TI - The assessment of Iran Monthly and seasonal Mean Temperatures sensitivity to Global land-Oceans mean Temperature index PT - JOURNAL ARTICLE TA - geospace JN - geospace VO - 17 VI - 58 IP - 58 4099 - http://geographical-space.iau-ahar.ac.ir/article-1-867-en.html 4100 - http://geographical-space.iau-ahar.ac.ir/article-1-867-en.pdf SO - geospace 58 ABĀ  - Although it is questionable whether there is climate change, but almost all climatologists agree global warming is a problem and that climate risk. 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's, 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. According to the results, all studies stations apart from Urmia and Khorramabad experience increasing trend in the average of temperature. The most influence over global warming observed from April to October is the month of the summer than other months of the relationship that has a significant high than the average summer temperature is going up. This process in the analysis of time-series and temperature trends has been quite evident. Change in trend occurred been a significant in most months and changes in the average temperature trend has been confirmed. The results obtained from the analysis period (hot and cold) temperatures average, indicating a strong relation to the heat period than the cold periods. The change in temperature trend occurred in both studies period, According to the results obtained are quite significant. CP - IRAN IN - LG - eng PB - geospace PG - 25 PT - Research YR - 2017