Climate Change and Climate Disaster

Studying Changes of Time Series of Mean Temperature of Jolfa and Sarab Stations (1986-2018)

Document Type : Original Article

Author

Ava Gholami

Humanities faculty, Geography department. University of Zanjan

Abstract
In order to reveal climate changes from a statistical view, parametric and non-parametric statistical tests are used. Among these methods, homogeneity tests, trend analysis, Arima methods and spectral analysis in time series of climate elements including temperature can be mentioned. Natural and human factors are involved in the creation of heterogeneity, which can be investigated through various statistical tests to find out the heterogeneity of information and discover its causes. The results of these tests are not always the same and each one has special features. n this research, after quality control of the data and doing homogeneity tests and trend detection by using MATLAB, fitting and forecasting of Annual and Monthly average temperature of Jolfa and Sarab stations during the statistical period 1986-2018 done by using ARIMA and SARIMA patterns in MINITAB. For studying stationary of Model, Autocorrelation and Partial Autocorrelation Functions was applied and considering model evaluation criteria, finally, ARIMA (0,1,1) and SARIMA (0,0,1) (1,2,3)12 for Jolfa station and ARIMA (1,1,0) SARIMA (0,0,2) (1,2,3)12 for Sarab station was identified as a suitable model for predicting the average annual and monthly temperature.

Keywords

Temperature
Time Series
Jolfa
ARIMA
SARIMA
Subjects

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