RESULTS OF SNOW COVER FORECAST IN THE CAUCASUS REGION USING THE METHOD OF SINGULAR-SPECTRAL ANALYSIS - Boris Azretaliyevich Ashabokov; Alla Amarbiyevna Tashilova; Lara Asirovna Kesheva (Наука. Инновации. Технологии)
Introduction: Changes in the mode of winter precipitation and snow cover can be considered as a complex indicator of the climate of the cold season, reflecting changes in the temperature regime, precipitation mode, the frequency of thaws, etc. Water reserves in the snow play a decisive role during the spring flood, affect soil moisture during the sowing of spring crops and the growth of winter crops. The importance of knowing the patterns of distribution of precipitation during the cold period for assessing the agro-climatic resources of the republic, which includes snow cover, should be emphasized. Materials and methods of research: The forecast of changes in snow cover characteristics is no less important than the forecast of climate changes (temperature and liquid precipitation). In this work, based on the meteorological data provided by the North Caucasian UGMS, we obtained the averaged series of the average decade height of snow cover and the number of days with snow cover for the south of the European territory of Russia (ETR). Using the method of singular-spectral analysis ("Caterpillar" -SSA), the dynamics were analyzed and the prognostic capabilities of the SSA method for the height of snow cover and the number of days with snow cover in the south of ETR were investigated. The SSA method is a tool for analyzing and predicting one-dimensional and multidimensional time series. On the basis of the T-test, the effectiveness of the recurrent R-SSA forecast of the average annual height of snow and the number of days with snow cover is shown. Results of the study and their discussion: For all the meteorological quantities considered, the periodicity of their changes, the standard deviation, the maximum deviation and the relative error were obtained. As a result of the selection of the main components (1, 3, and 13), prognostic trends of changes in the studied variables were obtained, periods of their increase and decrease were revealed, and predicted values of the average decade height of snow cover and the number of days for the period 2018-2022 were obtained. Conclusions: As a result of the use of the method of singular-spectral analysis, the forecast of such snow cover characteristics of the southern ETR, such as the average decade height of the snow cover and the number of days with snow cover of the southern ETR for 2018-2022, was made. The identified general trends in the studied characteristics of snow cover in the south of the ETR for the period up to 2022 allow characterizing regional climate changes in the south of the European part of Russia as an integral part of contemporary global warming.