Reliability framework for characterizing heat wave and cold spell events

Extreme weather events such as heat waves and cold spells affect people’s lives. This study develops a probabilistic framework to evaluate spells. As case studies, average daily temperatures of meteorological stations the two cities (Tehran Vancouver) from 1995 2016 are used identify four main indicators including intensity, duration, rate occurrence. In addition, spatial analysis is obtained through MODIS’s land surface temperature product. To include possible uncertainties, predictive probability distributions intensity duration derived using Bayesian scheme Monte Carlo Markov Chain method. The show that most extreme (lowest temperature) occurs during spell. Reliability evaluations indicate both more likely be affected by spell than wave. Results this can benchmark for wave/cold characterization. developed approach applied characterize other in any location.