Over the past few decades, higher greenhouse gas emissions have led to global warning and associted climate changes around the world. Climate change poses significant challenges to our life on Earth. A review of data recorded over the last 50 years shows that heat waves and heavy rains are preva‎lent in most parts of the world, resulting in an increase in the intensity, number, and frequency of extreme events, including floods and droughts. . The Intergovernmental Panel on Climate Change (IPCC), in a special report on the management of the risks of severe disasters, stressed that continued global warming will alter the severity and temporal and spatial pattern of climate change. For this reason, in the recent years, climatic hazards, which include heavy rainfall, very hot days, and increased length of heating periods, have been extensively studied on a wide range of spatial and temporal scales. In the present study, spatial-temporal changes and extreme temperatures based on various indicators in Iran have been investigated. For this purpose, minimum, average and maximum daily temperature data of 26 synoptic stations throughout Iran during the study period 1951 to 2019 were selected. First, the non-parametric Mann-Kendall test was used to examine the trend in the data set for 48 extracted indices related to extreme temperatures. 6 Climatic indicators and teleconnection patterns were also used to generate nonstationary models. The results showed that in general, the trend of temperature increase was significant at the level of 5% in the most indicators. In general, maximum and minimum extreme temperatures have experienced respectively about 5 ° C and 4 ° C, during the study period. The increasing trend of temperature in the western parts compared to other parts of Iran was significant, but it was observed that the increasing trend had the highest significance at minimum temperature and the lowest significant at medium temperature. In addition, the results showed that the estimated heat wave values under non-stationary assumptions can be very different from the corresponding values under stationary models. In general, changes in the concentration of carbon dioxide in the atmosphere have the largest share (superiority in 19 stations) in temperature non-stationary in different regions of Iran, and if this issue is ignored and analyzed with a stationary model, leading to error equll to 1 to 20 degrees at different stations.

عليرضا گوهري

محمدجواد زارعيان

سعيد اسلاميان، سعيد سلطاني