Management of Natural Ecosystems

Management of Natural Ecosystems

Evaluation of future temperature and precipitation changes by downscaling general circulation models(A case study of selected synoptic stations on the southern coasts of Iran)

Document Type : Original Article

Authors
Fatemeh Parakandeh Shahrezaei 1
Seyed Hassan Alavinia 2
Ebrahim omidvar 3
1 M.Sc. in Watershed Management, Department of Nature Engineering, Faculty of Natural Resources and Earth Sciences, University of Kashan, Kashan, Iran.
2 Assistant Professor, Department of Nature Engineering, Faculty of Natural Resources and Earth Sciences, University of Kashan, Kashan, Iran.
3 Associate Professor, Department of Nature Engineering, Faculty of Natural Resources and Earth Sciences, University of Kashan, Kashan, Iran.
10.22034/emj.2024.2025835.1056
Abstract
Natural resources and the environment are the foundation of life and human activities and other creatures, closely intertwined with them. In recent decades, the Earth has been significantly affected by the impacts of global warming and climate change and the country of Iran has not been exempted from this rule. as this phenomenon directly affects environmental, economic-social activities and human health. General circulation models are suitable tools for monitoring future climate change events, but due to their large spatial scale, they require downscaling. This study examined the status of climate variables such as precipitation and average temperature at five synoptic stations on the southern coasts of the country. The basic statistical periodconsidered from 1985 to 2015, and four climate scenarios from the sixth IPCC report were simulated using the MPI-ESM1.2-HR model for the statistical period2023-2043 through downscaling SDSM modeling. The results show an increase in temperature ranging from 1.64% to 8.9% compared to the base period under all four scenarios at all stations. Meanwhile, precipitation is decreasing at some stations under certain SSP scenarios and increasing at others. An increase of up to 140% in Bushehr station and a decrease of more than 10% in Kish station are expected. Estimating, predicting, and monitoring climate change occurrences in different time frames and according to the updated IPCC reports is essential to assist decision-makers and policymakers in taking action to reduce greenhouse gas emissions and adapt to this leading phenomenon.
Keywords
Climate change
CMIP
SSP
simulation
climate parameters
Subjects
آبکار، ع.، حبیب نژاد، م.، سلیمانی، ک.، و نقوی، ه. (1392). بررسی میزان کارایی مدل SDSM در شبیه سازی شاخص‌های دمایی در مناطق خشک و نیمه خشک. آبیاری و آب ایران، (2)4، 17-1.
زرین، آ.، و صالح آبادی، ن. (1398). پیش آگاهی مخاطره خشکسالی در تهران بر اساس برونداد مدل های CMIP6. ششمین کنفرانس منطقه‌ای تغییر اقلیم، تهران، آبان 1398، 173-157.
مساح بوانی، ع.ر.، و مرید، س. (1384). اثرات تغییر اقلیم بر جریان رودخانه زاینده رود اصفهان. علوم آب و خاک، (4)9، 28-17.
Abbas, A., Ullah, S., Ullah, W., Waseem, M., Dou, X., Zhao, C., Karim, A., Zhu, J., Hagan, D.F.T., Bhatti, A.S. and Ali, G. (2022). Evaluation and projection of precipitation in Pakistan using the Coupled Model Intercomparison Project Phase 6 model simulations. International Journal of Climatology, 42(13), 6665-6684.
Abdulla, F. (2020). 21st century climate change projections of precipitation and temperature in Jordan. Procedia Manufacturing, 44, 197-204.
Ali, S.R., N Khan, J., U Din Dar, M., Bhat, S.A., Fazil, S.M., Shah, M., and Mehraj, I. (2018). Modeling Climate Change Projections for Ferozpur Sub-catchment of Jhelum Sub-basin of Kashmir Valley.International Journal of Environment and Climate Change, 8(1), 39-52.
Araya-Osses, D., Casanueva, A., Román-Figueroa, C., Uribe, J.M., and Paneque, M. (2020). Climate change projections of temperature and precipitation in Chile based on statistical downscaling. Climate Dynamics, 54, 4309-4330.
Baghanam, A.H., Eslahi, M., Sheikhbabaei, A., and Seifi, A.J. (2020). Assessing the impact of climate change over the northwest of Iran: an overview of statistical downscaling methods. Theoretical and Applied Climatology, 141(3), 1135-1150.
Banze, F., Guo, J., and Xiaotao, S. (2018). Impact of climate change on precipitation in Zambeze River Basin in Southern Africa. Nature Environment and Pollution Technology, 17(4), 1093-1103.
Beck, S. and Mahony, M. (2018). The IPCC and the new map of science and politics. Wiley Interdisciplinary Reviews: Climate Change, 9(6), e547.
Bock, L., Lauer, A., Schlund, M., Barreiro, M., Bellouin, N., Jones, C., Meehl, G., Predoi, V., Roberts, M., and Eyring, V. (2020). Quantifying progress across different CMIP phases with the ESMValTool. Journal of Geophysical Research: Atmospheres, 125(21), e2019JD032321.
Camici, S., Palazzi, E., Pieri, A., Brocca, L., Moramarco, T., and Provenzale, A. (2015). Comparison between dynamical and stochastic downscaling methods in central Italy. Paper presented at the EGU General Assembly Conference Abstracts.
Dixon, K.W., Lanzante, J.R., Nath, M.J., Hayhoe, K., Stoner, A., Radhakrishnan, A., V. Balaji, and Carlos F. Gaitán., C. F. (2016). Evaluating the stationarity assumption in statistically downscaled climate projections: is past performance an indicator of future results? Climatic Change, 135, 395-408.
Eyring, V., Bony, S., Meehl, G. A., Senior, C. A., Stevens, B., Stouffer, R.J., and Taylor, K.E. (2016). Overview of the Coupled Model Intercomparison Project Phase 6 (CMIP6) experimental design and organization. Geoscientific Model Development, 9(5), 1937-1958.
Fallah, B., Sodoudi, S., Russo, E., Kirchner, I., and Cubasch, U. (2017). Towards modeling the regional rainfall changes over Iran due to the climate forcing of the past 6000 years. Quaternary International, 429, 119-128.
Fenta Mekonnen, D., and Disse, M. (2018). Analyzing the future climate change of Upper Blue Nile River basin using statistical downscaling techniques. Hydrology and Earth System Sciences, 22(4), 2391-2408.
Feyissa, G., Zeleke, G., Bewket, W., and Gebremariam, E. (2018). Downscaling of future temperature and precipitation extremes in Addis Ababa under climate change. Climate, 6(3), 58.
Fischer, E.M., and Knutti, R. (2016). Observed heavy precipitation increase confirms theory and early models. Nature Climate Change, 6(11), 986-991.
Hamlet, A.F., Byun, K., Robeson, S.M., Widhalm, M., and Baldwin, M. (2020). Impacts of climate change on the state of Indiana: ensemble future projections based on statistical downscaling. Climatic Change, 163, 1881-1895.
Heydarizad, M., Raeisi, E., Sori, R., and Gimeno, L. (2018). The identification of Iran’s moisture sources using a Lagrangian particle dispersion model. Atmosphere, 9(10), 408.
Heydarizad, M., Raeisi, E., Sorí, R., and Gimeno, L. (2019). Developing meteoric water lines for Iran based on air masses and moisture sources. Water, 11(11), 2359.
Heydarizad, M., Raeisi, E., Sori, R., Gimeno, L., and Nieto, R. (2018). The role of moisture sources and climatic teleconnections in northeastern and south-central Iran’s hydro-climatology. Water, 10(11), 1550.
IPCC, Climate Change. (2013). The physical science basis.
Ledley, T.S., Sundquist, E.T., Schwartz, S.E., Hall, D.K., Fellows, J.D. and Killeen, T.L. (1999). Climate change and greenhouse gases. Eos, Transactions American Geophysical Union, 80(39), 453-458.
Lovino, M.A., Pierrestegui, M.J., Müller, O.V., Berbery, E.H., Müller, G.V., and Pasten, M. (2021). Evaluation of historical CMIP6 model simulations and future projections of temperature and precipitation in Paraguay. Climatic Change, 164, 1-24.
Masson-Delmotte, V., Zhai, P., Pirani, A., Connors, S.L., Péan, C., Berger, S., Caud, N., Chen, Y., Goldfarb, L., Gomis, M.I. and Huang, M. (2021). Climate change 2021: the physical science basis. Contribution of working group I to the sixth assessment report of the intergovernmental panel on climate change, 2(1), 2391.
Meenu, R., Rehana, S., and Mujumdar, P.P. (2013). Assessment of hydrologic impacts of climate change in Tunga–Bhadra river basin, India with HEC‐HMS and SDSM. Hydrological processes, 27(11), 1572-1589.
Mesgari, E., Hosseini, S.A., Hemmesy, M.S., Houshyar, M., and Partoo, L.G. (2022). Assessment of CMIP6 models’ performances and projection of precipitation based on SSP scenarios over the MENAP region. Journal of Water and Climate Change, 13(10), 3607-3619.
Mesgari, E., Hosseini, S.A., Houshyar, M., Kaseri, M., and Safarpour, F. (2023). Future projection of early fall and late spring frosts based on EC-earth models and shared socioeconomic pathways (SSPs) scenarios over Iran plateau. Natural Hazards, 119(3), 1421-1435.
Molina, O.D., and Bernhofer, C. (2019). Projected climate changes in four different regions in Colombia. Environmental Systems Research, 8, 1-11.
Munawar, S., Rahman, G., Moazzam, M.F.U., Miandad, M., Ullah, K., Al-Ansari, N., and Linh, N.T.T. (2022). Future climate projections using SDSM and LARS-WG downscaling methods for CMIP5 GCMs over the transboundary Jhelum River Basin of the Himalayas Region. Atmosphere, 13(6), 898.
O’Neill, B.C., Kriegler, E., Riahi, K., Ebi, K.L., Hallegatte, S., Carter, T.R., Mathur, R., and Van Vuuren, D.P. (2014). A new scenario framework for climate change research: the concept of shared socioeconomic pathways. Climatic Change, 122, 387-400.
Pachauri, R.K., Allen, M.R., Barros, V.R., Broome, J., Cramer, W., Christ, R., Church, J.A., Clarke, L., Dahe, Q., Dasgupta, P. and Dubash, N.K. (2014). Climate change 2014: synthesis report. Contribution of Working Groups I, II and III to the fifth assessment report of the Intergovernmental Panel on Climate Change: Ipcc.
Peng, S., Wang, C., Li, Z., Mihara, K., Kuramochi, K., Toma, Y., and Hatano, R. (2023). Climate change multi-model projections in CMIP6 scenarios in Central Hokkaido, Japan. Scientific Reports, 13(1), 230.
Rajão, R., Soares-Filho, B., Nunes, F., Börner, J., Machado, L., Assis, D., Oliveira, A., Pinto, L., Ribeiro, V., Rausch, L. and Gibbs, H. (2020). The rotten apples of Brazil's agribusiness. Science, 369(6501), 246-248.
Sabziparvar, A., Movahedi, S., Asakereh, H., Maryanaji, Z., and Masoodian, S. (2015). Geographical factors affecting variability of precipitation regime in Iran. Theoretical and Applied Climatology, 120, 367-376.
Salman, S.A., Hamed, M.M., Shahid, S., Ahmed, K., Sharafati, A., Asaduzzaman, M., Ziarh, G.F., Ismail, T., Wang, X.J., and Dewan, A. (2022). Projecting spatiotemporal changes of precipitation and temperature in Iraq for different shared socioeconomic pathways with selected Coupled Model Intercomparison Project Phase 6. International Journal of Climatology. 42(16), 9032-9050.
Shukla, K.K., and Attada, R. (2023). CMIP6 models informed summer human thermal discomfort conditions in Indian regional hotspot. Scientific Reports, 13(1), 12549.
Sodoudi, S., Noorian, A., Geb, M., and Reimer, E. (2010). Daily precipitation forecast of ECMWF verified over Iran. Theoretical and Applied Climatology, 99, 39-51.
Solomon, S., Qin, D., Manning, M., Chen, Z., Marquis, M., Averyt, K.B., Tignor, M. and Miller, H.L. (2007). Summary for policymakers. Climate change, 1-18.
Tahir, T., Hashim, A., and Yusof, K. (2018). Statistical downscaling of rainfall under transitional climate in Limbang River Basin by using SDSM. Paper presented at the IOP conference series: earth and environmental science.
Talebmorad, H., Abedi-Koupai, J., Eslamian, S., Mousavi, S.F., Akhavan, S., Ostad-Ali-Askari, K., and Singh, V.P. (2021). Evaluation of the impact of climate change on reference crop evapotranspiration in Hamedan-Bahar plain. International Journal of Hydrology Science and Technology, 11(3), 333-347.
Tebaldi, C., and O’Neill, B.C. (2020). Climate scenarios and their relevance and implications for impact studies. In Climate Extremes and Their Implications for Impact and Risk Assessment, 11-29.
Wilby, R.L., Dawson, C.W., andand Barrow, E.M. (2002). SDSM-a decision support tool for the assessment of regional climate change impacts. Environmental Modelling and Software, 17(2), 145-157.

  • Receive Date 02 April 2024
  • Revise Date 07 June 2024
  • Accept Date 09 June 2024