Investigating the trend of average changes of annual temperatures in Iran
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Temperature is one of the key elements of climate formation and its changes can alter the climate structure of each region. To study the trend of temperature changes in Iran, the data from the three variables of average minimum temperature, average maximum temperature and average annual temperature of 43 synoptic stations were obtained from the Iranian Meteorological Organization for a 48-year statistical period (1966–2016). Moreover, in order to detect the trend of average changes of minimum, maximum and annual temperatures, fuzzy possibilistic regression and classical linear regression models were used. The comparison of the results of the slope of the change trend obtained from the two models clearly showed that, in most cases, the fuzzy possibilistic regression shows the slope of the change trend more than the classical linear regression. The statistics of root-mean-square error also showed that the function of classical linear regression was much better than fuzzy possibilistic regression. Therefore, based on the results of classical linear regression, the maximum amount of the average change trend of maximum annual temperatures of Iran is first observed in the west and northwest, and then in the northeastern of Iran. However, the average trend of minimum annual temperatures in Iran has shown more different spatial configurations than the average of maximum annual temperatures in Iran, with the highest rates of change in the east half, especially in the northeast. Finally, based on the classical linear regression model, it was observed that in the whole study period, 1.40 °C has been added to the average of maximum annual temperatures and 1.68 °C to the average of minimum annual temperatures in Iran.
KeywordsClimate change Classical linear regression Fuzzy possibilistic regression Trend
The authors wish to thank all who assisted in conducting this work.
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