Investigating the Trend of Temperature Changes in Isfahan Station, Iran Using the Sequential Mann-Kendall Method

Abstract

During recent decades, global climate change has been one of the most important research topics in the study of the earth, and its consequences have been reported in many types of research. The aim of this research is to investigate the trend of monthly, seasonal and annual temperature changes in Isfahan province, Iran using the non-parametric Mann-Kendall test. In this research, to investigate the trend of temperature changes in Isfahan, the mean monthly, seasonal, and annual temperature data during a 67 years period (1951-2017) has been used. Then, the occurrence time and direction of trend of all studied temperature series were specified using sequential Mann-Kendall test. The statistical analysis of the results showed that all three parameters are distributed symmetrically and follow the normal distribution. The results showed that the mean monthly temperature time series had non-significant trend at level of 5%. The average seasonal trend of temperature using the sequential Mann -Kendall test indicates non-significant trend in the winter and an increasing trend in other seasons, but this trend is nonsignificant at level of 5%. The results revealed an increasing trend in the annual temperature series, which was significant at level of 5%.

Keywords

• climate changes
• non-parametric test
• temperature
• time series