As the scientific community accepts the modern global climate changes, statistical analysis of a time series of hydrometeorological parameters becomes topical. A time series of air temperature was decomposed in this work; the decomposition allows one to distinguish regular, seasonal, and random components and to assess their statistical significance and adequacy to observation results. On the basis of a linear-regression model, a statistically significant increase in the annual average air temperature in the region under study was determined, both for the entire observation period and for separate months of the year.
$^1$Department of Physics, Moscow State University, Moscow, 119991 Russia
$^2$Department of Applied Mathematics and Information Technologies, Financial University under the Government of the Russian Federation, Leningradskii pr. 46, Moscow, 125993 Russia
$^3$Severtsov Institute of Ecology and Evolution, Russian Academy of Sciences, Leninskii pr. 33, Moscow, 119071 Russia.