Evaluation of Ensemble Uncertainty in the Simulation of Atmospheric General Circulation Models a Meteorological Data (Case Study of Synoptic Station in Rasht)

One of the most reliable methods for assessing the effects of climate change is the use of climate variables simulated by general atmospheric circulation (GCM) models, but these simulations have uncertainties. Avoiding the uncertainties associated with climate change in research will reduce the credibility of the results and result in unrealistic and unrealistic results. In this study, the data of temperature, precipitation and radiation simulated by 5 models HADCM3, NCCCSM, NCCCSM, INCM3, GFCM21 and MPEH5 at the Synoptic Station of Rasht based on A1B, A2 and B1 emission scenarios were statistically analyzed. Also, the uncertainty of each of the general atmospheric circulation models and diffusion scenarios was investigated by weighting method. The results of the test of the calculated statistics for each model were presented individually. The INCM3 model in the A1B scenario for simulating rainfall, the NCCCSM model in the A1B scenario for radiation simulation and GFCM21 under B1 scenario for simulating minimum temperature and HADCM3 model in the A1B scenario for maximum temperature simulation. The results of ensemble performance of the models also showed that in the future planning, the group composition of the models can be simulated with less uncertainty and more accurately the climatic parameters. In order to select the best scenario based on the group implementation of the models, the best match is the simulated rainfall data with real data based on B1 scenario, for A1B scenario data and minimum and maximum temperature based on scenario B1.