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کد مقاله : JEST-1610-3046 (R1) بازدید : 190 صفحه: 1 - 14

10.22034/jest.2020.21435.3046

نوع مقاله: پژوهشی

اثر پدیده‌ی تغییر اقلیم بر فراسنجه‌های اقلیمی همدان

محورهای موضوعی : مدیریت محیط زیست

محمد تقی اسدی 1 , حمید زارع ابیانه 2 , نسرین دلاور 3 , آذر اسدی 4

1 - دانش آموخته کارشناسی ارشد گروه مهندسی آب، دانشکده کشاورزی، دانشگاه بوعلی سینا همدان، همدان، ایران.
2 - دانشیار گروه مهندسی آب دانشکده کشاورزی دانشگاه بو علی سینا همدان
3 - دانش آموخته کارشناسی ارشد گروه مهندسی آب، دانشکده کشاورزی، دانشگاه بوعلی سینا همدان، همدان، ایران.
4 - دانش آموخته کارشناسی ارشد گروه مهندسی آب، دانشکده کشاورزی و منابع طبیعی، دانشگاه رازی،کرمانشاه، ایران.

تاریخ دریافت : 1395/07/17 تاریخ پذیرش : 1395/10/29 تاریخ انتشار : 1398/09/01

کلید واژه: مدل‌های گردش عمومی جو, ریز‌مقیاس‌نمایی, LARS-WG, همدان, تغییراقلیم,

چکیده مقاله :

زمینه و هدف: فرآیند تغییر اقلیم به ویژه تغییرات دما و بارش مهم‌ترین بحث مطرح در قلمرو علوم محیطی می‌باشد. این پدیده به‌دلیل ابعاد علمی و کاربردی آن از اهمیت فزاینده‌ای برخوردار است. چرا که سیستم‌های انسانی وابسته به عناصر اقلیمی مانند کشاورزی و صنایع بر مبنای ثبات و پایداری اقلیم طراحی شده و عمل می‌نمایند. روش بررسی: در پژوهش حاضر از داده‌های خروجی پنج مدل گردش عمومی جو GFCM21، HADCM3، INCM3، IPCM4 و NCCCSM برای بررسی تغییرات چهار فراسنجه‌ی دمای کمینه، دمای بیشینه، بارش وساعت آفتابی همدان در دوره‌ی 2065-2046 استفاده شد. برای این منظور با استفاده از مدل ریز‌مقیاس‌نمایی LARS-WG و لحاظ سه سناریوی A1B، A2 و B1، تغییرات ماهانه‌ی فراسنجه‌ها محاسبه شد. یافته‌ها: نتایج نشان داد به‌طور متوسط، بیش‌ترین افزایش دمای کمینه مربوط به مدل GFCM21 تحت سناریوی A1B، برابر 5/2 درجه سانتی‌گراد می‌باشد و کم‌ترین آن در مدل INCM3 تحت سناریوی B1 معادل 1 درجه سانتی‌گراد مشاهده شد. بیش‌‌ترین و کم‌ترین افزایش دمای بیشینه به‌ترتیب به سناریوی A1B و B1 مدل GFCM21 با 4/2 و 4/1 درجه سانتی‌گراد افزایش تعلق داشت. بیش‌‌ترین افزایش بارش مربوط به سناریوی B1 مدل IPCM4 به‌مقدار 8/15 درصد و بیش‌ترین کاهش در مدل GFCM21 تحت سناریویA1B معادل 13 درصد بود. بیش‌‌ترین افزایش تابش خورشیدی در مدل HADCM3 تحت سناریوی A1B با 24 درصد و کم‌ترین مقدار آن در سناریوی A2 مدل NCCCSM به‌مقدار 17/3 درصد کاهش مشاهده گردید. بحث ونتیجه‌گیری: نتایج این تحقیق نشان داد دمای کمینه و بیشینه در دوره‌ی 2065-2046 افزایش می‌یابد. تغییرات بارش، هم به‌صورت افزایشی و هم به‌صورت کاهشی دیده شد. تغییرات ساعت آفتابی نیز بسیار کم و نامحسوس است.

چکیده انگلیسی:

Background and Objective: Process of climate change, particularly changes in temperature and precipitation; have raised the most discussion in the realm of environmental science. Human systems that are dependent on climatic elements such as agriculture and industry were designed based on stable climate. Method: In this study the output of general circulation models (GFCM21, HADCM3, INCM3, IPCM4 and NCCCSM) was used to simulate the climate parameters (minimum temperature, maximum temperature, precipitation and sunshine hours) in Hamadan station during 2046-2065. Three scenarios A1B, A2 and B1 were considered. Monthly changes of climate parameters were calculated by LARS-WG model. Findings: The results showed that the most increasing in minimum temperature were seen under A1B scenario of GFCM21 model (2.5˚C). The least increasing was related to INCM3 under B1 scenario (1˚C). The highest and lowest increasing in maximum temperature were seen in GFCM21 model under A1B and B1 scenarios by 2.4 and 1.4˚C, respectively. B1 scenario of IPCM4 model showed the highest increase in precipitation by 15.8 percent and A1B scenario of GFCM21 model reported the highest decrease by 13 percent. Solar radiation project by HADCM3 model, A1B scenario showed the most increase about 24 percent and based on NCCCSMmodel, A2 scenario lowest increase (by 13 percent) was seen. Discussion and Conclusion: The results of this study indicated minimum and maximum temperatures will increase in period of 2046-2065. Both increases and decreases in precipitation were seen. Also variations sun hour is very little.

منابع و مأخذ:


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  5. Babaeian, I., Najafi, Z. 2011. Climate Change Assessment in Khorasan-e Razavi Province from 2010 to 2039 Using Statistical Downscaling of GCM Output. Journal of Geography and Regional Development (Peer-Reviewed), 8(15). (In Persian)
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  8. Saadi, S., Todorovic, M., Tanasijevic, L., Pereira, L., Pizzigalli, C. Lionello, P., 2015. Climate change and Mediterranean agriculture: Impacts on winter wheat and tomato crop evapotranspiration, irrigation requirements and yield. Journal of Agricultural Water Management Vol. 147, pp. 103-115.
    9.
  9. Ohunakin, O. S., Adaramola, M. S., Oyewola, O. M., Matthew, O. J. Fagbenle, R. O., 2015. The effect of climate change on solar radiation in Nigeria. Journal of Solar Energy, Vol. 116, pp. 272-286.
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_||_

  1. Haghtalab, N.,  Goodarzi, M, Habibi Nokhandan, M., Yavari, A.R., Jafari, H.R. 2013. Climate modeling in Tehran and Mazandaran provinces by LARSWG and comparing changes in northern and southern central Alborz hillside. Journal of environmental science and technology. 2013, 15(1); p 38-49. (In Persian)
    2.
  2. Rasuli, A.A., Rezaei Banafsheh, M., Massah, A.R., Khorshiddoust, A.M., Ghermezcheshmeh, B., 2014. Investigation Impact of Morpho-Climatic Parameters on Aaccuracy of LARS-WG Model. Iranian Journal of Watershed Management Science and Engineering, 8 (24), P 9-24.(In Persian)
    3.
  3. Mohammadi, H., Moghbel, M.,  Ranjbar, F., 2010.The study of temperature and precipitation changes in Iran with MAGICC SCENGEN model geography summer. 8(25) p 125-142. (In Persian)
    4.
  4. Dousti; M., Habibnezhad Roshan; M., Shahedi, K; Miryaghoubzade, M., 2014. Study of climate indices of Tamar River basin Golestan Province in terms of climate change using by LARS-WG model. Journal of the Earth and Space Physics (JESP), 39(4), P 177-189. (In Persian)
    5.
  5. Babaeian, I., Najafi, Z. 2011. Climate Change Assessment in Khorasan-e Razavi Province from 2010 to 2039 Using Statistical Downscaling of GCM Output. Journal of Geography and Regional Development (Peer-Reviewed), 8(15). (In Persian)
    6.
  6. Rajabi, A., Shabanlou,S, 2014.Study of some climate index changes in NCCCSM global circulation model output. Case study: Kermanshah (Iran). Iranian Water Research Journal, 7(13) P 41 –49. (In Persian)
    7.
  7. Mahsafar, H., Maknoun, R. Saghafian, B., 2011. The impact of climate change on Urmia Lake water level, 8(19): p. 47-58.
    8.
  8. Saadi, S., Todorovic, M., Tanasijevic, L., Pereira, L., Pizzigalli, C. Lionello, P., 2015. Climate change and Mediterranean agriculture: Impacts on winter wheat and tomato crop evapotranspiration, irrigation requirements and yield. Journal of Agricultural Water Management Vol. 147, pp. 103-115.
    9.
  9. Ohunakin, O. S., Adaramola, M. S., Oyewola, O. M., Matthew, O. J. Fagbenle, R. O., 2015. The effect of climate change on solar radiation in Nigeria. Journal of Solar Energy, Vol. 116, pp. 272-286.
    10.
  10. Tramblay, Y., Badi, W., Driouech, F., Adlouni, S., Neppel, L. Servat, E., 2012. Climate change impacts on extreme precipitation in Morocco. Journal of Global and Planetary Change, Vol. 83, pp. 104-114.
    11.
  11. Yinlong, X., Xiaoying, Z., Yong, L. W. Erda, L., 2006. Statistical analysis of the climate changes scenarios over China in the 21st century. Journal of Advances in Climate Change Research, Vol. 2, pp. 50-53.
    12.
  12. Khosravi, M., Esmaeilnezhad, M., Nazaripour, H., 2010. Climate Change and its Impact on Middle East Water Resources. Proceedings of the Fourth International Congress of Islamic Geographers of the Islamic World, Iran, Zahedan.(In Persian)
    13.
  13. Ashraf, B., Mousavi Baygi, M., Kamali, Gh. A, Davari K., 2011. Prediction of Water Requirement of Sugar beet during 2011-2030 by Using Simulated Weather Data with LARS-WG Downscaling Model. Journal of Water and Soil. 25 (5), p. 1184-1196.(In Persian)
    14.
  14. Abassi, F., Malbusi, I., Babaeian, Asmari, M., Borhani, R., 2010. Climate Change Prediction of South Khorasan Province During 2010-2039 by Using Statistical Downscaling of ECHO-G Data. Journal of Water and Soil. 24(2), p. 218-233.(In Persian)
    15.
  15. Du, Y., Cheng, X,. Wang, X., Ai, H., Hai-Lai. H., Wu, X. 2013. A Review of Assessment and Adaptation Strategy to Climate Change Impacts on the Coastal Areas in South China. Journal of Advances in Climate Change Research,. 44, p. 201-207.
    16.
  16. Ansari, H., Khadivi, M., Salehnia, N., Babaeian, I., 2015.Evaluation of Uncertainty LARS Model under Scenarios A1B, A2 and B1 in Precipitation and Temperature Forecast (Case Study: Mashhad Synoptic Stations). Iranian journal of irrigation and drainage. 8(4), 664-672. (In Persian)
    17.
  17. Pooralihosein, Sh., Massah Bavani, A.R., 2014., Risk analysis and assessment of impacts of climate change on temperature and precipitation of East Azerbaijan in 2013-2022. Journal of the Earth and Space Physics (JESP). 39(4), P 191-208. (In Persian)
    18.
  18. Chen, H., Guo, J., Zhang, Z. Xu, Ch., Y., 2013. Prediction of temperature and precipitation in Sudan and South Sudan by using LARS-WG in future. Journal of Theoretical and Applied Climatology, 113(3), p. 363-375.
    19.
  19. Roshan, Gh., Khoshakhlagh., F., Azizi, Gh.,2012. Assessment of Suitable General Atmosphere Circulation Models for Forecasting Temperature and Precipitation Amounts in Iran under Condition of Global Warming.Journal of Geography and development, 10(27), P 19-36. (In Persian)
    20.

 

 

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