Spectral analysis of the time series for average annual values of the globally averaged surface temperature anomaly shows the presence of harmonics of the lunar nodal cycle with a period of 18.6 years,whichcan be used to predict the values of theseries. Three models of theseries were considered: autoregression AR(p), combined model of autoregression – integrated moving average ARIMA(p,d,q) and artificial neural network. It is shown that the ARIMA(4,1,4) model gives the best results for predicting the global temperature anomaly for three years.
The temperature and humidity regime of the Right Bank is considered according to the data of four weather stations in three natural climatic periods – stabilization, the first and second waves of global warming. There is an increase in the rate of warming from one natural climatic period to another. Against the background of a progressive rise in temperatures, there is an increase in the amount of precipitation in the cold half of the year and its decrease in the warm one. The revealed trend may indicate an increase in weather and climate risks of crop production in the Right Bank of the Saratov region
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