| Summary: | Downscaling of climate projections is the most adapted method to assess the impacts of climate change at regional and local scale. In the last decade, downscaling techniques which provide reasonable approach in improving resolution of General Circulation Models’ (GCMs) output are developed in notable manner. Most of these techniques are limited to spatial downscaling of GCMs’ output and still there is a high demand to develop temporal downscaling approaches. As the main objective of this study, combined approach of spatial and temporal downscaling is developed to improve the resolution of rainfall predicted by GCMs. Proposed approach is based on the Statistical Downscaling Model (SDSM) and scaling invariant concept. Melbourne airport rain gauge station is subjected to this study. SDSM model is calibrated for 1971-1990 period and validated for 1991-2000 period. Further, second order bias correction function is used to improve the accuracy of simulated annual maximum rainfalls by SDSM. By analysing the moments of observed rainfall intensities, one time regime (12 minutes to 24 hours) which exists simple scaling behaviour is identified and it is used to estimate the sub daily extreme intensities. Accuracy of estimated sub daily extreme intensities are checked and it showed a good agreement with observed intensities. Finally, the major output of this study, Intensity Duration Frequency (IDF) relations are developed for the future periods of 2020s, 2050s and 2080s in the context of climate change.
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