Climate Change Research

Climate Change Research

Forecasting Precipitation in the Northern Half of Iran Based on the Output of Selected CMIP6 Models

Document Type : Original Article

Authors
Ali Shahi 1
Bromand Salahi 2
1 Ph.D. Student of Climatology, Department of Physical Geography, Faculty of Social Sciences, University of Mohaghegh Ardabili, Ardabil, Iran
2 Professor of Climatology, Department of Physical Geography, Faculty of Social Sciences, University of Mohaghegh Ardabili, Ardabil, Iran
10.30488/ccr.2025.522854.1284
Abstract
This study aimed to forecast precipitation at 32 synoptic stations in the northern half of Iran in the next three decades. For this purpose, data from 5 AOGCM models, namely MPI-ESM1-2-HR, INM-CM5-0, CMCC-CM2-SR5, BCC-CSM2-MR, and EC-EARTH3-CC, from the CMIP6 series of models were used under 2 scenarios: SSP2-4.5 (moderate) and SSP5-8.5 (pessimistic). The observation period was 1985-2014 and the future period was 2030-2059. The raw precipitation output was downscaled by CMHyd software. The performance of the models was evaluated by calculating the KGE statistic measure and the Taylor diagram was used to select the appropriate downscaling method among Linear Scaling, Power transformation, and Distribution mapping methods. In order to reduce the uncertainty with the weighted averaging method (based on rank), the ensemble model was calculated. The calculations showed that the generated ensemble model has better performance than the individual models. The maximum decrease in precipitation on an annual scale in the future period will occur at Jolfa station with an approximate value of 40% in the average scenario, and the largest increase in precipitation will occur at Sahand station with an increase of 14% in the future period in the pessimistic scenario. The research findings indicate that the maximum, average, and minimum values ​​of the KGE statistical index for the emsemble model compared to the precipitation values ​​of the stations in the study area were 0.1, 0.05, and zero, respectively. The results showed that on an annual time scale, under the average scenario, 78% of the stations will experience a decrease in precipitation, while under the pessimistic scenario, 75% of the studied meteorological stations will have an increase in precipitation. According to the present study, 56% of the studied stations had increasing annual precipitation changes under the SSP585 scenario and decreasing under the SSP245 scenario
Keywords
Climate Change
Emsemble
Modeling
Iran

Subjects

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