Modelling and Forecasting the Impact of Air Temperature on Global Warming: Karachi as a Case Study

Abstract The world has experienced extreme climate changes and global warming. It also causes high temperature, droughts, rising sea level and flooding. In Karachi, the construction activities and transportation caused most of the Green House Gases (GHG) and carbon dioxide (CO2) emission. In the paper, the data under consideration is 60 years mean monthly maximum and minimum air temperature of Karachi ranging from 1961 to 2020 has been used to forecast the temperature impact over time. The minimum and maximum temperature data were observed, forecasted city temperature. ARMA (p, q) model used to modelling and forecasting the behaviour of Karachi maximum and minimum air temperature using Pakistan Metrological Department (PMD) data. The results show that the Theil’s U-Statistics values of each month lie approaches to zero shows that the air temperature is strongly correlated to previously observed values. The results of this study are very beneficial for observing the influence of air temperature on the global warming.