The impact of climate change on mean, maximum and minimum temperatures using statistical downscaling techniques: A case of Gaziantep region

In this study global temperature over Gaziantep region was investigated using Statistical downscaling technique. This SD models depend on the foundational concept that regional inputs or local variables heavily depend on the large scale atmospheric variables. In this research, the scenarios of the downscaled emissions were obtained from CanESM2 Canadian Second Generation Earth System Model in the city of Gaziantep, a province in south-eastern Turkey. These scenarios are compared to the observed variables form the analysis. The key aims of this thesis are to (i) investigate the predicted monthly mean, maximum, and minimum temperatures and (ii) the GCM (General Circulation Model) projections that are simulated under three scenarios (RCP2.6, RCP4.5, AND RCP8.5). To achieve this purpose, the research utilizes the Linear Regression model (LR), Group Method of Data Handling (GMDH), and Gene Expression Programming (GEP) to compare the statistically downscaled findings of the monthly temperatures. Therefore, GMDH was the best predictor model of mean temperature with a coefficient of determination (R2) of 0.955 for the period of calibration (1962-1990) and 0.9317 for the validation period (1991-2005). Similarly, GMDH had the highest coefficient of determination (R) for maximum and minimum temperatures for the calibration period (R2=0.934 and R2=0.907) and validation period (R2=0.91 and R2=0.84), respectively. In general, the simulated scenarios predict an increase in mean, max and min temperatures in Gaziantep region for the future period of 2021-2100. In addition, the scenario of RCP4.5 is the best anticipator for the mean and minimum temperatures, while RCP2.6 better projects maximum temperature of the case study. The mean and maximum temperature charts display a parabolic trend, but for minimum temperature, the graphs show no pattern. Lastly, the months of August and December were compared in a scatter graph indicating the annual mean, maximum and minimum projections. Key Words: Statistical Downscaling, GCM, Temperature, GEP, GMDH