Extreme temperature events have increased in Iran in recent decades. In this research, we evaluate the performance of CMIP6-DCPP individual models and a multi-model ensemble (MME) from CMIP6-DCPP against observational data in Iran. We used the delta change factor (DCF) and the independence weighted mean (IWM) methods to correct the bias of individual models and generate the MME. Eighteen temperature indices recommended by ETCCDI were used to predict extreme temperatures in the near term by comparing the hindcast (1981–2019) and forecast (2021–2028) periods. The result shows that DCPP-MME performed well in simulating temperature over most parts of Iran. Positive anomalies in mean, minimum, and maximum temperatures are obvious in Iran in the next decade, which is amplified by the elevation. As a key result, the minimum temperature will increase at a higher rate than the maximum temperature, which will make a negative diurnal temperature range anomaly in most regions in the near-term period. The frequency and intensity of warm (cold) extremes would increase (decrease) in the upcoming years. Therefore, in mountainous and high-latitude regions of Iran, the coldest days and nights are getting warmer compared to the hottest days and nights. In addition, ice days and frost days decrease considerably by almost 15 and 11 days in the north of Iran, respectively. Tropical nights and summer days will increase in all regions, with their maxima in central and eastern arid regions. Also, warm spell duration with an increase of 14 days is very noticeable in the forecast period.

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