This thesis presents the development and application of a downscaling framework for multi site simulation of daily rainfall. The rainfall simulation is achieved in two stages. First, rainfall occurrences at multiple sites are downscaled, which is followed by the generation of daily rainfall amounts at each site identified as wet. A continuous weather state based nonparametric downscaling model conditional on atmospheric predictors and a previous day average rainfall state is developed for simulation of multi site rainfall occurrences. A nonparametric kernel density approach is used for simulation of rainfall amounts at individual sites conditional on atmospheric variables and the previous day rainfall amount. The proposed model maintains spatial correlation of rainfall occurrences by simulating concurrently at all stations and of amounts by using random innovations that are spatially correlated yet serially independent. Temporal dependence is reproduced in the occurrence series by conditioning on previous day average wetness fraction and assuming the weather states to be Markovian, and in the amount series by conditioning on the previous day rainfall amount. The seasonal transition is maintained by simulating rainfall on a day-to-day basis using a moving window formulation. The developed downscaling framework is calibrated using the relevant atmospheric variables and rainfall records of 30 stations around Sydney, Australia. Results indicate a better representation of the spatio-temporal structure of the observed rainfall as compared to existing alternatives. Subsequently, the framework is applied to predict plausible changes in rainfall in warmer conditions using the same set of atmospheric variables for future climate obtained as a General Circulation Model simulation. While the case studies presented are restricted to a specific region, the downscaling model is designed to be useful in any generic catchment modelling and management activity and/or for investigating possible changes that might be experienced by hydrological, agricultural and ecological systems in future climates.