Analysis of long-term changes in temperature over iran using the cru ts dataset

Study of climate change helps in the management of water resources and agricultural production. Temperature increase is one of the most definite aspects of climate change. Limited number of weather stations and the quality and duration of records of weather variables are among the most important limiting factors in climate change studies. Application of gridded regional/global datasets is a promising option to overcome these limitations. In this study, temporal trends in annual, seasonal and monthly averages of daily minimum, mean and maximum temperatures were analysed using the data obtained from the CRU TS 4.01 gridded dataset and the Mann-Kendall (MK) test. The results show that over 1987-2016 (second period), long-term national annual average of daily mean temperature has increased by 0.4-1.2 °C across the country as compared to 1957-1986 (first period). Over the last here decades, temporal trend in annual average daily mean temperature was estimated at 0.39 °C.dec-1 (1.17 °C increase in 30 years). The observed increase in daily minimum temperature (1.23 °C in 30 years) over the second period was larger than the increase observed in daily mean temperature. Analysis of temporal trends in seasonal averages reveals that winter and spring, especially in the west and northwest, experienced the strongest positive trends over the last three decades. The results of this study confirm the occurrence of significant temperature changes in winter, spring and summer, which are important to the country’s agriculture sector.