Changing the date of the first fall frost and the last spring frost is an important phenomenon in agriculture that can be one of the consequences of global warming. Using general circulation models (GCMs) is a way to study future climate. In this study, observations of temperature and precipitation were weighted by using Mean Observed Temperature-Precipitation (MOTP) method. This method considers the ability of each model in simulating the difference between the mean simulated temperature and mean precipitation in each month in the baseline period and the corresponding observed values. The model that had more weight, selected as the optimum model because it is expected that the model will be valid for the future. But, these models are not indicative of stationary climate change due to their low spatial resolution. Therefore, in this research, the outputs of GCM models are based on the three emission scenarios A2 and B1 and A1B, downscaled by LARS-WG for Isfahan station. The data were analyzed by SPSS software at a 95% confidence level (P<0.05). The results indicated that in the Isfahan in the future period 2020-2049 based on the three scenarios, as compared with baseline period 1971-2000, the first fall frost will occur later and the last spring frost will occur earlier. The first fall frost will occur later for 2 days (based on the A1B emission scenario) to 5 days (based on the A2 emission scenario) and the last spring frost will occur earlier for 2 days (based on the and B1 emission scenario) to 4 days (based on the A2 emission scenario). Finally, the best distribution functions for the first fall frost and the last spring frost for the baseline period and under climate change were selected and compared using the EasyFit software.
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