Evaluation of Extreme cold temperatures spatio-temporal Iran under the effects of global warming to reduce risks

According to climate changes in recent years due to consequences of economic, social and financial damages associated with uncomfortable events to reduce the risks of many importance. in an effective risk management system, identification and forecast as the main pillar of the system is considered to be so this study aims to mull over the effect of global warming in Iran so cold temperatures during the coming decades to say come in; since the identity of the regions and their zoning is an important step in order to reduce risks arising from it. In order to achieve the prime target of daily temperature data model EH5OM the Max Planck Institute Germany during the period (2015 - 2050 AD) , under the scenario A1B 1 / 75 differentiation degree arched , to the extent of Iran loaded . In the next step releasing data with a separate 0 / 27 * 0 / 27 arched by the model REGCM4 Downscaled. Cold days to identify the standard deviation of index temperature (NTD). Data in terms of rule extended heat index value (NTD< 0) are arranged and then the first 500 days that condition (NTD> -2) estimates that were selected in the sample sentence and an array of size 500 × 2140 was formed. The results indicate that the frost so that Iran could be using cluster analysis methods in neural network SOM divided into nine regions. In the coming decades Extreme cold in the western half and altitude bar (mountains and foothills) more visible areas inside and southern coasts. Minimum event Extreme cold Iran is related to the plain desert and maximum in the northwest.