Probabilistic projection of extreme precipitation changes over Iran by the CMIP6 multi-model ensemble

Abstract

Based on the historical (period of 1990–2014) spatial and temporal ranking, a future projection of four extreme precipitation indices over Iran is conducted. A multi-model ensemble approach and a rank-based weighting method with ten models from the CMIP6 dataset are used for this projection. The weight of each model is calculated based on its historical simulation skill, and weighted models are employed for future projections across three periods (2026–2050, 2051–2075, and 2076–2100), under four Shared Socioeconomic Pathway (SSP) scenarios (SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5). The results show that an increase in total extreme precipitation (R95p) and the absolute intensity of extreme precipitation (AEPI) in Iran is almost certain in all periods, under all scenarios. The maximum increase of the R95p index is 10%, and the probability of its increase in all periods and scenarios (except for SSP1-2.6 scenario in the 2076–2100 period) exceeds 50%. This probability of increase is particularly high in the first period, ranging from 70 to 90%. In all periods and scenarios, the median of the number of days with extreme precipitation (R95d) is close to zero or negative. This index exhibits a decrease compared to the historical period, with a probability of over 60%, except for the 2026–2050 period under SSP1-2.6 and SSP5-8.5 scenarios. Furthermore, the probability of an increase in the AEPI compared to the historical period is more than 75%. This study finds no significant increase or decrease in the fraction of total rainfall from events exceeding the extreme precipitation threshold (R95pT).