THE SUMMER TEMPERATURES FORECAST BY THE METHOD OF SINGULAR-SPECTRAL ANALYSIS IN THE SOUTH OF RUSSIA IN 2019-2023

Introduction: The 2019 Climate Report on the Territory of the Russian Federation states that warming continues in Russia, the rate of which is much higher than the global average for the globe. In recent years, the world has witnessed the largest natural disasters in modern human history, one of the...

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Main Authors: A. A. Tashilova, B. A. Ashabokov, L. A. Kesheva, N. V. Teunova
Format: Article
Language:Russian
Published: North-Caucasus Federal University 2022-07-01
Series:Наука. Инновации. Технологии
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Online Access:https://scienceit.elpub.ru/jour/article/view/58
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author A. A. Tashilova
B. A. Ashabokov
L. A. Kesheva
N. V. Teunova
author_facet A. A. Tashilova
B. A. Ashabokov
L. A. Kesheva
N. V. Teunova
author_sort A. A. Tashilova
collection DOAJ
description Introduction: The 2019 Climate Report on the Territory of the Russian Federation states that warming continues in Russia, the rate of which is much higher than the global average for the globe. In recent years, the world has witnessed the largest natural disasters in modern human history, one of the reasons for which are abnormally high temperatures. Materials and methods of the research: Based on the meteorological data for the period 1961-2018 provided by the North Caucasus Department of Hydrometeorology and Environmental Monitoring, an analysis and forecast of the series of summer temperatures in the south of the European territory of Russia (ETR) was made. The analysis and forecast of time series are based on the method of singular-spectral analysis, implemented in the program «Caterpillar»-SSA. The method makes it possible to single out various regularities in the behavior of time series, which are often not a priori obvious. Forecast of average summer temperatures in the south of the ETR for the period 2019-2023 using the program «Caterpillar»-SSA was carried out. The results of the study and their discussion: For the possibility of using the method of singular-spectral analysis, the average summer temperatures were selected according to the results of prediction criteria that determine the stability of the trend: the maximum value of the Hurst exponent on trend stability (H > 0,80); the maximum value of the determination coefficient to determine the statistical significance of the trend (R2 > 0,20). According to the results of a fractal analysis of the trend persistence of average summer temperatures, the maximum value of the Hurst exponent equal to H = 0,80 was obtained. To highlight the trend and periodic component, one (MC1) and three (MC3) main components were used. Using of the first twenty main components (MC20) made it possible to study and restore the internal structure of the entire time series as accurately as possible for a subsequent forecast for 5 years. The restoration, approximation and forecasting of the series was carried out by the obtained linear-recurrence formula. The forecast quality was determined by the following criteria: the standard deviation of the forecast series, the maximum deviation of the forecast values from the real ones, the relative forecast error and the results of the f-test conducted for the initial and forecast series for 1998-2018 at 5% error rate. Conclusions: According to the forecast for the period 2019-2023 average summer tem- perature tends to further increase. In 2022, one should expect an increase in average summer temperature to 22,0°C, which is close to the extremely high average summer temperature of 22,2°C in the south of the ETR in 2010.
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spelling doaj-art-3f8bfdc4b7994df5b11c2188bc781c712025-08-20T03:57:40ZrusNorth-Caucasus Federal UniversityНаука. Инновации. Технологии2308-47582022-07-010211513457THE SUMMER TEMPERATURES FORECAST BY THE METHOD OF SINGULAR-SPECTRAL ANALYSIS IN THE SOUTH OF RUSSIA IN 2019-2023A. A. Tashilova0B. A. Ashabokov1L. A. Kesheva2N. V. Teunova3High-Mountain Geophysical InstituteHigh-Mountain Geophysical InstituteHigh-Mountain Geophysical InstituteHigh-Mountain Geophysical InstituteIntroduction: The 2019 Climate Report on the Territory of the Russian Federation states that warming continues in Russia, the rate of which is much higher than the global average for the globe. In recent years, the world has witnessed the largest natural disasters in modern human history, one of the reasons for which are abnormally high temperatures. Materials and methods of the research: Based on the meteorological data for the period 1961-2018 provided by the North Caucasus Department of Hydrometeorology and Environmental Monitoring, an analysis and forecast of the series of summer temperatures in the south of the European territory of Russia (ETR) was made. The analysis and forecast of time series are based on the method of singular-spectral analysis, implemented in the program «Caterpillar»-SSA. The method makes it possible to single out various regularities in the behavior of time series, which are often not a priori obvious. Forecast of average summer temperatures in the south of the ETR for the period 2019-2023 using the program «Caterpillar»-SSA was carried out. The results of the study and their discussion: For the possibility of using the method of singular-spectral analysis, the average summer temperatures were selected according to the results of prediction criteria that determine the stability of the trend: the maximum value of the Hurst exponent on trend stability (H > 0,80); the maximum value of the determination coefficient to determine the statistical significance of the trend (R2 > 0,20). According to the results of a fractal analysis of the trend persistence of average summer temperatures, the maximum value of the Hurst exponent equal to H = 0,80 was obtained. To highlight the trend and periodic component, one (MC1) and three (MC3) main components were used. Using of the first twenty main components (MC20) made it possible to study and restore the internal structure of the entire time series as accurately as possible for a subsequent forecast for 5 years. The restoration, approximation and forecasting of the series was carried out by the obtained linear-recurrence formula. The forecast quality was determined by the following criteria: the standard deviation of the forecast series, the maximum deviation of the forecast values from the real ones, the relative forecast error and the results of the f-test conducted for the initial and forecast series for 1998-2018 at 5% error rate. Conclusions: According to the forecast for the period 2019-2023 average summer tem- perature tends to further increase. In 2022, one should expect an increase in average summer temperature to 22,0°C, which is close to the extremely high average summer temperature of 22,2°C in the south of the ETR in 2010.https://scienceit.elpub.ru/jour/article/view/58f-тестaverage summer temperaturessingular spectral analysismain componentsforecastmodel residualsf-testtrendsouth etr
spellingShingle A. A. Tashilova
B. A. Ashabokov
L. A. Kesheva
N. V. Teunova
THE SUMMER TEMPERATURES FORECAST BY THE METHOD OF SINGULAR-SPECTRAL ANALYSIS IN THE SOUTH OF RUSSIA IN 2019-2023
Наука. Инновации. Технологии
f-тест
average summer temperatures
singular spectral analysis
main components
forecast
model residuals
f-test
trend
south etr
title THE SUMMER TEMPERATURES FORECAST BY THE METHOD OF SINGULAR-SPECTRAL ANALYSIS IN THE SOUTH OF RUSSIA IN 2019-2023
title_full THE SUMMER TEMPERATURES FORECAST BY THE METHOD OF SINGULAR-SPECTRAL ANALYSIS IN THE SOUTH OF RUSSIA IN 2019-2023
title_fullStr THE SUMMER TEMPERATURES FORECAST BY THE METHOD OF SINGULAR-SPECTRAL ANALYSIS IN THE SOUTH OF RUSSIA IN 2019-2023
title_full_unstemmed THE SUMMER TEMPERATURES FORECAST BY THE METHOD OF SINGULAR-SPECTRAL ANALYSIS IN THE SOUTH OF RUSSIA IN 2019-2023
title_short THE SUMMER TEMPERATURES FORECAST BY THE METHOD OF SINGULAR-SPECTRAL ANALYSIS IN THE SOUTH OF RUSSIA IN 2019-2023
title_sort summer temperatures forecast by the method of singular spectral analysis in the south of russia in 2019 2023
topic f-тест
average summer temperatures
singular spectral analysis
main components
forecast
model residuals
f-test
trend
south etr
url https://scienceit.elpub.ru/jour/article/view/58
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