ANALYSIS OF TRIGONOMETRIC COMPONENTS OF TIME SERIES OF ENVIRONMENTAL MONITORING DATA

Autor: Irina G. Ustinova, Svetlana L. Bondarenko, Olga V. Rozhkova
Jazyk: ruština
Rok vydání: 2021
Předmět:
Zdroj: Известия Томского политехнического университета: Инжиниринг георесурсов, Vol 331, Iss 10, Pp 135-145 (2021)
Druh dokumentu: article
ISSN: 24131830
2500-1019
2413-1830
DOI: 10.18799/24131830/2020/10/2859
Popis: 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.
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