عنوان مقاله [English]
With the emergence and intensification of the phenomenon of global warming, it is considered essential to develop efficient strategies to adapt to this phenomenon. In the first step, this necessity obtains a proper understanding of the vulnerability of different regions from climate change and provides adaptation strategies to climate change according to the regional capacities. The purpose of this research is to know the effect of global warming on the changes in high oven temperatures during the next decades in the territory of Iran. For this purpose, the data of the EH5OM database for the period from 2015 to 2050 AD in the form of 3-hour observations (8 times a day) under the A1B scenario. They were downloaded from the Max Planck Physics Center and microscaled using the REGCM4 regional model. Then, the hourly microscale air temperature data with a spatial resolution of 0.27 x 0.27 degrees of arc were converted into daily average, which resulted in a matrix of 13140 x 2140 dimensions. To identify hot days, we used the normalized temperature deviation (NTD) index; So that the data obtained from the output of the model were sorted according to the value of this profile and the range of heat rule (NTD>0), in the next step, the first 500 days that met the condition (NTD>2) were selected as a sample. The results showed that the perspective of Iran's hot fields can be divided into 9 regions based on the self-organizing neural network (SOM) method. Also, in the coming decades, maximum heat will occur in the western half and the high altitude belt (mountains and foothills), so that the temperature will be higher in the mentioned areas than in the interior and southern coasts of the country. The minimum occurrence of Farin Garm in Iran is related to the desert plain area and then the southeast of the country.