Comparative study between observed and numerical downscaled data of surface air temperature

Surface Air temperature, being one of the key parameters of climate, plays an important role in occurrence severe environmental issues like droughts, floods, rate of evaporation etc. In this study, an endeavor has been made to investigate the experiments available in Educational Global Climate Model (EdGCM) at Sylhet Agricultural University for recognizing best suited experiment to predict the changing pattern of surface air temperature at Sylhet region. Downscaling is a cutting-edge procedure to produce high-goals atmosphere change expectation from coarse to fine goals of worldwide atmosphere model outcomes and a conspicuous device for estimating future atmosphere situation at the local scale for some information alarm zone like Bangladesh. Maps are generated from EdGCM simulation run to collect data and depict global temperature variations. Transform software have been connected to downscale the outcomes of temperature data by Doubled_CO2, Global_Warming_01, Ice_Age_21kya, IPCC_A1F1_CO2, Modern_PredictedSST and Modern_SpecifiedSST. The trend analysis was performed using the Mann-Kendall Trend test and Sen-slope estimator. Temperature changes are significant for observed results, Doubled_CO2 and IPCC_A1F1_CO2 results where p-value is less than alpha 0.05. Doubled_CO2 results are more suited for dry season and IPCC_A1F1_CO2 provides better results for monsoon. The investigation could have been unquestionably progressively broad in the event that more situations of EdGCM information were utilized, and local boundary conditions were used.