پیش‌بینی تغییر اقلیم با استفاده از رویکرد مدل های چندگانۀ گروهی در حوضۀ آبخیز قره سو

نوع مقاله : پژوهشی

نویسندگان

1 دانشیار گروه مهندسی آب، پردیس ابوریحان، دانشگاه تهران

2 دانش‏آموختۀ کارشناسی ارشد مهندسی منابع آبیاری و زهکشی، پردیس ابوریحان، دانشگاه تهران

3 استادیار گروه علوم محیط زیست، دانشکدۀ علوم، دانشگاه زنجان

10.22059/ije.2022.329152.1541

چکیده

با توجه به اینکه گرمایش زمین عامل تهدید‌کننده‏ای برای زندگی بشر در کرۀ زمین است، پیش‏بینی تغییرات اقلیمی در آینده امری ضروری به حساب می‏آید. از اهداف این مطالعه، پیش‏بینی دما و بارش روزانه آیندۀ نزدیک (2021-2040)، با استفاده از مدل‏های گردش عمومی جو- اقیانوس (AOGCM) و نیز کاهش عدم قطعیت‏‏ها آن‏ها است. بنابراین، در این تحقیق ابتدا، از میان مدل‏های بررسی‌شده، 5 مدل مناسب شامل HADGEM2-ES،MICRO IPSL-CM5A-LR،NOERESM1-M ESM2M-GFDEL  انتخاب و به روش LARS-WG ریزمقیاس‌نمایی شد. سپس، با استفاده از دو رویکرد وزن‏دهی Raisanen و میانگین مشاهداتی دما و بارش (MOTP) جهت وزن‏دهی و همادی کردن مدل‏های چندگانه (Ensemble Multi-Model) استفاده شد. نتایج نشان می‏دهد دمای حداکثر در تمامی ماه‏ها افزایش می‏یابد که بیشترین افزایش دما در مدل Raisanen، در ماه فوریه و کمترین افزایش در ماه اکتبر است. در مدل وزن‏دهی MOTP، بیشترین افزایش دما در ماه ژانویه و کمترین افزایش دما، ماه آگوست است. تغییرات بارندگی در ماه‏های ژوئن، جولای و آگوست کاهش چشم‏گیری را به دلیل بارش مشاهداتی جزئی داشته است. در این تحقیق روش وزن‏دهی MOTP برای پیش‏بینی متغیرهای اقلیمی در دوره‏های آینده به دلیل داشتن R2 بالاتر و کمترین RMSE به عنوان روش بهتر در پیش‏بینی داده‏های اقلیمی انتخاب شد. طبق نتایج به‌دست‌آمده انتظار می‏رود بازخورد بارزی در بیلان آبی منطقه به دلیل اثر افزایش دما و افزایش تبخیر به وجود آید و همچنین، پتانسیلی برای تغییر در وقایع جوی و هیدرولوژی حوزه به وجود آید.

کلیدواژه‌ها


عنوان مقاله [English]

Predicting Climate Change Using the Multiple Group Model Approach in Qarasu Watershed

نویسندگان [English]

  • Alireza Massah Bavani 1
  • Sajad ghasemzadeh 2
  • Abbas Rozbahani 1
  • رجائی Rajaei 3
1 University of Tehran
2 Tehrn university
3 Environmental science department, Science faculty, Zanjan University
چکیده [English]

Abstract
Given that global warming is a threat to human life on Earth, predicting future climate change is essential. One of the objectives of this study is to predict daily temperature and precipitation in the near future (2021-2040), using general atmosphere-ocean circulation (AOGCM) models and reduce their uncertainties. Therefore, in this study, first, among the studied models, 5 suitable models including HADGEM2-ES, MICRO IPSL-CM5A-LR, NOERESM1-M ESM2M-GFDEL were selected and downscale by LARS-WG method. Then, using two approaches of Raisanen weighting and observational mean temperature and precipitation (MOTP) were used to weight and ensemble multiple models. The results show that the maximum temperature increases in all months, with the highest temperature increase in the Riesen model in February and the lowest increase in October. In the MOTP weighting model, the highest temperature increase is in January and the lowest temperature increase is in August. The percentage of rainfall changes in June, July and August decreased significantly due to slight observational rainfall. In this study, the MOTP weighting method was chosen to predict climate variables in future periods due to having a higher R2 and the lowest RMSE as a better method in predicting climate data. Therefore, according to the results, it is expected that significant feedback in the water balance of the region will be due to the effect of increasing temperature and increased evaporation, as well as the potential for changes in atmospheric events and hydrology of the basin.

کلیدواژه‌ها [English]

  • Keywords: Climate Change
  • Ocean-atmosphere general circulation models (AOGCM)
  • Weighting methods
  • Multiple group models
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