عدم قطعیت مدل‏های AOGCM در بررسی اثرات تغییر اقلیم بر پارامترهای اقلیمی (مطالعه موردی: حوزه آبخیز قره‏سو)

Currently, the most reliable tools for generating climate scenarios are coupled atmosphere-ocean general circulation models (AOGCMs). However, when predicting climatic parameters and estimating future runoff under the influence of climate change, various sources of uncertainty exist, including the uncertainty of AOGCM models. In this study, downscale data from 21 AOGCM models under the balanced and optimistic RCP4.5 scenario were examined and evaluated to assess the uncertainty of these models. After validating the models, the best and most suitable model for the study area was selected on the basis of criteria such as coefficient of determination (R2) and efficiency coefficient (ME). Weighting methods and box-whisker plots (Box-Visker) were also used to investigate the uncertainty of the AOGCM models.
The analysis of monthly average precipitation at the Kermanshah synoptic station and simulated precipitation by AOGCM models during the base period (2005-1976) showed that each model estimated different values of precipitation. Regarding precipitation, the MRI-CGCM3, MPI-ESM-LR, BNU-ESM, ACCESS1-0, MIROC-ESM, MIROC-ESM-CHEM, and MPI-ESM-MR models performed better, whereas for temperature, the ACCESS1-0, CNRM-CM5, MIROC-ESM, MIROC-ESM-CHEM, MPI-ESM-LR, MPI-ESM-MR, MRI-CGCM3, and BNU-ESM models performed better in simulation. The weighting results for each model in precipitation and temperature modeling showed that the models with the least error received the highest weight. Thus, the MRI-CGCM3, MPI-ESM-LR, BNU-ESM, ACCESS1-0, MIROC-ESM, MIROC-ESM-CHEM, and MPI-ESM-MR models had the highest weight in simulating precipitation, maximum temperature, and minimum temperature during the past period, and can be ...