Izvestiya of Saratov University.

Earth Sciences

ISSN 1819-7663 (Print)
ISSN 2542-1921 (Online)
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Language: 
Russian
Heading: 
Geography
Article type: 
Article
UDC: 
551.5
DOI: 
10.18500/1819-7663-2022-22-4-230-234
EDN: 
LPKOEH

Application of time series models for forecasting the global temperature anomalies

Autors: 
Bogdanov Mikhail Borisovich, Saratov State University
Morozova Svetlana Vladimirovna, Saratov State University
Alimpieva Mariya A., Saratov State University
Abstract: 

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, which can be used to predict the values of the series. Three models of the series 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.

Key words: 
forecasting
global temperature
time series models
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Received: 
15.08.2022
Accepted: 
01.09.2022
Published: 
23.12.2022