نوع مقاله : مقاله پژوهشی
تازه های تحقیق
ابلاغیان، آ.، آخوندعلی، ع. م.، رادمنش، ف.، زارعی، ح.، 1398، بررسی روند تغییرات دما، بارندگی و رطوبت نسبی در ایران: علوم و مهندسی آبیاری، 42(3)، 197-212.
چمانهفر، س.، موسوی بایگی، م.، بابائیان، ا.، مدرسی، ف.، 1401، پیشنگری شاخصهای حدی بارشی و دمایی در دوره 2100-2026 بر اساس برونداد مدلهای CMIP6 (مطالعه موردی: مشهد): نشریه آبیاری و زهکشی ایران، 16(5)، 963-976.
دارند، م.، 1394، واکاوی وردایی زمانی- مکانی رطوبت جوّی ایرانزمین طی بازه زمانی 2013-1979: پژوهشهای جغرافیای طبیعی، 47(2)، 213-239.
دارند، م.، حمیدی، س.، 1400، شبیهسازی تغییرات دمای ایرانزمین بر پایه سناریوهای مختلف RCP: مخاطرات محیط طبیعی، 10(28)، 85-106.
زرین، آ.، داداشی رودباری، ع.، 1399، پیشنگری چشمانداز بلندمدت دمای آینده ایران مبتنی بر برونداد پروژه مقایسه مدلهای جفتشده فاز ششم (CMIP6): فیزیک زمین و فضا، 46(3)، 583-602.
زرین، آ.، داداشی رودباری، ع.، 1400، پیشنگری دورههای خشک و مرطوب متوالی در ایران مبتنی بر برونداد همادی مدلهای تصحیحشده اریبی CMIP6: فیزیک زمین و فضا، 47(3)، 561-578.
زرین، آ.، داداشی رودباری، ع.، کدخدا، ا.، 1401، پیشنگری خشکسالی تحت سناریوهای SSP تا پایان قرن بیستویکم، مطالعه موردی: حوضه دریاچه ارومیه: تحقیقات آب و خاک ایران، 53(7)، 1499-1516.
زرین، آ.، داداشی رودباری، ع.، 1401، بررسی مدلهای CMIP6 در برآورد دمای ایران با تأکید بر حساسیت اقلیم ترازمند (ECS) و پاسخ اقلیم گذرا (TCR): مجله ژئوفیزیک ایران، 17(1)، 39-56.
سرابی، م.، دستورانی، م.، زرین، آ.، 1399، بررسی تأثیر تغییرات اقلیمی آینده بر وضعیت دما و بارش (مطالعه موردی: حوضه آبخیز سد طرق مشهد): نشریه هواشناسی و علوم جوّ، 3(1)، 63-83.
علیزاده چوبری، ا.، نجفی، م. س.، 1396، روند تغییرات دمای هوا و بارش در مناطق مختلف ایران: فیزیک زمین و فضا، 43(3)، 569-584.
کدخدا، ا.، امیدوار،ک.، زرین، آ.، مزیدی، ا.، داداشی رودباری، ع.، 1402، پیشنگری تنش گرمایی در ایران بر اساس برونداد چندمدلی همادی CMIP6: مجله ژئوفیزیک ایران، 17(2)، 157-173.
مسعودیان، س. ا.، 1384، بررسی روند دمای ایران در نیم سده گذشته: پژوهشهای جغرافیایی، 54، 29-45.
Ahmadi, H., Rostami, N., and Dadashi-Roudbari, A., 2023, The impact of climate change on snowfall in Iran Basins using the satellite-derived snow products and CMIP6 Bias Corrected model: Theoretical and Applied Climatology, 151(1-2), 603-618.
Akinsanola, A. A., Ogunjobi, K. O., Abolude, A. T., and Salack, S., 2021, Projected changes in wind speed and wind energy potential over West Africa in CMIP6 models: Environmental Research Letters, 16(4), 044033.
Almazroui, M., Islam, M. N., Saeed, F., et al., 2021, Projected changes in temperature and precipitation over the United States, Central America, and the Caribbean in CMIP6 GCMs: Earth Systems and Environment, 5, 1-24.
Bai, H., Xiao, D., Wang, B., Liu, D. L., Feng, P., and Tang, J., 2021, Multi‐model ensemble of CMIP6 projections for future extreme climate stress on wheat in the North China Plain: International Journal of Climatology, 41, E171-E186.
Deng, K., Azorin-Molina, C., Minola, L., Zhang, G., and Chen, D., 2021, Global near-surface wind speed changes over the last decades revealed by reanalyses and CMIP6 model simulations: Journal of Climate, 34(6), 2219-2234.
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.
Eyring, V., Cox, P. M., Flato, G. M., et al., 2019, Taking climate model evaluation to the next level: Nature Climate Change, 9(2), 102-110.
Farhat, F., Kashifi, M. T., Jamal, A., and Saba, I., 2022, Spatiotemporal projections of precipitation and temperature over Afghanistan based on CMIP6 global climate models: Modeling Earth Systems and Environment, 8(3), 4229-4242.
Gidden, M. J., Riahi, K., Smith, S. J., et al., 2019, Global emissions pathways under different socioeconomic scenarios for use in CMIP6: a dataset of harmonized emissions trajectories through the end of the century: Geoscientific Model Development, 12(4), 1443-1475.
Huang, J., Li, Q., and Song, Z., 2022, Historical global land surface air apparent temperature and its future changes based on CMIP6 projections: Science of The Total Environment, 816, 151656.
Intergovernmental Panel on Climate Change (IPCC), 2013, Summary for Policymakers of Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change: Cambridge University Press, Cambridge, UK.
Intergovernmental Panel on Climate Change (IPCC), 2018, Global warming of 1.5°C, in Masson-Delmotte, V., et al. (eds.), An IPCC special report on the impacts of global warming of 1.5°C above pre-industrial levels and related global greenhouse gas emission pathways, in the context of strengthening the global response to the threat of climate change, sustainable development, and efforts to eradicate poverty: Cambridge University Press, Cambridge, UK.
Intergovernmental Panel on Climate Change (IPCC), 2021, Summary for policymakers Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change: Cambridge University Press.
Kumar, P., and Sarthi, P. P., 2021, Intraseasonal variability of Indian Summer Monsoon Rainfall in CMIP6 models simulation: Theoretical and Applied Climatology, 145(1-2), 687-702.
Lavergne, T., Kern, S., Aaboe, S., et al., 2022, A new structure for the sea ice essential climate variables of the Global Climate Observing System: Bulletin of the American Meteorological Society, 103(6), E1502-E1521.
Long, Y., Xu, C., Liu, F., Liu, Y., and Yin, G., 2021, Evaluation and projection of wind speed in the arid region of northwest China based on CMIP6: Remote Sensing, 13(20), 4076.
Lun, Y., Liu, L., Cheng, L., Li, X., Li, H., and Xu, Z., 2021, Assessment of GCMs simulation performance for precipitation and temperature from CMIP5 to CMIP6 over the Tibetan Plateau: International Journal of Climatology, 41(7), 3994-4018.
Mahlstein, I., Daniel, J. S., and Solomon, S., 2013, Pace of shifts in climate regions increases with global temperature: Nature Climate Change, 3(8), 739-743.
Matzarakis, A., Hämmerle, M., Endler, C., Muthers, S., and Koch, E., 2012, Assessment of tourism and recreation destinations under climate change conditions in Austria: Meteorologische Zeitschrift, 21(2), 157.
Meehl, G. A., Covey, C., Delworth, T., et al., 2007, The WCRP CMIP3 multimodel dataset: A new era in climate change research: Bulletin of the American Meteorological Society, 88(9), 1383-1394.
Modaresi, F., and Araghi, A., 2023, Projecting future reference evapotranspiration in Iran based on CMIP6 multi-model ensemble: Theoretical and Applied Climatology, 153, 101-112.
Oleson, K. W., Monaghan, A., Wilhelmi, O., et al., 2015, Interactions between urbanization, heat stress, and climate change: Climatic Change, 129, 525-541.
O'Neill, B. C., Tebaldi, C., Van Vuuren, D. P., et al., 2016, The scenario model intercomparison project (ScenarioMIP) for CMIP6: Geoscientific Model Development, 9(9), 3461-3482.
Scafetta, N., 2023, CMIP6 GCM ensemble members versus global surface temperatures: Climate Dynamics, 60(9-10), 3091-3120.
Shen, C., Zha, J., Zhao, D., Wu, J., Fan, W., Yang, M., and Li, Z., 2021, Estimating centennial-scale changes in global terrestrial near-surface wind speed based on CMIP6 GCMs: Environmental Research Letters, 16(8), 084039.
Shi, J., Tian, Z., Lang, X., and Jiang, D., 2023, Past to future drylands in China: A multimodel analysis using CMIP6 simulations: Journal of Climate, 36(8), 2735-2751.
Supharatid, S., Nafung, J., and Aribarg, T., 2022, Projected changes in temperature and precipitation over mainland Southeast Asia by CMIP6 models: Journal of Water and Climate Change, 13(1), 337-356.
Taylor, K. E., 2001, Summarizing multiple aspects of model performance in a single diagram: Journal of Geophysical Research: Atmospheres, 106(D7), 7183-7192.
Taylor, K. E., Stouffer, R. J., and Meehl, G. A., 2012, An overview of CMIP5 and the experiment design: Bulletin of the American Meteorological Society, 93(4), 485-498.
Trenberth, K. E., 2011, Changes in precipitation with climate change: Climate Research, 47(1-2), 123-138.
Wei, T., Yan, Q., Qi, W., Ding, M., and Wang, C., 2020, Projections of Arctic sea ice conditions and shipping routes in the twenty-first century using CMIP6 forcing scenarios: Environmental Research Letters, 15(10), 104079.
Wu, J., Shi, Y., and Xu, Y., 2020, Evaluation and projection of surface wind speed over China based on CMIP6 GCMs: Journal of Geophysical Research: Atmospheres, 125(22), e2020JD033611.
Xie, B., Zhang, Q., and Ying, Y., 2011 Trends in precipitable water and relative humidity in China: 1979–2005: Journal of Applied Meteorology and Climatology, 50(10), 1985-1994.
Yang, X., Zhou, B., Xu, Y., and Han, Z., 2021, CMIP6 evaluation and projection of temperature and precipitation over China: Advances in Atmospheric Sciences, 38, 817-830.
Yassen, A. N., Nam, W. H., and Hong, E. M., 2020, Impact of climate change on reference evapotranspiration in Egypt: Catena, 194, 104711.
You, Q., Min, J., Lin, H., Pepin, N., Sillanpää, M., and Kang, S., 2015, Observed climatology and trend in relative humidity in the central and eastern Tibetan Plateau: Journal of Geophysical Research: Atmospheres, 120(9), 3610-3621.
Yu, E., Liu, D., Yang, J., Sun, J., Yu, L., and King, M. P., 2023, Future climate change for major agricultural zones in China as projected by CORDEX-EA-II, CMIP5 and CMIP6 ensembles: Atmospheric Research, 288, 106731.
Zarrin, A., Dadashi-Roudbari, A., and Hassani, S., 2021, Historical variability and future changes in seasonal extreme temperature over Iran: Theoretical and Applied Climatology, 146, 1227-1248.
Zhou, T., Chen, Z., Zou, L., et al., 2020, Development of climate and earth system models in China: Past achievements and new CMIP6 results: Journal of Meteorological Research, 34, 1-19.
موضوعات
عنوان مقاله English
نویسندگان English
It is challenging to estimate how the climate of a region will change under global warming in the future. Among the essential climate variables, temperature, relative humidity and wind speed are very important, and their changes in relation to each other can have many consequences, such as increasing heat stress and evapotranspiration.
In this research, we investigated future temperature, wind speed, and relative humidity in Iran. Five models, namely GFDL-ESM4, IPSL-CM6A-LR, MPI-ESM1-2-HR, MRI-ESM2-0, and UKESM1-0-LL from the Coupled Model Intercomparison Project Phase 6 (CMIP6) have been evaluated versus observations for 1990-2014. A multi-model ensemble was generated with the Integrated Weighted Mean (IWM) method from selected CMIP6 models, and the performances of individual CMIP6 and CMIP6-MME models in estimating temperature, wind speed, and relative humidity were investigated. The results showed that all five selected models are capable to reproduce the variables; however, the CMIP6-MME significantly improved the results. The CMIP6-MME showed good agreement with observational data both in terms of climatology and spatial distribution of each variable, and its performance is higher compared to individual models.
We have used two Shared Socioeconomic Pathways (SSPs), namely SSP2-4.5 and SSP5-8.5, and three-time periods, namely near-term (2026-2050), midterm (2051-2075), and long-term (2076-2100) relative to the historical period (1990-2014).
The results of this study showed that Iran will undergo changes in temperature, wind speed, and relative humidity spatial distribution in the future. The decrease in relative humidity and dryness of the air in the future can have important consequences for agriculture, food security, and water resources management. The findings of this study, in agreement with previous studies, emphasize the significant increase in temperature throughout Iran. Under the SSP2-4.5 (SSP5-8.5) scenario, the average annual temperature of the country increases by 1.40 (1.83), 2.34 (3.58), and 2.99 (5.58) degrees Celsius in the near (2026-2050), middle (2051-2075), and far (2076-2100) future, respectively.
Along with the increasing trend of temperature in Iran, wind speed will decrease in most regions of the country in the middle and end of the 21st century under two SSP scenarios. This decreasing trend can be a result of decreasing atmospheric instability and increasing potential temperature. The northwest of Iran has shown the maximum increasing temperature and the maximum decreasing wind speed. The decrease in relative humidity in Iran has been evident since the 1990s, and the projection results indicate that it will decrease in large parts of Iran in the future. However, the relative humidity in the southeast of Iran shows an increasing rate in the future. Results of this study show that the heat stress will be significantly higher through SSP5-8.5 than SSP2-4.5 in the 21st century due to the decrease in wind speed and increase in temperature throughout Iran. Therefore, Iran should quickly move on to formulate and implement long-term adaptation plans for resilience against climate change.
کلیدواژهها English