A Study of Climate Change in Iran Based on Shared Socioeconomic Pathways Scenarios

Document Type : Research Paper

Authors

1 Assistant Professor of Climatology, Department of Climatology, Faculty of Natural Resources, University of Kurdistan, Sanandaj, Iran

2 Associate professor, Department of Agricultural Economics, Faculty of Agriculture & Natural Resources, Ardakan University, Ardakan, Iran

10.22034/gp.2024.63432.3304

Abstract

The aim of the present study is to estimate climate change in Iran based on the CMIP6 report, using a satellite data approach and climatic variables (minimum temperature, maximum temperature, and precipitation) up to the year 2100. The tools employed in this study include innovative algorithmic methods, coding techniques, and NASA datasets. To assess and predict the aforementioned climatic variables, the intermediate scenario (SSP2-4.5) and the worst-case scenario (SSP5-8.5) of the Canadian CanESM5 model, which is based on greenhouse gas emissions (Shared Socioeconomic Pathways), were used. Additionally, for a better analysis, evaluation, and comparison of future climate changes in Iran, the 80-year study period was divided into two periods: the near future (2021–2060) and the far future (2061–2100). The results showed that for the first 40-year period (2021–2060), based on the SSP2-4.5 scenario, the changes in climatic variables, minimum temperature of 1.91 °C, maximum temperature of 1.41 °C, and maximum precipitation of 15.22 mm, were predicted. Moreover, for the second 40-year period (2061–2100), based on the SSP2-4.5 scenario, the changes in climatic variables, minimum temperature of 1.71 °C, maximum temperature of 1.17 °C, and maximum precipitation of 22.25 mm, were predicted. Based on the findings obtained from CMIP6 and using the SSP2-4.5 and SSP5-8.5 scenarios in predicting climatic variables, the results indicated that the minimum and maximum temperatures exhibited an increasing trend, and this increase will be greater in the SSP5-8.5 scenario compared to the SSP2-4.5 scenario. Additionally, the results showed that the amount of precipitation based on the SSP2-4.5 scenario in the near future period will be lower than in the far future period, and the amount of precipitation in the SSP5-8.5 scenario will have a decreasing trend compared to the SSP2-4.5 scenario.

Keywords

Main Subjects


هدف پژوهش حاضر برآورد تغییر اقلیم ایران براساس گزارش CMIP6 با رویکرد داده‌های ماهواره‌ای با استفاده از عناصر اقلیمی (کمینه دما، بیشینه دما و بارش) تا سال 2100 بود. ابزارهای مورد استفاده در این پژوهش شامل روش‌های نوآورانه الگوریتم، کدنویسی و داده‌های ناسا بود. به منظور ارزیابی و پیش‌بینی عناصر اقلیمی مذکور از دو سناریوی حدوسط (SSP2_4.5) و سناریوی خیلی بدبینانه (SSP5_8.5) مدل CanESM5 کانادا مبتنی بر انتشار گازهای گلخانه‌ای که به عنوان مسیرهای اجتماعی - اقتصادی مشترک (SSPs) بود، استفاده شد. برای تحلیل، بررسی و مقایسه بهتر تغییرات اقلیمی آینده ایران، بازه زمانی مورد مطالعه 80 ساله، به دو دوره آینده نزدیک (2060- 2021) و آینده دور (2100- 2061) تقسیم شد. نتایج نشان داد که در دوره 40 ساله اول (2060-2021) براساس سناریوی SSP2_4.5 تغییر روند عناصر اقلیمی به صورت کمینه دمای 91/1 سانتی‌گراد، بیشینه دمای 41/1 سانتی‌گراد و مقدار بیشینه بارش 22/15 میلی‌متر برای سال‌های آتی گزارش شد.  هم‌چنین برای دوره 40 ساله دوم (2100- 2061) براساس سناریوی SSP2_4.5 تغییر روند عناصر اقلیمی با کمینه دمای 71/1 سانتی‌گراد، بیشینه دمای 17/1 سانتی‌گراد و مقدار بیشینه بارش 25/22 میلی‌متر برای سال‌های آینده پیش‌بینی شدند. با توجه به یافته‌های به دست آمده از CMIP6 و به کمک سناریوی‌های SSP2_4.5 و SSP5_8.5 در پیش‌بینی عناصر اقلیمی، نتایج نشان دادند که مقدار عناصر اقلیمی کمینه و بیشینه دما، با مقیاس افزایشی همراه بود و این افزایش در سناریوی SSP5_8.5 نسبت به سناریوی SSP2_4.5 بیش‌تر بود، هم‌چنین پیش‌بینی مقدار پارامتر اقلیمی بارش براساس سناریوی SSP2_4.5 در دوره آینده نزدیک (2060- 2021)  نسبت به دوره آینده دور (2100- 2061) کم‌تر خواهد بود و مقدار بارش در سناریوی SSP5_8.5 به نسبت سناریوی SSP2_4.5 روند کاهشی خواهد داشت.

Abbasi, F., Kouhi, M., Javanshiri, Z., Malbousi, S., Habibi Nokhandan, M., Babaeian, I., & Falamarzi, Y. (2020). Climate change detection update over Iran during 1958-2017. Journal of Climate Research, 1399(42), 137-153. (in Persian)
Ahmadabadi A, Sedighifar Z. (2018). Prediction of Climate Change Induced Hydrogeomorphology by using SDSM in CAN Watershed. Jgs; 18 (51):103-114. URL: http://jgs.khu.ac.ir/article-1-2697-fa.html. (in Persian)
Akbary, M., & sayad, V. (2021). Analysis of climate change studies in Iran. Physical Geography Research, 53(1), 37-74. doi: 10.22059/jphgr.2021.301111.1007528. (in Persian)
Alizadeh, E., mousavi, H., Yarahmadi, J., & Faraji, A. (2020). Assessment the Impact of Climate Change on Precipitation in Non-Observed data using the CCT Toolkit Case study: Daryan sub basin. Journal of Geography and Planning, 24(73), 305-323. doi: 10.22034/gp.2020.10790. (in Persian)
Asakereh, H., Masoodian, S. A., & Tarkarani, F. (2021). A Discrimination of Roles of Internal and External Factors on the Decadal Variation of Annual Precipitation in Iran over Recent Four Decades (1975-2016). Physical Geography Research, 53(1), 91-107. doi: 10.22059/jphgr.2021.304776. 1007529. (in Persian)
Azizi, H. R., Ebrahimi, H., Mohamadvali samani, H., & Khaki, V. (2020). Assessment the Intensity of the Effect of Climate Change on Groundwater Resources of Varamin plain using NISTOR index. Iran-Water Resources Research, 16(3), 172-187. (in Persian)
Baccini, M., Kosatsky, T & Biggeri, A. (2013). Impact of Summer Heat on Urban Population Mortality in Europe during the 1990s: an Evaluation of Years of Life Lost Adjusted for Harvesting, PLoS ONE, 8, e69638. doi:10.1371/journal.pone.0069638
Boonman, C.C.F., Huijbregts, M.A.J., López, A.B., Schipper A.M., Thuiller, W., Santini, L. (2021). Trait-based projections of climate change effects on global biome distributions, Diversity and Distributions, 28 (1). https://doi.org/10.1111/ddi.13431
Bukovsky, M. S., Gao, J., Mearns, L. O., & O'Neill, B. C. (2021). SSP-based land-use change scenarios: A critical uncertainty in future regional climate change projections. Earth's Future, 9 (3). https://doi.org/10.1029/2020EF001782
Castro, A.Q.; Yaneth, A. B.T.; Erick, R.B.; Juan G.L.; Jesús, G.R.P. (2022). Modeling the effect of climate change scenarios on water quality for tropical reservoirs, Journal of Environmental Management, 322: 116137. https://doi.org/10.1016/j.jenvman.2022.116137.
Cicerone, R., & Nurse, P. (2014) Climate Change Evidence & Causes, An overview from the Royal Society and the US National Academy of Sciences.
Collins, M.; Barreiro, M.; Frölicher, T.; Kang S.M.; Ashok, K.; Roxy M.K.; Singh, D.; Tedeschi, R.G.; Wang, G.; Wilcox, L & Wu, B. (2020). Frontiers in Climate Predictions and Projections, Journal frontiers in Climate, 2. https://doi.org/10.3389/fclim.2020.571245
Erler, A.R., Frey, S.K., Khader, O., D'Orgeville, M., Park, Y.J., Hwang, H.T., Lapen, D.R., Peltier, W.R & Sudicky, E. A. (2019). Evaluating climate change impacts on soil moisture and groundwater resources within a lake‐affected region, Water Resources Research, 55 (10). https://doi.org/10.1029/2018WR023822
Fahiminezhad E, Baaghide M O, Babaeian I, Entezari A. (2019). Simulation of the effect of global warming on the mean and extreme events of some hydrochemical variables in Shandiz catchment basin Case study: The Case of the general circulation model CanESM2. Journal of Spatial Analysis Environmental Hazards; 6(3):27-48. http://jsaeh.khu.ac.ir/article-1-2788-fa.html. (in Persian)
Farajzadeh, Manoochehr, and Ghasemifar, Elham (2019). Fundamentals of Climate Change and Its Consequences. Tehran: Nashre entekhab, p. 435. (in Persian)
Feng, A & Chao, Q. (2020). An Overview of Assessment Methods and Analysis for Climate Change Risk in China. Phys, Chem. Earth, Parts A/B/C, 117: 102861. doi:10.1016/j.pce.2020.102861
Feyissa, G.; Zeleke, G.; Bewket, W & Ephrem, G. (2018). Downscaling of Future Temperature and Precipitation Extremes in Addis Ababa under Climate Change, Climate, 6 (58). https://doi.org/10.3390/cli6030058
Gomiero, A., Bellerby, R. G. J., Manca Z.M., Babbini, L & Viarengo, A. (2018). Biological Responses of Two marine Organisms of Ecological Relevance to On-Going Ocean Acidification and Global Warming, Environ. Pollut, 236: 60–70. doi:10.1016/j.envpol.2018.01.063
Hamidian Pour, M., Fallah Ghalhari, G., & Reza Alimoradi, M. (2021). Evaluating the Efficiency of the SDSM Model in Investigating the Consequences of Climate Change for Different Climate Zones in Iran. Climate Change Research, 2(5), 1-14. doi: 10.30488/ccr.2020.248188.1023. (in Persian)
Hejazizadeh Z, Zarei S. (2023). Investigation of Changes of Temperature and Rainfall Indicators in Kurdistan Province Based on Radiation Injection Scenarios (RCP). jgs; 23 (69), 1. http://jgs.khu.ac.ir/article-1-3015-fa.html. (in Persian)
Huang, J., Li, Y. Fu, C. Chen, F. Fu, Q. Dai, A. Shinoda, M. Ma, Z. Guo, W. Li, Z. Zhang, L. Liu, Y. Yu, H. He, Y. Xie, Y. Guan, X. Ji, M. Lin, L. Wang, S. Yan, H & Wang, G. (2017). Dryland climate change: Recent progress and challenges, Reviews of geophysics, 55 (3). https://doi.org/10. 1002/2016RG000550
Huang, Y.F.; Jong, T.A.; Yong, J.T.; Mirzaei, M.; Mohd, Z.M.A. (2016). Drought Forecasting Using SPI and EDI under RCP-8.5 Climate Change Scenarios for Langat River Basin, Malaysia, Procedia Engineering, 154: 710-717. https://doi.org/10.1016/j.proeng.2016.07.573.
IPCC, (2021) Summary for Policymakers. In: Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change [Masson-Delmotte, V., P. Zhai, A. Pirani, S.L. Connors, C. Péan, S. Berger, N. Caud, Y. Chen, L. Goldfarb, M.I. Gomis, M. Huang, K. Leitzell, E. Lonnoy, J.B.R. Matthews, T.K. Maycock, T. Waterfield, O. Yelekçi, R. Yu, and B. Zhou (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, pp. 3−32, doi:10.1017/9781009157896.001.
IPCC. (2013). Summary for Policymakers, Climate Change 2013: The Physical Science Basis, Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change In: Stocker TF, Qin D, Plattner G. K., Tignor M., Allen SK et al. (eds.), Cambridge University Press, Cambridge, United Kingdom and new York, NY, USA.
IPCC-TGICA. (2007). General Guidelines on the Use of Scenario Data for Climate Impact and Adaptation Assessment. Version 2. Prepared by T.R. Carter on behalf of the Intergovernmental Panel on Climate Change, Task Group on Data and Scenario Support for Impact and Climate Assessment, 66 pp.
Isobe, M. (2013). Impact of Global Warming on Coastal Structures in Shallow, Water. Ocean Eng, 71. doi:10.1016/j.oceaneng.2012.12.032
Jahanbakhsh Asl, S., Khorshiddoust, A., Alinejad, M. H., & Pourasghr, F. (2016). Impact of Climate Change on Precipitation and Temperature by Taking the Uncertainty of Models and Climate Scenarios (Case Study: Shahrchay Basin in Urmia). Hydrogeomorphology, 3(7), 107-122. (in Persian)
Jiang, C., Shaw, K. S., Upperman, C. R., Blythe, D., Mitchell, C & Murtugudde, R. (2015). Climate Change, Extreme Events and Increased Risk of Salmonellosis in Maryland, USA: Evidence for Coastal Vulnerability, Environ. Int, 83. doi:10.1016/j.envint.2015.06.006
Karimiahmad abad, M., & Nabizadeh, A. (2018). Assessment of climate change impacts on climate parameters of Urmia Lake basin during 2011-2040 years by using LARS-WG model. Journal of Geography and Planning, 22(65), 265-285. (in Persian)
Khayat, A., Amirabadizadeh, M., Pourreza-Bilondi, M., & khozeymehnehad, H. (2020). Study Temperature and Precipitation Parameters under the Effect of Climate Change (Case study: Birjand Plain). Irrigation and Water Engineering, 11(1), 200-210. doi: 10.22125/iwe.2020.114963. (in Persian)
Li, X., Clinton, N., Si, Y., Liao, J., Liang, L & Gong, P. (2015). Projected Impacts of Climate Change on Protected Birds and Nature Reserves in China, Sci. Bull, 60. doi: 10.1007/s11434-015-0892-y
Li, X., Zickfeld, K., Mathesius, S., Kohfeld, K., & Matthews, J.B.R. (2020). Irreversibility of marine climate change impacts under carbon dioxide removal, Geophysical Research Letters, 47 (17). https://doi.org/10.1029/2020GL088507
Lu, S., Bai, X., Zhang, X., Li, W & Tang, Y. (2019). The Impact of Climate Change on the Sustainable Development of Regional Economy, J. Clean. Prod, 233: 1387–1395. doi:10.1016/j.jclepro.2019.06.074
Luo, Q., Li, S., Guo, Y., Han, X & Jaakkola, J. J. K. (2019). A Systematic Review and Meta-Analysis of the Association between Daily Mean Temperature and Mortality in China. Environ. Res, 173. doi:10.1016/j.envres.2019.03.044
Mirakbari, M., Mesbahzadeh, T., Mohseni Saravi, M., Khosravi, H., & Mortezaie Farizhendi, G. (2018). Performance of Series Model CMIP5 in Simulation and Projection of Climatic Variables of Rainfall, Temperature and Wind Speed (Case Study: Yazd). Physical Geography Research, 50(3), 593-609. doi: 10.22059/jphgr.2018.248177.1007156. (in Persian)
Mirshekaran, Y., Kakapour, V., & Zarey, A. (2021). Assess the effect of climate change on precipitation and temperature using AR4 models (Case Study: Gharasoo Basin of Kermanshah province). Climate Change Research, 2(8), 23-34. doi: 10.30488/ccr.2022.319044.1061. (in Persian)
Mirzaei, M., Lawrence, B., & Samani Majd, A. M. (2021). Climate change of ZayandehRood watershed based on IPCC scenarios and Köppen–Geiger classification. Journal of Urban Sustainable Development, 2(5), 23-37. doi: 10.22034/usd.2021.696816. (in Persian)
Mishra, A.K., Singh, V.P & Jain, S. K. (2010). Impact of Global Warming and Climate Change on Social Development, J. Comp. Soc. Welfare, 26. doi: 10.1080/17486831003687626
Mohammadloo, M; Haqizadeh, A; Zeinivand, H and Tahmasibipour, N (2017). Evaluation of climate change on temperature and precipitation trends in Barandozchay watershed, In the West Azerbaijan, using General Circulation Models (GCM). Journal of Geography Space, 16(56), 151-168. http://geographical-space.iau-ahar.ac.ir/article-1-1164-fa.html. (in Persian)
Mohammadpourkhoie, M. M., & Nasseri, M. (2022). Evaluation of Unstationary and Extreme Value Patterns of Precipitation over Iran considering Impacts of Climate Change. Journal of Climate Research, 1401(49), 131-148. (in Persian)
Molodi G, khorani A, moradi A. (2016). Impacts of climate change on heat waves in northern coast of Persian Gulf. Journal of Spatial Analysis Environmental Hazards; 3 (1):1-14. http://jsaeh.khu.ac.ir/article-1-2541-fa.html. (in Persian)
NASA Center for Climate Simulation. (2021). NEX-GDDP-CMIP6: Bias Correction and Spatial Disaggregation (BCSD) Technical Note. Retrieved from https://www.nccs.nasa.gov/sites/default/files/NEX-GDDP-CMIP6-Tech_Note_4.pdf
NASA Goddard Space Flight Center. (2020). NEX-GDDP-CMIP6: NASA Earth Exchange Global Daily Downscaled Projections based on CMIP6 [Dataset]. NASA Earth Exchange. Retrieved August 2, 2025, from https://data.nasa.gov/
Nazarenko, L. S.; Tausnev, N.; Russell, G. L.; Rind, D.; Miller, R. L & Schmidt, G. A. (2022). Future climate change under SSP emission scenarios with GISS-E2.1. Journal of Advances in Modeling Earth Systems, 14 (7): 119-125. https://doi.org/10.1029/2021MS00287
Onozuka, D., Gasparrini, A., Sera, F., Hashizume, M & Honda, Y. (2019). Future Projections of Temperature-Related Excess Out-Of-Hospital Cardiac Arrest under Climate Change Scenarios in Japan, Sci. Total Environ, 682. doi:10.1016/j.scitotenv.2019.05.196
Ozturk, T., Turp, M.T., Türkeş, M & Kurnaz, M. L. (2018). Future Projections of Temperature and Precipitation Climatology for CORDEX-MENA Domain Using RegCM4.4, Atmos. Res, 206. doi:10.1016/j.atmosres.2018.02.009
Pouyanfar, N., Mozafari, G. A., Omidvar, K., & Mazidi, A. (2022). Trend of changes in pistachio plant chilling need and its prediction using SDSM model (Case study: Yazd). Journal of Geography and Planning, 26(80), 60-45. doi: 10.22034/gp.2021.45642.2827. (in Persian)
Rathore, P.; Arijit, R.; Harish, K. (2019). Modelling the vulnerability of Taxus wallichiana to climate change scenarios in South East Asia, Ecological Indicators, 102. https://doi.org/10.1016/j.ecolind.2019.02.020.
Salimi, S.; Martin, B.; Miklas, S. (2021). Response of the peatland carbon dioxide sink function to future climate change scenarios and water level management, Glob Change Biol, 27. https://doi.org/10.1111/gcb.15753
Sarabi, M., Dastorani, M. T., & Zarrin, A. (2020). Investigating Impact of Future Climate Changes on Temperature and Precipitation condition (Case Study: Torogh Dam Watershed, Mashhad). Journal of Meteorology and Atmospheric Science, 3(1), 63-83. doi: 10.22034/jmas.2021.278862.1129. (in Persian)
Sobhani, B & Safarian, V. (2024). Obviousization and estimation of climate change in the coming years of Iran. Journal of Environmental Science Studies, 8(4). Doi: 10.22034/jess.2023.393740.2007. (In persian)
An Overview of CMIP5 and the Experiment Design, Bulletin of the American Meteorological Society (BAMS), 93 (4). https://doi.org/10.1175/BAMS-D-11-00094.1
Thrasher, B., Wang, W., Michaelis, A., Melton, F., Lee, T & Nemani, R. (2022). NASA Global Daily Downscaled Projections, CMIP6. Sci Data, 9: (262). https://doi.org/10.1038/s41597-022-01393-4
Wang, X. L., Feng, Y & Swail, V. R. (2015), Climate change signal and uncertainty in CMIP5-basedprojections of global ocean surface wave heights, J. Geophys. Res. Oceans, 120 (5). https://doi.org/10.1002/2015JC010699
Wang, X.; Hou, X.; Piao, Y.; Feng, A & Li, Y. (2021). Climate Change Projections of Temperature Over the Coastal Area of China Using SimCLIM, Frontiers in Environmental Science, 9: https://doi.org/10.3389/fenvs.2021.782259
Zohrevandi H, Khorshid dost A M, Sari saraf B. (2020). Prediction of Climate Change in Western of Iran using Downscaling of HadCM3 Model under Different Scenarios. Journal of Spatial Analysis Environmental Hazards; 7 (1):49-64. http://jsaeh.khu.ac.ir/article-1-2741-fa.html. (in Persian)