عنوان مقاله [English]
Today, global warming effects on various aspects of the Earth are no secret to anyone. Because of this, the research ahead is done for the detection of global warming on minimum temperatures, monthly and periodic (hot and cold) as well. For this study, two groups of data, temperature data of 17 synoptic stations and corresponding amounts of data in global temperature anomalies were figured out over 60 years period of time (1951 to 2010). Goals, the Pearson correlation method for detecting relationships between data, linear and polynomial regression for trend analysis time series data , To illustrate the correlation between the spatial distribution of temperature data with global warming stations nationwide Geostatistical model Finally, non-parametric test for detecting significant temperature change Man - Kendall were used. Based on the results, apart from Khorramabad and urmia stations that have negative relation with global warming and Hamadan and Kerman stations that do not show any significant relationship with global warming, global warming is seen as a positive influence on the other stations. Caspian Bank stations than any other stations in the cold months of global warming have much more influence. Checking the changes of minimum temperature trend showed a significant change in several months. In the warm months the maximum temperature variability is seen in the southern stations of Ahwaz, Abadan, Bushehr and Shiraz. Results obtained from the survey period (hot and cold) minimum temperature, indicate a greater influence global temperature anomaly on the minimum temperatures are warm period of year. During the warm period, southern stations have had the highest influence on the station and during the cold period Caspian Bank stations have had the highest relationship with it. The changes were made based on both periods the obtained results are clarity significant.