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

Document Type : Research Article


1 University of Tehran

2 Tehrn university

3 university of Tehran

4 Environmental science department, Science faculty, Zanjan University


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.


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Volume 8, Issue 4
January 2022
Pages 1189-1197
  • Receive Date: 09 August 2021
  • Revise Date: 28 November 2021
  • Accept Date: 28 November 2021
  • First Publish Date: 22 December 2021
  • Publish Date: 22 December 2021