Uncertainty analysis of global climate models in predicting monthly average temperature using Latin Hypercub Sampling (case study: Minab Dam basin)

It is necessary to understand the climate change in next decades to have a suitable environmental planning for adapting and reducing it's effects. In climate change studies, ignoring uncertainties at various stages of impact assessment will reduce confidence in system results. This uncertainty is due to the performance of general circulation models, different emission scenarios and doanscaling process. In this research uncertainty of monthly average temperature of drainage basin of Minab dam is projected in two periods(2016-2045 and 2046-2075) using outcomes of the five general circulation models of the HADGEM2-ES, BNU-ESM, CCSM4, CSIRO-MK3-6, MPI-ESM-MR under three scenarios of RCP2.6, RCP4.5 and RCP8.5. For this purpose, using the method of variants of average tempreture for change factor, future is downscaled. Latin hypercube method wich is an accidental sampelling is used here for checking the uncertainty of models. The results of period uncertainty, in all models and scenarios showed that, the uncertainty of the second period (2046-2075) is greater than in the first period (2016-2045). It means, increasing the length of the forecast period increases the error in predicting climate change models. The results showed the uncertainty of the different models showed that the least uncertainty was related to the CSIRO-Mk3-6 model in the RCP2.6 scenario and the 2016-2045 period, while the highest uncertainty was related to the HadGEM2-ES model in the scenario and period.It is necessary to understand the climate change in next decades to have a suitable environmental planning for adapting and reducing it's effects. In climate change studies, ignoring uncertainties at various stages of impact assessment will reduce confidence in system results. This uncertainty is due to the performance of general circulation models, different emission scenarios and doanscaling process. In this research uncertainty of monthly average temperature of drainage basin of Minab dam is projected in two periods(2016-2045 and 2046-2075) using outcomes of the five general circulation models of the HADGEM2-ES, BNU-ESM, CCSM4, CSIRO-MK3-6, MPI-ESM-MR under three scenarios of RCP2.6, RCP4.5 and RCP8.5. For this purpose, using the method of variants of average tempreture for change factor, future is downscaled. Latin hypercube method wich is an accidental sampelling is used here for checking the uncertainty of models. The results of period uncertainty, in all models and scenarios showed that, the uncertainty of the second period (2046-2075) is greater than in the first period (2016-2045). It means, increasing the length of the forecast period increases the error in predicting climate change models. The results showed the uncertainty of the different models showed that the least uncertainty was related to the CSIRO-Mk3-6 model in the RCP2.6 scenario and the 2016-2045 period, while the highest uncertainty was related to the HadGEM2-ES model in the scenario and period.It is necessary to understand the climate change in next decades to have a suitable environmental planning for adapting and reducing it's effects. In climate change studies, ignoring uncertainties at various stages of impact assessment will reduce confidence in system results. This uncertainty is due to the performance of general circulation models, different emission scenarios and doanscaling process. In this research uncertainty of monthly average temperature of drainage basin of Minab dam is projected in two periods(2016-2045 and 2046-2075) using outcomes of the five general circulation models of the HADGEM2-ES, BNU-ESM, CCSM4, CSIRO-MK3-6, MPI-ESM-MR under three scenarios of RCP2.6, RCP4.5 and RCP8.5. For this purpose, using the method of variants of average tempreture for change factor, future is downscaled. Latin hypercube method wich is an accidental sampelling is used here for checking the uncertainty of models. The results of period uncertainty, in all models and scenarios showed that, the uncertainty of the second period (2046-2075) is greater than in the first period (2016-2045). It means, increasing the length of the forecast period increases the error in predicting climate change models. The results showed the uncertainty of the different models showed that the least uncertainty was related to the CSIRO-Mk3-6 model in the RCP2.6 scenario and the 2016-2045 period, while the highest uncertainty was related to the HadGEM2-ES model in the scenario and period.It is necessary to understand the climate change in next decades to have a suitable environmental planning for adapting and reducing it's effects. In climate change studies, ignoring uncertainties at various stages of impact assessment will reduce confidence in system results. This uncertainty is due to the performance of general circulation models, different emission scenarios and doanscaling process. In this research uncertainty of monthly average temperature of drainage basin of Minab dam is projected in two periods(2016-2045 and 2046-2075) using outcomes of the five general circulation models of the HADGEM2-ES, BNU-ESM, CCSM4, CSIRO-MK3-6, MPI-ESM-MR under three scenarios of RCP2.6, RCP4.5 and RCP8.5. For this purpose, using the method of variants of average tempreture for change factor, future is downscaled. Latin hypercube method wich is an accidental sampelling is used here for checking the uncertainty of models. The results of period uncertainty, in all models and scenarios showed that, the uncertainty of the second period (2046-2075) is greater than in the first period (2016-2045). It means, increasing the length of the forecast period increases the error in predicting climate change models. The results showed the uncertainty of the different models showed that the least uncertainty was related to the CSIRO-Mk3-6 model in the RCP2.6 scenario and the 2016-2045 period, while the highest uncertainty was related to the HadGEM2-ES model in the scenario and period.