Assessment of extreme heat stress probabilities in Iran's urban settlements, using first order Markov chain model. (January 2018) - Roshan, Gholamreza; Nastos, Panagiotis T.
Highlights: The Universal Thermal Climate Index (UTCI) was used to define and visualize the bioclimatic conditions in Iran. In this work, first order Markov chain model was applied to estimate the probability of extreme heat stress conditions in Iran. The spatial distribution of extreme heat stress probabilities by bioclimatic atlas maps has been showed. The findings showed that a total of 83.7% of the stations have experienced UTCI classes of very strong (VSHS) or even extreme (EHS) heat stress indicating that Iran faces more VSHS and EHS events against cold stress events. Abstract: Extreme weather phenomena affect human societies, and especially thermal stress is a considerable threat. Therefore, the goal of this study is twofold: On one hand, to assess the frequencies of classes of the Universal Thermal Climate Index (UTCI) in Iran. The findings showed that a total of 83.7% of the stations have experienced UTCI classes of very strong (VSHS) or even extreme (EHS) heat stress indicating that Iran faces more VSHS and EHS events against cold stress events. On the other hand, in the process, first order Markov chain model was applied to estimate the probability of extreme heat stress conditions. One of the most important findings of this section was that 63.8% of the stations experienced VSHS conditions in the long term that maximum frequency of the probability of this condition appeared in the zone along the coastal strip of the Persian Gulf and Sea of Oman against to the rest of Iran, it is suggested that early warning system for heat stress should be designed, providing alerts on time to eliminate casualties and strengthen the resilience of the local population.