Nonlinear Analysis of Daily Temperature Data

In this work, we analyze average daily air temperature records for 12 years for some cities. For each city, daily recodes are deeply influenced by the seasonal fluctuation. We attempted to remove this seasonality by subtracting a properly adjusted sine function. Nonlinear analysis of data will be attempted to find fractal and/or chaotic nature of daily average temperature of original data as well as the data after removal of seasonality and compare the results. Evidence of chaos is found through calculation of Lyapunov exponent.