Potential of atmospheric-ocean general circulation models in simulating relative humidity changes (Case study: Neka city)

The warming of the earth also affects the condition of other parts of the climate system and causes the phenomenon of climate change. Global warming increases the moisture capacity of the air and decreases the relative humidity of the air. The most common method of simulating climate parameters is to use the output data of atmospheric general circulation models. When the results of the models are evaluated on a much smaller scale, significant differences are created. But how can these differences be eliminated and models can be chosen that can provide a suitable background for the future of climate change. In this research, these differences are investigated and the accuracy of the results of climate models in predicting the relative humidity of the air is investigated using the validation method. In this regard, the relative humidity data of Dasht Naz synoptic station in Neka city was used on a daily basis with a statistical length of 25 years (1990-2014). Next, the relative humidity parameter data of the closest cell to the synoptic station was downloaded from the data of general atmospheric circulation models, the sixth report of the Intergovernmental Panel on Climate Change, in the common period (1990-2014) and extracted in Arc GIS 10.8 software. According to the results, ACCESS-ESM1-5, CNRM-CM6-1, CanESM5, IPSL-CM6A-LR, GISS-E2-1-G and MIROC6 models showed the highest correlation with observational data, but Except for two ACCESS-ESM1-5 and CanESM5 models, the other mentioned models had a high bias compared to the observational data. Therefore, ACCESS-ESM1-5 and CanESM5_ESM models are recommended among climate models to predict relative humidity in the future in the Neka region.