The study explored the spatio-temporal evolution of rainfall and precipitable water oscillations using data of over two decades. The monthly averages of rainfall and precipitable water were obtained from six locations in the southwestern climatic region of Nigeria. The data were analysed using five mathematical models namely the sum of two-Gaussians, the sum of two-Lorentzian, Fourier on four harmonics, sine wave and fourth-order polynomial functions for prediction purposes. The performances of these models were evaluated using the mean bias error (MBE), root mean square error (RMSE), mean percentage error (MPE), standard error (SE) and the correlation coefficient (R). The performance indicators of the models showed that the Gaussian and Lorentzian models are in good agreement with the observed data. However, the Fourier on fourth harmonics model had the lowest MBE, RMSE and MPE, consequently highest correlation coefficient values, indicating high model accuracy. Thus, the Fourier model has the best correlation with the observed data and is recommended for estimating these variables in the selected locations.