Considering the urban growth G = G (P, E) as a function of population growth P and environmental and climatic change E the thesis studies the urban growth of Karachi by studying the variations of P and E for Karachi and their interactions. Though, the scope of E is large we keep restricting to temperature variations only. Karachi is worth studying because of its high population growth rate and evidences of climatic variability. Chapter 1 looks into the trends of urban population growth of Karachi in global, regional and national perspectives by using Reciprocal Logarithmic Model, Polynomial Models and Exponential Growth Rate Model. The population growth rate of Karachi is forecasted for (2011-2020) with the help of annual growth rate model. Chapter 2 studies the district and town wise population-area relationship using Hoover indices and Lorenz curves. It also studies the population density distribution of Towns and slums (Katchi-Abadies) of Karachi. It is found that the town wise pattern is better than the district wise distribution. The population density distribution of 18 towns of Karachi is studied with the help of Flatten Gradient Density Model and Spatial Interaction Models, the probability of change of the population density of the towns is studied with the help of Spatial Interaction Model. Global Flatten Gradient Density Model is developed to determine population densities of KKAs, results are verified by log linear and linear exponential transformation models. Chapter, 3 studies the variations of urban land temperature (ULT) of Karachi and the xiArabian Sea surface temperature (SST) in the vicinity of Karachi using linear as well as non liner models. The probabilistic behavior of the two data sets is also explored. Comparing the variations of ULT of Karachi and less populated city of Hyderabad it is tried to find that whether the rise of temperature of Karachi is a consequence of heavy urbanization. Our ARIMA forecasts for SST predicts the months of May, June, July, August and some days in October for the year 2010 to show extreme temperatures which is confirmed by the actual 2010 records. For the long run our models predict warm summers in 2014, 2016, 2018, and 2019. A good correlation exists between urban land and sea surface temperatures. Chapter 4 studies one of the possible consequences of the increase in SST. On the basis of 120 years data of frequency of cyclones in the Arabian Sea this study investigates the possibility of increase in the frequency of cyclones. Trends for May, June, October, and November are found to be significantly increasing. The Persistency of the data is tested with the help of Hurst exponents. For the above mentioned months the Hurst exponents range between 0.83 and 0.98 indicating a high level of persistency. The chapter ends with a study of possible impacts of the increasing frequency of Arabian Sea cyclones on the coastal towns of Karachi studied. It is found that Bin Qasim town is most vulnerable in view of its long coastal length (11 Km) and Saddar and Clifton towns(509,915) is most vulnerable in view of its large population. Chapter 5 concludes the thesis and mentions the future aspects.