Abstract

Introduction. It is known that the time course of temperature during the year is seasonal. However, the rates of temperature growth in transition periods are different. This complicates the prediction of such an important parameter, in particular for agriculture, as the air temperature of the surface layer of the atmosphere. Accordingly, the article analyzes the intra-annual variability of air temperature and compares it with a sinusoidal model of the annual temperature course. Materials and research methods. The time series of the air temperature of the surface layer of the atmosphere for the city of Stavropol are considered and the task is to compare the actual and theoretical values of annual amplitudes. In the elementary (sinusoidal) model, this theoretical value turns out to be directly proportional to the annual variance. The time series of temperature differences (inter-monthly changes), the so-called discrete derivatives, is also considered, and the comparison of the usual and discrete derivative of the sine function as an elementary model of the annual temperature course is carried out. A new value is introduced – the standard deviation of variability, which also characterizes the variance, yet not for a number of temperatures, but their differences. Research results and their discussion. It is noted that the theoretical (i.e., valid for the sinusoidal model) and the actual value of the amplitude of the annual temperature course are quite well matched. However, due to non-periodic deviations, the difference between these values can reach 2 °C, which is characterized by asymmetry on the intra-annual variability chart. In addition, the average annual temperature course is considered and its analysis is carried out using discrete derivatives. It is shown that the ratio of the annual temperature amplitude to the amplitude of the discrete derivative of this value is equal to the cyclic frequency of fluctuations of the annual temperature course. Conclusions. The results obtained confirm the possibility of using a sinusoidal model of the annual temperature course (although with some limitations related to the asymmetry and shift of intra-annual peak points). The analysis of the annual temperature course using discrete derivatives and its comparison with the sinusoidal model revealed the features of the average annual intra-annual variability of surface air temperature for the city of Stavropol for the period 1944 – 2022. Sometimes there is a change in the rate of heating or cooling; in rare cases, there is an inversion when considering the time series of average monthly temperatures).

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