΎΠ².The relevance of the research is caused by the need to conserve forest zones and to develop forest industry. The main aim of the research is to use long-term trends in characteristics under study such as density of annual rings, changes in total ozone in the atmosphere and the de Martonne aridity index for assessing climate change. In addition, another aim of the study is to de-compose the dendrochronological signal into components associated with individual factors. Objects of the research are time series of the total ozone content in the atmosphere, density of annual rings and the de Martonne aridity index. Methods: time series analysis, spectral singular analysis (Caterpillar-SSA method), F-criterion. Results. The authors have analyzed the dendrochronological and climatic data in two numerical experiments (Data Mining). This allowed obtaining the information for the forecast of annual growth of coniferous trees and linking the individual components of the dendrochronological signal with the influence of certain factors (temperature, precipitation, ultraviolet-B radiation, etc.). The use of the Ca-terpillar-SSA method in combination with previously made factor analysis of the dispersion of the dendrochronological series helps allocate climatic and sensitive to ultraviolet-B radiation components in separate time series. The obtained components can be used for longterm prediction of wood density. Ultraviolet-B radiation (total ozone content) and climate signal can be used for reconstruction and prediction of atmospheric characteristics (total ozone content, the de Martonne aridity index). Equations of nonlinear trends of maximum density of annual rings of coniferous trees, of total ozone content, of the de Martonne aridity index also allow obtaining a reliable prediction of the conditions of formation of annual rings and wood density, but for a shorter period, as they do not consider the cyclicity of climatic processes
Analysis of trigonometric components of time series of environmental monitoring data
ΠΠΊΡΡΠ°Π»ΡΠ½ΠΎΡΡΡ. ΠΡΠΎΠ³Π½ΠΎΠ· ΡΠΎΡΡΠΎΡΠ½ΠΈΡ ΠΏΡΠΈΡΠΎΠ΄Π½ΡΡ
ΡΠ΅ΡΡΡΡΠΎΠ² ΠΈ ΠΈΠ·ΠΌΠ΅Π½Π΅Π½ΠΈΠΉ ΠΊΠ»ΠΈΠΌΠ°ΡΠ° Π²ΡΠ΅Π³Π΄Π° Π°ΠΊΡΡΠ°Π»Π΅Π½, ΡΠ°ΠΊ ΠΆΠ΅, ΠΊΠ°ΠΊ ΠΈ ΠΏΠΎΠΈΡΠΊ Π½ΠΎΠ²ΡΡ
ΠΌΠ°ΡΠ΅ΠΌΠ°ΡΠΈΡΠ΅ΡΠΊΠΈΡ
ΠΏΠΎΠ΄Ρ
ΠΎΠ΄ΠΎΠ². ΠΠ½Π°Π»ΠΈΠ· Π΄Π΅Π½Π΄ΡΠΎΡ
ΡΠΎΠ½ΠΎΠ»ΠΎΠ³ΠΈΡΠ΅ΡΠΊΠΈΡ
ΠΈ ΠΊΠ»ΠΈΠΌΠ°ΡΠΈΡΠ΅ΡΠΊΠΈΡ
Π²ΡΠ΅ΠΌΠ΅Π½Π½ΡΡ
ΡΡΠ΄ΠΎΠ² Π΄Π°Π΅Ρ Π²Π°ΠΆΠ½ΡΡ ΠΈΠ½ΡΠΎΡΠΌΠ°ΡΠΈΡ Π΄Π»Ρ ΠΎΠΏΠΈΡΠ°Π½ΠΈΡ ΡΡΠΈΡ
ΡΡΠ΄ΠΎΠ², ΠΏΠΎΠ½ΠΈΠΌΠ°Π½ΠΈΡ, Π° ΡΠ°ΠΊΠΆΠ΅ ΠΏΡΠ΅Π΄ΡΠΊΠ°Π·Π°Π½ΠΈΡ ΠΏΠΎΠ²Π΅Π΄Π΅Π½ΠΈΡ ΡΡΠ΄ΠΎΠ², Ρ
Π°ΡΠ°ΠΊΡΠ΅ΡΠΈΠ·ΡΡΡΠΈΡ
Π³ΠΎΠ΄ΠΈΡΠ½ΡΠΉ ΠΏΡΠΈΡΠΎΡΡ Π»Π΅ΡΠΎΠ², ΠΏΡΠΎΡΠ΅ΠΊΠ°ΡΡΠΈΡ
Π² Π½ΠΈΡ
ΡΠΊΠΎΠ»ΠΎΠ³ΠΈΡΠ΅ΡΠΊΠΈΡ
ΠΏΡΠΎΡΠ΅ΡΡΠΎΠ², Π° ΡΠ°ΠΊΠΆΠ΅ ΠΊΠ»ΠΈΠΌΠ°ΡΠ° Π² ΡΠ΅Π»ΠΎΠΌ. Π Π°Π±ΠΎΡΡ ΡΠ°ΠΊΠΎΠ³ΠΎ ΠΏΠ»Π°Π½Π° ΠΏΠΎΠ»Π΅Π·Π½Ρ ΠΈ ΡΠ²ΡΠ·Π°Π½Ρ Ρ Π½Π΅ΠΎΠ±Ρ
ΠΎΠ΄ΠΈΠΌΠΎΡΡΡΡ ΡΠΎΡ
ΡΠ°Π½Π΅Π½ΠΈΡ Π·Π°ΠΏΠΎΠ²Π΅Π΄Π½ΡΡ
Π»Π΅ΡΠ½ΡΡ
Π·ΠΎΠ½ ΠΈ ΡΠ°Π·Π²ΠΈΡΠΈΡ Π»Π΅ΡΠ½ΠΎΠΉ ΠΈΠ½Π΄ΡΡΡΡΠΈΠΈ Π² ΡΠ΅Π»ΠΎΠΌ. Π¦Π΅Π»Ρ: ΠΏΡΠΎΠ³Π½ΠΎΠ·ΠΈΡΠΎΠ²Π°Π½ΠΈΠ΅ ΠΏΡΠΈΡΠΎΠ΄Π½ΡΡ
ΡΠ΅ΡΡΡΡΠΎΠ² ΠΈ ΠΊΠ»ΠΈΠΌΠ°ΡΠ° Π½Π° ΠΎΡΠ½ΠΎΠ²Π΅ Π²ΡΠ΄Π΅Π»Π΅Π½ΠΈΡ ΠΈ ΠΈΡΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°Π½ΠΈΡ ΠΌΠ½ΠΎΠ³ΠΎΠ»Π΅ΡΠ½ΠΈΡ
ΡΡΠ΅Π½Π΄ΠΎΠ² ΠΈ ΡΡΠΈΠ³ΠΎΠ½ΠΎΠΌΠ΅ΡΡΠΈΡΠ΅ΡΠΊΠΈΡ
ΡΠΎΡΡΠ°Π²Π»ΡΡΡΠΈΡ
ΠΈΠ·Π²Π΅ΡΡΠ½ΡΡ
Ρ
Π°ΡΠ°ΠΊΡΠ΅ΡΠΈΡΡΠΈΠΊ: ΠΏΠ»ΠΎΡΠ½ΠΎΡΡΠΈ Π³ΠΎΠ΄ΠΈΡΠ½ΡΡ
ΠΊΠΎΠ»Π΅Ρ, ΠΈΠ·ΠΌΠ΅Π½Π΅Π½ΠΈΠΉ ΠΎΠ±ΡΠ΅Π³ΠΎ ΡΠΎΠ΄Π΅ΡΠΆΠ°Π½ΠΈΡ ΠΎΠ·ΠΎΠ½Π° Π² Π°ΡΠΌΠΎΡΡΠ΅ΡΠ΅, Π²Π»ΠΈΡΡΡΠ΅Π³ΠΎ Π½Π° ΡΡΠΎΠ²Π΅Π½Ρ Π£Π€-Π ΡΠ°Π΄ΠΈΠ°ΡΠΈΠΈ ΠΈΠ»ΠΈ Π£Π€-Π, ΠΈ ΠΈΠ½Π΄Π΅ΠΊΡΠ° Π°ΡΠΈΠ΄Π½ΠΎΡΡΠΈ Π΄Π΅ ΠΠΎΡΡΠΎΠ½Π°, ΡΠΎΠ΄Π΅ΡΠΆΠ°ΡΠ΅Π³ΠΎ ΠΈΠ½ΡΠΎΡΠΌΠ°ΡΠΈΡ ΠΎ ΡΠ΅ΠΌΠΏΠ΅ΡΠ°ΡΡΡΠ΅ ΠΈ Π²Π»Π°ΠΆΠ½ΠΎΡΡΠΈ Π»Π΅ΡΠ½ΡΡ
Π·ΠΎΠ½; ΠΏΡΠ΅Π΄ΡΡΠ°Π²Π»Π΅Π½ΠΈΠ΅ ΠΈΡΡ
ΠΎΠ΄Π½ΡΡ
Π²ΡΠ΅ΠΌΠ΅Π½Π½ΡΡ
ΡΡΠ΄ΠΎΠ² Π² Π°Π΄Π΄ΠΈΡΠΈΠ²Π½ΠΎΠΉ ΡΠΎΡΠΌΠ΅ Π² Π°Π½Π°Π»ΠΈΡΠΈΡΠ΅ΡΠΊΠΎΠΌ Π²ΠΈΠ΄Π΅. ΠΠ±ΡΠ΅ΠΊΡΡ: Π²ΡΠ΅ΠΌΠ΅Π½Π½ΡΠ΅ ΡΡΠ΄Ρ ΠΎΠ±ΡΠ΅Π³ΠΎ ΡΠΎΠ΄Π΅ΡΠΆΠ°Π½ΠΈΡ ΠΎΠ·ΠΎΠ½Π° Π² Π°ΡΠΌΠΎΡΡΠ΅ΡΠ΅, ΠΏΠ»ΠΎΡΠ½ΠΎΡΡΠΈ Π³ΠΎΠ΄ΠΈΡΠ½ΡΡ
ΠΊΠΎΠ»Π΅Ρ ΠΈ ΠΈΠ½Π΄Π΅ΠΊΡΠΎΠ² Π°ΡΠΈΠ΄Π½ΠΎΡΡΠΈ Π΄Π΅ ΠΠΎΡΡΠΎΠ½Π°. ΠΠ΅ΡΠΎΠ΄Ρ: Π°Π½Π°Π»ΠΈΠ· Π²ΡΠ΅ΠΌΠ΅Π½Π½ΡΡ
ΡΡΠ΄ΠΎΠ² (Π΄Π΅ΠΊΠΎΠΌΠΏΠΎΠ·ΠΈΡΠΈΡ Π²ΡΠ΅ΠΌΠ΅Π½Π½ΠΎΠ³ΠΎ ΡΡΠ΄Π°, ΠΈΠ΄Π΅Π½ΡΠΈΡΠΈΠΊΠ°ΡΠΈΡ ΠΏΠ°ΡΠ°ΠΌΠ΅ΡΡΠΎΠ² ΠΌΠΎΠ΄Π΅Π»ΠΈ, ΠΏΡΠΎΠ³Π½ΠΎΠ·ΠΈΡΠΎΠ²Π°Π½ΠΈΠ΅ Π²ΡΠ΅ΠΌΠ΅Π½Π½ΠΎΠ³ΠΎ ΡΡΠ΄Π°), ΡΡΠ°ΡΠΈΡΡΠΈΡΠ΅ΡΠΊΠΈΠΉ Π°Π½Π°Π»ΠΈΠ· (F-ΠΊΡΠΈΡΠ΅ΡΠΈΠΉ, [chi]{2}- ΠΊΡΠΈΡΠ΅ΡΠΈΠΉ ΠΠΈΡΡΠΎΠ½Π°). Π Π΅Π·ΡΠ»ΡΡΠ°ΡΡ. ΠΡΠΎΠΈΠ·Π²Π΅Π΄Π΅Π½ Π°Π½Π°Π»ΠΈΠ· Π΄Π΅Π½Π΄ΡΠΎΡ
ΡΠΎΠ½ΠΎΠ»ΠΎΠ³ΠΈΡΠ΅ΡΠΊΠΈΡ
ΠΈ ΠΊΠ»ΠΈΠΌΠ°ΡΠΈΡΠ΅ΡΠΊΠΈΡ
Π΄Π°Π½Π½ΡΡ
Π½Π° ΠΏΡΠ΅Π΄ΠΌΠ΅Ρ Π½Π°Π»ΠΈΡΠΈΡ ΡΡΠΈΠ³ΠΎΠ½ΠΎΠΌΠ΅ΡΡΠΈΡΠ΅ΡΠΊΠΎΠΉ ΠΊΠΎΠΌΠΏΠΎΠ½Π΅Π½ΡΡ. ΠΡΠΎ Π΄Π°Π»ΠΎ Π²ΠΎΠ·ΠΌΠΎΠΆΠ½ΠΎΡΡΡ ΠΏΠΎΠ»ΡΡΠΈΡΡ ΡΠ²Π΅Π΄Π΅Π½ΠΈΡ Π΄Π»Ρ ΠΏΡΠΎΠ³Π½ΠΎΠ·Π° ΡΠ΅ΠΌΠΏΠ΅ΡΠ°ΡΡΡΡ, ΠΎΡΠ°Π΄ΠΊΠΎΠ², Π£Π€-Π ΠΈ Π΄Ρ. ΠΠΎΠ»ΡΡΠ΅Π½Ρ Π°Π½Π°Π»ΠΈΡΠΈΡΠ΅ΡΠΊΠΈΠ΅ Π²ΡΡΠ°ΠΆΠ΅Π½ΠΈΡ Π΄Π»Ρ ΡΡΠΈΠ³ΠΎΠ½ΠΎΠΌΠ΅ΡΡΠΈΡΠ΅ΡΠΊΠΈΡ
ΡΠΎΡΡΠ°Π²Π»ΡΡΡΠΈΡ
ΠΌΠ°ΠΊΡΠΈΠΌΠ°Π»ΡΠ½ΠΎΠΉ ΠΏΠ»ΠΎΡΠ½ΠΎΡΡΠΈ Π³ΠΎΠ΄ΠΈΡΠ½ΡΡ
ΠΊΠΎΠ»Π΅Ρ, ΠΎΠ±ΡΠ΅Π³ΠΎ ΡΠΎΠ΄Π΅ΡΠΆΠ°Π½ΠΈΡ ΠΎΠ·ΠΎΠ½Π°, ΠΈΠ½Π΄Π΅ΠΊΡΠ° Π°ΡΠΈΠ΄Π½ΠΎΡΡΠΈ Π΄Π΅ ΠΠΎΡΡΠΎΠ½Π°. Π‘ΠΎΠ²ΠΎΠΊΡΠΏΠ½ΠΎΡΡΡ ΡΡΠΈΠ³ΠΎΠ½ΠΎΠΌΠ΅ΡΡΠΈΡΠ΅ΡΠΊΠΎΠΉ ΡΠΎΡΡΠ°Π²Π»ΡΡΡΠ΅ΠΉ ΠΈ ΡΡΠ΅Π½Π΄Π° ΠΏΠΎΠ·Π²ΠΎΠ»ΡΠ΅Ρ ΠΏΠΎΠ»ΡΡΠΈΡΡ Π΄ΠΎΡΡΠΎΠ²Π΅ΡΠ½ΡΠΉ ΠΏΡΠΎΠ³Π½ΠΎΠ· ΠΈ ΡΠ΅ΠΊΠΎΠ½ΡΡΡΡΠΊΡΠΈΡ ΡΡΠ»ΠΎΠ²ΠΈΠΉ ΡΠΎΡΠΌΠΈΡΠΎΠ²Π°Π½ΠΈΡ Π³ΠΎΠ΄ΠΈΡΠ½ΡΡ
ΠΊΠΎΠ»Π΅Ρ ΠΈ ΠΏΠ»ΠΎΡΠ½ΠΎΡΡΠΈ Π΄ΡΠ΅Π²Π΅ΡΠΈΠ½Ρ. ΠΡΠΎΠ³Π½ΠΎΠ·Π½ΡΠ΅ ΠΌΠΎΠ΄Π΅Π»ΠΈ Π°ΠΏΠΏΡΠΎΠΊΡΠΈΠΌΠ°ΡΠΈΠΈ Π²ΡΠ΅ΠΌΠ΅Π½Π½ΡΡ
ΡΡΠ΄ΠΎΠ² ΡΡΠΈΠ³ΠΎΠ½ΠΎΠΌΠ΅ΡΡΠΈΡΠ΅ΡΠΊΠΈΠΌ ΠΏΠΎΠ»ΠΈΠ½ΠΎΠΌΠΎΠΌ ΠΌΠΎΠ³ΡΡ ΠΊΠΎΠ½ΠΊΡΡΠΈΡΠΎΠ²Π°ΡΡ Ρ ΠΏΡΠΎΠ³Π½ΠΎΠ·Π½ΡΠΌΠΈ ΠΌΠΎΠ΄Π΅Π»ΡΠΌΠΈ Π²ΡΠ΅ΠΌΠ΅Π½Π½ΡΡ
ΡΡΠ΄ΠΎΠ² ΡΠΏΠ΅ΠΊΡΡΠ°Π»ΡΠ½ΠΎ-ΡΠΈΠ½Π³ΡΠ»ΡΡΠ½ΠΎΠ³ΠΎ ΡΠ°Π·Π»ΠΎΠΆΠ΅Π½ΠΈΡ ("ΠΡΡΠ΅Π½ΠΈΡΠ°").The relevance. The forecast of the state of natural resources and climate change is always relevant, as well as the search for new mathematical approaches. Analysis of dendrochronological and climate time series provides important information for describing these series, understanding, and predicting the behavior of these series. Therefore, the relevance of the study is caused not only by the need to predict the growth of trees, forecasting environmental processes, climate in general, but also by the need to preserve forest zones and develop the forest industry as a whole. The main aim of the research is to identify and use long-term trends and trigonometric components of the studied characteristics: the density of annual rings, changes in the total ozone content in the atmosphere and the De Martonne aridity index to assess climate change. The original time series are presented in additive form in analytical one. Objects of the research are time series of the total ozone content in the atmosphere, density of annual rings and the De Martonne aridity index. Methods: time series analysis, statistical analysis, F-criterion. Results. The analysis of dendrochronological and climatic data for the presence of trigonometric components is produced. This made it possible to obtain information for the forecast of temperature, precipitation, ultraviolet-B radiation, etc. Analytical expressions for trigonometric components of maximum density of annual rings, total ozone content, De Martonne aridity index are obtained. The combination of the trigonometric component and the trend allows us to obtain a reliable forecast of the conditions for the formation of annual rings and the density of wood. The resulting model will provide a prediction of the value of a variable (UV-B radiation, the maximum density of annual rings or the De Morton aridity index) at unobserved moments of time
Reconstruction of changes in stratospheric ozone in the taiga forests based of the singular spectral analysis
ΠΠΊΡΡΠ°Π»ΡΠ½ΠΎΡΡΡ. ΠΡΠΎΠ±Π»Π΅ΠΌΠ° ΡΠ½ΠΈΠΆΠ΅Π½ΠΈΡ ΡΡΠΎΠ²Π½Ρ ΡΡΡΠ°ΡΠΎΡΡΠ΅ΡΠ½ΠΎΠ³ΠΎ ΠΎΠ·ΠΎΠ½Π° ΠΈ ΠΈΠ½ΡΠ΅ΡΠ΅Ρ ΠΊ Π΅Π³ΠΎ ΠΏΡΠΎΡΠ»ΡΠΌ ΠΈΠ·ΠΌΠ΅Π½Π΅Π½ΠΈΡΠΌ ΡΠ²ΡΠ·Π°Π½Ρ Ρ ΠΏΡΠΎΠΈΡΡ
ΠΎΠ΄ΡΡΠΈΠΌ ΠΏΡΠΈ ΡΡΠΎΠΌ ΡΠ²Π΅Π»ΠΈΡΠ΅Π½ΠΈΠ΅ΠΌ Π΄ΠΎΠ·Ρ ΡΠ»ΡΡΡΠ°ΡΠΈΠΎΠ»Π΅ΡΠΎΠ²ΠΎΠΉ ΡΠ°Π΄ΠΈΠ°ΡΠΈΠΈ Π² ΠΊΠΎΡΠΎΡΠΊΠΎΠ²ΠΎΠ»Π½ΠΎΠ²ΠΎΠΌ Π΄ΠΈΠ°ΠΏΠ°Π·ΠΎΠ½Π΅, Π΄ΠΎΡΡΠΈΠ³Π°ΡΡΠ΅ΠΉ ΠΏΠΎΠ²Π΅ΡΡ
Π½ΠΎΡΡΠΈ ΠΠ΅ΠΌΠ»ΠΈ. Π Π΅ΠΊΠΎΠ½ΡΡΡΡΠΊΡΠΈΡ ΠΈ ΠΏΡΠΎΠ³Π½ΠΎΠ· Π΄ΠΎΠ»Π³ΠΎΠΏΠ΅ΡΠΈΠΎΠ΄Π½ΡΡ
ΠΊΠΎΠ»Π΅Π±Π°Π½ΠΈΠΉ ΠΈΡΡΠ»Π΅Π΄ΡΠ΅ΠΌΡΡ
ΠΏΠ°ΡΠ°ΠΌΠ΅ΡΡΠΎΠ² ΠΌΠΎΠ³ΡΡ Π±ΡΡΡ ΠΎΡΡΡΠ΅ΡΡΠ²Π»Π΅Π½Ρ ΠΏΡΠΈ ΠΏΠΎΠΌΠΎΡΠΈ ΠΌΠ΅ΡΠΎΠ΄Π° ΠΌΠ½ΠΎΠΆΠ΅ΡΡΠ²Π΅Π½Π½ΠΎΠΉ ΡΠ΅Π³ΡΠ΅ΡΡΠΈΠΈ ΠΏΠΎ Π΄Π°Π½Π½ΡΠΌ ΠΏΠ»ΠΎΡΠ½ΠΎΡΡΠΈ Π³ΠΎΠ΄ΠΈΡΠ½ΡΡ
ΠΊΠΎΠ»Π΅Ρ Ρ
Π²ΠΎΠΉΠ½ΡΡ
. Π§ΡΠΎΠ±Ρ ΡΠ°ΡΡΠΈΡΠΈΡΡ Π±Π°Π·Ρ ΡΠΊΡΠΏΠ΅ΡΠΈΠΌΠ΅Π½ΡΠ°Π»ΡΠ½ΡΡ
Π΄Π°Π½Π½ΡΡ
, ΠΏΡΠΎΠ²ΠΎΠ΄ΡΡΡΡ ΠΏΠΎΠΈΡΠΊΠΎΠ²ΡΠ΅ ΡΠ°Π±ΠΎΡΡ ΠΏΠΎ ΠΈΠ·ΠΌΠ΅ΡΠ΅Π½ΠΈΡ Π½ΠΎΠ²ΡΡ
Ρ
Π°ΡΠ°ΠΊΡΠ΅ΡΠΈΡΡΠΈΠΊ Π³ΠΎΠ΄ΠΈΡΠ½ΡΡ
ΠΊΠΎΠ»Π΅Ρ, Π° ΡΠ°ΠΊΠΆΠ΅ ΡΡΠΎΡΠ½ΡΠ΅ΡΡΡ ΠΌΠ°ΡΠ΅ΠΌΠ°ΡΠΈΡΠ΅ΡΠΊΠΈΠΉ Π°ΠΏΠΏΠ°ΡΠ°Ρ ΠΌΠ΅ΡΠΎΠ΄ΠΈΠΊ ΠΏΡΠ΅Π΄Π²Π°ΡΠΈΡΠ΅Π»ΡΠ½ΠΎΠΉ ΠΎΠ±ΡΠ°Π±ΠΎΡΠΊΠΈ Π΄Π°Π½Π½ΡΡ
, Π°Π½Π°Π»ΠΈΠ·ΠΈΡΡΡΡΡΡ ΡΠ²ΡΠ·ΠΈ Π±ΠΈΠΎΠΈΠ½Π΄ΠΈΠΊΠ°ΡΠΎΡΠΎΠ² Ρ Π°ΡΠΌΠΎΡΡΠ΅ΡΠ½ΡΠΌΠΈ ΠΏΠ°ΡΠ°ΠΌΠ΅ΡΡΠ°ΠΌΠΈ, ΠΈ ΡΠ°Π·ΡΠ°Π±Π°ΡΡΠ²Π°ΡΡΡΡ Π½ΠΎΠ²ΡΠ΅ ΠΌΠΎΠ΄Π΅Π»ΠΈ ΠΈΡ
ΠΏΡΠΎΠ³Π½ΠΎΠ·Π°. Π Π΅ΠΊΠΎΠ½ΡΡΡΡΠΊΡΠΈΡ ΠΈΡΡΠΎΡΠΈΡΠ΅ΡΠΊΠΈΡ
ΠΈΠ·ΠΌΠ΅Π½Π΅Π½ΠΈΠΉ Π°ΡΠΌΠΎΡΡΠ΅ΡΠ½ΡΡ
Ρ
Π°ΡΠ°ΠΊΡΠ΅ΡΠΈΡΡΠΈΠΊ ΠΌΠΎΠΆΠ΅Ρ Π±ΡΡΡ ΡΠ°ΡΡΠΌΠΎΡΡΠ΅Π½Π° Π² ΠΊΠΎΠ½ΡΠ΅ΠΊΡΡΠ΅ ΠΏΠ΅ΡΡΠΏΠ΅ΠΊΡΠΈΠ²Ρ ΠΈΡΠΊΡΡΡΡΠ²Π΅Π½Π½ΠΎΠ³ΠΎ Π²ΠΎΡΡΡΠ°Π½ΠΎΠ²Π»Π΅Π½ΠΈΡ Π»Π΅ΡΠ½ΡΡ
ΡΠ΅ΡΡΡΡΠΎΠ². Π¦Π΅Π»Ρ: ΡΠ°ΡΡΠΌΠΎΡΡΠ΅ΡΡ ΠΌΠ΅ΡΠΎΠ΄ΠΈΠΊΡ ΡΠ΅ΠΊΠΎΠ½ΡΡΡΡΠΊΡΠΈΠΈ ΠΎΠ±ΡΠ΅Π³ΠΎ ΡΠΎΠ΄Π΅ΡΠΆΠ°Π½ΠΈΡ ΠΎΠ·ΠΎΠ½Π° Π½Π° ΠΎΡΠ½ΠΎΠ²Π΅ ΡΠ°Π·ΡΠ°Π±ΠΎΡΠ°Π½Π½ΠΎΠΉ ΠΌΠ½ΠΎΠ³ΠΎΠΊΠΎΠΌΠΏΠΎΠ½Π΅Π½ΡΠ½ΠΎΠΉ ΡΠΈΠ½Π³ΡΠ»ΡΡΠ½ΠΎΠΉ ΡΠΏΠ΅ΠΊΡΡΠ°Π»ΡΠ½ΠΎΠΉ ΠΌΠΎΠ΄Π΅Π»ΠΈ ΠΎΡΠΊΠ»ΠΈΠΊΠ° Π΄ΡΠ΅Π²Π΅ΡΠΈΠ½Ρ Π³ΠΎΠ΄ΠΈΡΠ½ΡΡ
ΠΊΠΎΠ»Π΅Ρ Ρ
Π²ΠΎΠΉΠ½ΡΡ
Π½Π° ΠΈΠ·ΠΌΠ΅Π½Π΅Π½ΠΈΡ Π°ΡΠΌΠΎΡΡΠ΅ΡΠ½ΡΡ
ΠΏΠ°ΡΠ°ΠΌΠ΅ΡΡΠΎΠ². ΠΠ±ΡΠ΅ΠΊΡΡ. Π ΡΠ΅ΡΠ΅Π½ΠΈΠ΅ ΡΠ΅Π·ΠΎΠ½Π° ΡΠΎΡΡΠ° Ρ Π΄Π΅ΡΠ΅Π²ΡΠ΅Π² ΡΠΎΡΠΌΠΈΡΡΠ΅ΡΡΡ Π΄ΡΠ΅Π²Π΅ΡΠ½Π°Ρ ΡΡΡΡΠΊΡΡΡΠ° Π³ΠΎΠ΄ΠΈΡΠ½ΡΡ
ΠΊΠΎΠ»Π΅Ρ ΡΠΎ ΡΠ²ΠΎΠΉΡΡΠ²Π°ΠΌΠΈ ΠΊΠΎΠΌΠΏΠΎΠ·ΠΈΡΠΈΠΎΠ½Π½ΠΎΠ³ΠΎ ΠΌΠ°ΡΠ΅ΡΠΈΠ°Π»Π°. ΠΠ°ΠΆΠ΄Π°Ρ ΠΈΠ· ΠΊΠΎΠΌΠΏΠΎΠ½Π΅Π½Ρ Π³ΠΎΠ΄ΠΈΡΠ½ΠΎΠ³ΠΎ ΠΊΠΎΠ»ΡΡΠ°: ΡΠ³Π»Π΅ΡΠΎΠ΄ΡΠΎΠ΄Π΅ΡΠΆΠ°ΡΠ°Ρ ΠΌΠ°ΡΡΠΈΡΠ°, Π²ΠΎΠ΄Π° ΠΈ ΡΠ³Π»Π΅ΠΊΠΈΡΠ»ΡΠΉ Π³Π°Π·, ΡΠΎΠ΄Π΅ΡΠΆΠΈΡ ΠΎΡΠΊΠ»ΠΈΠΊΠΈ Π½Π° ΠΈΠ·ΠΌΠ΅Π½Π΅Π½ΠΈΡ ΡΡΠ»ΠΎΠ²ΠΈΠΉ ΠΎΠΊΡΡΠΆΠ°ΡΡΠ΅ΠΉ ΡΡΠ΅Π΄Ρ. ΠΠ° ΠΎΡΠ½ΠΎΠ²Π΅ ΠΌΠ½ΠΎΠ³ΠΎΠΊΠΎΠΌΠΏΠΎΠ½Π΅Π½ΡΠ½ΠΎΠΉ ΠΌΠΎΠ΄Π΅Π»ΠΈ ΡΡΠΌΠΌΠ°ΡΠ½ΡΠ΅ ΠΎΡΠΊΠ»ΠΈΠΊΠΈ Π³ΠΎΠ΄ΠΈΡΠ½ΡΡ
ΠΊΠΎΠ»Π΅Ρ, ΠΏΠΎΠ»ΡΡΠ΅Π½Π½ΡΠ΅ ΠΏΡΠΈ ΠΏΠΎΠΌΠΎΡΠΈ ΠΏΡΠΎΠ³ΡΠ°ΠΌΠΌΠ½ΠΎΠ³ΠΎ ΠΎΠ±Π΅ΡΠΏΠ΅ΡΠ΅Π½ΠΈΡ Caterpillar SSA 3.40, ΠΌΠΎΠ³ΡΡ Π±ΡΡΡ ΠΈΡΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°Π½Ρ Π΄Π»Ρ ΡΠ΅ΠΊΠΎΠ½ΡΡΡΡΠΊΡΠΈΠΈ ΠΈΠ·ΠΌΠ΅Π½Π΅Π½ΠΈΠΉ ΠΎΠ±ΡΠ΅Π³ΠΎ ΡΠΎΠ΄Π΅ΡΠΆΠ°Π½ΠΈΡ ΠΎΠ·ΠΎΠ½Π° Π² Π·ΠΎΠ½Π°Ρ
Ρ ΠΎΠΏΡΠΈΠΌΠ°Π»ΡΠ½ΡΠΌΠΈ ΡΡΠ»ΠΎΠ²ΠΈΡΠΌΠΈ ΡΠΎΡΡΠ° Ρ
Π²ΠΎΠΉΠ½ΡΡ
Π² ΠΎΡΠ»ΠΈΡΠΈΠ΅ ΠΎΡ Π·ΠΎΠ½ Ρ Π΄ΠΎΠΌΠΈΠ½ΠΈΡΠΎΠ²Π°Π½ΠΈΠ΅ΠΌ ΡΠ΅ΠΌΠΏΠ΅ΡΠ°ΡΡΡΠ½ΠΎΠ³ΠΎ ΡΠ°ΠΊΡΠΎΡΠ°. ΠΠ΅ΡΠΎΠ΄Ρ: Π΄Π΅Π½Π΄ΡΠΎΡ
ΡΠΎΠ½ΠΎΠ»ΠΎΠ³ΠΈΡΠ΅ΡΠΊΠΈΠΉ ΠΌΠ΅ΡΠΎΠ΄; ΡΠΈΠ½Π³ΡΠ»ΡΡΠ½ΡΠΉ ΡΠΏΠ΅ΠΊΡΡΠ°Π»ΡΠ½ΡΠΉ Π°Π½Π°Π»ΠΈΠ·; ΡΠΊΠΎΠ½ΠΎΠΌΠ΅ΡΡΠΈΡΠ΅ΡΠΊΠΈΠ΅ ΠΌΠ΅ΡΠΎΠ΄Ρ Π°Π½Π°Π»ΠΈΠ·Π° Π²ΡΠ΅ΠΌΠ΅Π½Π½ΡΡ
ΡΡΠ΄ΠΎΠ²; ΠΈΠ½ΡΠ΅Π»Π»Π΅ΠΊΡΡΠ°Π»ΡΠ½ΡΠΉ Π°Π½Π°Π»ΠΈΠ· Π΄Π°Π½Π½ΡΡ
; ΠΈΠΌΠΈΡΠ°ΡΠΈΠΎΠ½Π½ΠΎΠ΅ ΠΌΠΎΠ΄Π΅Π»ΠΈΡΠΎΠ²Π°Π½ΠΈΠ΅. Π Π΅Π·ΡΠ»ΡΡΠ°ΡΡ. ΠΠΎΡΡΠΎΠ²Π΅ΡΠ½ΠΎΡΡΡ ΡΠ°Π·ΡΠ°Π±ΠΎΡΠ°Π½Π½ΠΎΠΉ ΠΌΠΎΠ΄Π΅Π»ΠΈ ΠΎΡΠΊΠ»ΠΈΠΊΠΎΠ² Π³ΠΎΠ΄ΠΈΡΠ½ΡΡ
ΠΊΠΎΠ»Π΅Ρ Ρ
Π²ΠΎΠΉΠ½ΡΡ
Π½Π° ΠΈΠ·ΠΌΠ΅Π½Π΅Π½ΠΈΡ Π°ΡΠΌΠΎΡΡΠ΅ΡΠ½ΡΡ
ΠΏΠ°ΡΠ°ΠΌΠ΅ΡΡΠΎΠ² ΠΏΠΎΠ΄ΡΠ²Π΅ΡΠΆΠ΄Π°Π΅ΡΡΡ Π½Π° Π²ΡΠ±ΠΎΡΠΊΠ΅ ΡΡΠ³ΠΎΠ΄ΠΈΡΠ½ΡΡ
Ρ
ΡΠΎΠ½ΠΎΠ»ΠΎΠ³ΠΈΠΉ ΠΊΠΎΠΌΠΏΠΎΠ½Π΅Π½Ρ Π΄ΡΠ΅Π²Π΅ΡΠΈΠ½Ρ. ΠΡΠΈΡΠ΅ΡΠΈΠΉ ΠΠ°ΡΠ±ΠΈΠ½Π°-Π£ΠΎΡΡΠΎΠ½Π° ΠΏΠΎΠ·Π²ΠΎΠ»ΡΠ΅Ρ Π²ΡΠ΄Π΅Π»ΠΈΡΡ Π³ΡΡΠΏΠΏΡ Ρ
ΡΠΎΠ½ΠΎΠ»ΠΎΠ³ΠΈΠΉ, Π² ΠΌΠΎΠ΄Π΅Π»ΡΡ
ΠΊΠΎΡΠΎΡΡΡ
ΠΎΡΡΡΡΡΡΠ²ΡΠ΅Ρ Π°Π²ΡΠΎΠΊΠΎΡΡΠ΅Π»ΡΡΠΈΡ Π²ΠΎΠ·ΠΌΡΡΠ΅Π½ΠΈΠΉ. ΠΡΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°Π½ΠΈΠ΅ ΠΌΠΎΠ΄Π΅Π»ΠΈ ΡΡΠΌΠΌΠ°ΡΠ½ΡΡ
ΠΎΡΠΊΠ»ΠΈΠΊΠΎΠ² Π΄Π»Ρ ΡΡΠ΅Ρ
ΠΊΠΎΠΌΠΏΠΎΠ½Π΅Π½Ρ Π΄ΡΠ΅Π²Π΅ΡΠΈΠ½Ρ ΡΡΡΠ΅ΡΡΠ²Π΅Π½Π½ΠΎ ΠΏΠΎΠ²ΡΡΠ°Π΅Ρ Π΄ΠΎΡΡΠΎΠ²Π΅ΡΠ½ΠΎΡΡΡ ΡΠ΅ΠΊΠΎΠ½ΡΡΡΡΠΊΡΠΈΠΈ ΠΈΡΡΠ»Π΅Π΄ΡΠ΅ΠΌΡΡ
Π°ΡΠΌΠΎΡΡΠ΅ΡΠ½ΡΡ
ΠΏΠ°ΡΠ°ΠΌΠ΅ΡΡΠΎΠ² Π΄Π»Ρ ΡΠ°Π΅ΠΆΠ½ΠΎΠΉ Π·ΠΎΠ½Ρ Ρ ΠΎΠΏΡΠΈΠΌΠ°Π»ΡΠ½ΡΠΌΠΈ ΡΡΠ»ΠΎΠ²ΠΈΡΠΌΠΈ Π΄Π»Ρ Π³ΠΎΠ΄ΠΈΡΠ½ΠΎΠ³ΠΎ ΠΏΡΠΈΡΠΎΡΡΠ° Π΄Π΅ΡΠ΅Π²ΡΠ΅Π². ΠΠ°Π½Π½ΡΠ΅ ΡΠ΅ΠΊΠΎΠ½ΡΡΡΡΠΊΡΠΈΠΈ ΠΎΠ±ΡΠ΅Π³ΠΎ ΡΠΎΠ΄Π΅ΡΠΆΠ°Π½ΠΈΡ ΠΎΠ·ΠΎΠ½Π° Π΄Π»Ρ ΡΠ°Π΅ΠΆΠ½ΠΎΠΉ Π·ΠΎΠ½Ρ Π’ΠΎΠΌΡΠΊΠΎΠ³ΠΎ ΠΎΠ±Π»Π°ΡΡΠΈ ΠΏΠΎΠ·Π²ΠΎΠ»ΡΡΡ ΡΠ΄Π΅Π»Π°ΡΡ Π²ΡΠ²ΠΎΠ΄, ΡΡΠΎ, Π½Π΅ΡΠΌΠΎΡΡΡ Π½Π° ΡΠΎΡΡ ΡΡΠΎΠ²Π½Ρ ΠΎΠ·ΠΎΠ½Π° Π² ΡΡΡΠ°ΡΠΎΡΡΠ΅ΡΠ΅, ΠΈΠ·ΠΌΠ΅Π½Π΅Π½ΠΈΡ ΠΎΠ±ΡΠ΅Π³ΠΎ ΡΠΎΠ΄Π΅ΡΠΆΠ°Π½ΠΈΡ ΠΎΠ·ΠΎΠ½Π° Π½Π΅ Π²Π΅ΡΠ½ΡΠ»ΠΈΡΡ ΠΊ ΡΠ²ΠΎΠΈΠΌ ΡΡΠ΅Π΄Π½ΠΈΠΌ ΠΈΡΡΠΎΡΠΈΡΠ΅ΡΠΊΠΈΠΌ Π·Π½Π°ΡΠ΅Π½ΠΈΡΠΌ, ΡΡΠΎΠ²Π΅Π½Ρ Π£Π€-Π ΠΏΠΎ-ΠΏΡΠ΅ΠΆΠ½Π΅ΠΌΡ Π²ΡΡΠΎΠΊ, Π½ΠΎ, ΡΠ΅ΠΌ Π½Π΅ ΠΌΠ΅Π½Π΅Π΅, ΡΠ΅ΡΡΠΈΡΠΎΡΠΈΡ ΠΈ ΡΠΎΠ²ΡΠ΅ΠΌΠ΅Π½Π½ΡΠΉ ΠΏΠ΅ΡΠΈΠΎΠ΄ ΡΠ²Π»ΡΡΡΡΡ Π±Π»Π°Π³ΠΎΠΏΡΠΈΡΡΠ½ΡΠΌΠΈ Π΄Π»Ρ Π»Π΅ΡΠΎΠΏΠΎΡΠ°Π΄ΠΎΠΊ.The relevance. The problem of reducing the level of stratospheric ozone and the interest in its past changes are associated with the increase in the dose of ultraviolet radiation in the short-wave range reaching the Earth's surface. Reconstruction and prediction of longperiod fluctuations of the studied parameters can be carried out using the method of multiple regression according to the density of annual growth rings of conifers. In order to expand the experimental data base, exploratory work is being carried out to measure new characteristics of annual growth rings, as well as the mathematical apparatus of data preprocessing techniques is being refined, the connections of bioindicators with atmospheric parameters are being analyzed and new models of their prediction are being developed. Reconstruction of historical changes in atmospheric characteristics can be considered in the context of the prospect of artificial restoration of forest resources. The aim of the research is to discuss a technique for reconstructing the total ozone content based on a multicomponent singular spectral model of the response of conifers annual growth rings. Objects. During the growing season, trees form a woody structure of annual growth rings with the properties of a composite material. Each of the components of the annual growth rings such as a carbon-containing matrix, water and carbon dioxide contains responses to changes in environmental conditions. On the basis of a multicomponent model, the total responses of annual rings obtained using the Caterpillar SSA 3.40 software can be used to reconstruct changes in the total ozone content in zones with optimal coniferous growth conditions, as opposed to zones with dominance of the temperature factor. Methods: dendrochronological method; singular spectral analysis; econometric methods of time series analysis; data mining; simulation modeling. Results. The reliability of the model of responses of coniferous annual growth rings to changes in atmospheric parameters is confirmed by a sample of ergodic chronologies of wood components. The Durbin-Watson statistic makes it possible to identify a group of chronologies in whose models there is no autocorrelation of perturbations. The use of the cumulative response model for three wood components significantly increases the reliability of the reconstruction of the studied atmospheric parameters for the taiga zone with optimal conditions for annual tree growth. The data of the reconstruction of the total ozone content for the taiga zone of the Tomsk region allow us to conclude that despite the increase in the ozone level in the stratosphere, the changes in the total ozone content have not returned to their average historical values, the level of UV-B is still high, but nevertheless the territory and the modern period are favorable for forest plantations