Projection of Future Drought Trends in Iran Using the CMIP6 Multi-Model Ensemble

Ahadi, Mahyar; Zeynali, Batol; Salahi, Bromand; Shoja, Faeze; Fazl Kazemi, Amin; Babaeian, Iman; Kohi, Mansoureh

doi:10.22111/jneh.2025.50138.2075

Projection of Future Drought Trends in Iran Using the CMIP6 Multi-Model Ensemble

Document Type : Research Article

Authors

¹ PhD Student of Climatology, Faculty of Social Sciences, University of Mohaghegh Ardabili. Ardabil, Iran

² Professor of Climatology, Faculty of Social Sciences, University of Mohaghegh Ardabili, Ardabil, Iran

³ Professor of Climatology, Department of Physical Geography, University of Mohaghegh Ardabili, Iran

⁴ Associate Professor in Climatology, Department of Physical Geography, University of Tehran, Iran

⁵ PhD Student of Meteorology, Department of Space Physics, Institute of Geophysics, University of Tehran, Tehran, Iran

⁶ Professor of Climatology, Atmospheric Science and Meteorological Research Centre, Climate Research Institute, Mashhad, Iran

10.22111/jneh.2025.50138.2075

Abstract

Ongoing global warming has caused unprecedented changes in climate systems, leading to an increase in the intensity and frequency of weather and climate extremes. This study uses the sixth phase of the Coupled Model Intercomparison Project (CMIP6) data to investigate projected changes in drought events over Iran under two Shared Socioeconomic Pathway emission scenarios. The observational period of 1985-2014 and the next three 25-year periods, are the near future 2020-2026, 2075-2051 and far future 2100-2076, were considered as study periods. The standard precipitation evapotranspiration index (SPEI) was used to estimate drought over a 12-month timescale. According to the results, under SSP2-4.5, the average precipitation of the country increases by 20%, 12%, and 16% in the near-, medium-, and far-future periods, respectively, and by 15%, 13%, and 21% in the pessimistic scenario. In terms of temperature, the most severe increase is related to the pessimistic scenario and in the far future at 3.7 degrees Celsius. The average 12-month SPEI drought index shortly under the SSP2-4.5 and SSP5-8.5 scenarios will be equal to 0.53 and 0.80, respectively, in the medium future, -0.1 and zero, and in the far future, -0.45 and -0.84. According to the results, by applying the pessimistic scenario, the severity of droughts in the near and medium future will decrease by 96% and 49%, respectively, and in the future, it will increase by 300%. However, if the SSP2-4.5 scenario occurs, there will be a 61% decrease soon and an increase of 64% and 234% in the medium and long term, respectively. Examining the trend of average temperature and drought severity using the Mann-Kendall test indicated an increase in average temperature and drought severity at 100% of the stations with a confidence level of 99%.

Keywords

Main Subjects

Climate-Change

References

REFERENCES

References (in Persian)

Dastourani, M., Hoseinabadi, S., Yaghoobzadeh, M., & Forouzan Mehr, M. (2024). The effect of climate change on meteorological drought using the data of the Sixth Climate Change Report (Case study: Shiraz city). Water Resources Engineering, 17(61), 13-27. doi: 10.30495/wej.2024.30610.2360. [In Persian]

Khadempour, F., Amirabadizadeh, M. and Falamarzi, Y. (2024). Streamflow forecasting under the impacts of climate change based on the combined output of CMIP6 models (Case study: Dez Dam). Integrated Watershed Management. doi: 10.22034/iwm.2024.2022522.1133. [In Persian].

Mohammadi, N. and Hedjazizadeh, Z. (2024). The effects of climate change on increasing the risk of drought in Tehran using CMIP6 scenarios. Water and Soil Management and Modelling, 4(2), 133-148. doi: 10.22098/mmws.2023.12563.1252. [In Persian]

References (in English)

Ayugi, B., Zhihong, J., Zhu, H., Ngoma, H., Babaousmail, H., Rizwan, K., & Dike, V. (2021). Comparison of CMIP6 and CMIP5 models in simulating mean and extreme precipitation over East Africa. International Journal of Climatology, 41(15), 6474-6496.

Dai, A. (2013). Increasing drought under global warming in observations and models. Nature Climate Change, 3(1), 52-58.

FAO, F. (2018). The impact of disasters and crises on agriculture and food security. Report.

Hao, Z., Xia, Y., Luo, L., Singh, V. P., Ouyang, W., & Hao, F. (2017). Toward a categorical drought prediction system based on US Drought Monitor (USDM) and climate forecast. Journal of Hydrology, 551, 300-305.

Thornthwaite, C. W. (1948). An approach toward a rational classification of climate. Geographical Review, 38(1), 55-94.

Vicente-Serrano, S. M., Beguería, S., & López-Moreno, J. I. (2010). A multiscalar drought index sensitive to global warming: the standardised precipitation evapotranspiration index. Journal of Climate, 23(7), 1696-1718.

Wang, T., Tu, X., Singh, V. P., Chen, X., & Lin, K. (2021). Global data assessment and analysis of drought characteristics based on CMIP6. Journal of Hydrology, 596, 126091.

Yang, X., Zheng, W., Ren, L., Zhang, M., Wang, Y., Liu, Y., ... & Jiang, S. (2018). Potential impact of climate change on the future streamflow of the Yellow River Basin based on CMIP5 data. Proceedings of the International Association of Hydrological Sciences, 376, 97-104.

Yu, M., Li, Q., Hayes, M.J., Svoboda, M.D., Heim, R.R., 2014. Are droughts becoming more frequent or severe in China based on the standardised precipitation evapotranspiration index: 1951–2010? Int. J. Climatol. 34 (3), 545–558.

Zeng, J., Li, J., Lu, X., Wei, Z., Shangguan, W., Zhang, S., ... & Zhang, S. (2022). Assessment of global meteorological, hydrological and agricultural drought under future warming based on CMIP6. Atmospheric and Oceanic Science Letters, 15(1), 100143.

Zhao, F., Wu, Y., Yin, X., Sun, K., Ma, S., Zhang, S., ... & Chen, J. (2022). Projected changes in population exposure to drought in China under CMIP6 forcing scenarios. Atmospheric Environment, 282, 119162.