Articles | Volume 369
Proc. IAHS, 369, 147–155, 2015
https://doi.org/10.5194/piahs-369-147-2015
Proc. IAHS, 369, 147–155, 2015
https://doi.org/10.5194/piahs-369-147-2015

  11 Jun 2015

11 Jun 2015

Downscaling approach to develop future sub-daily IDF relations for Canberra Airport Region, Australia

H. M. S. M. Herath1, P. R. Sarukkalige1, and V. T. V. Nguyen2 H. M. S. M. Herath et al.
  • 1Department of Civil Engineering, Curtin University, Perth, Western Australia
  • 2Department of Civil Engineering, McGill University, Canada

Abstract. Downscaling of climate projections is the most adopted method to assess the impacts of climate change at regional and local scale. In the last decade, downscaling techniques which provide reasonable improvement to 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. Canberra airport region is subjected to this study and the applicability of proposed downscaling approach is evaluated for Sydney, Melbourne, Brisbane, Adelaide, Perth and Darwin regions. Statistical Downscaling Model (SDSM) is used to spatial downscaling and numerical model based on scaling invariant concept is used to temporal downscaling of rainfalls. National Centre of Environmental Prediction (NCEP) data is used in SDSM model calibration and validation. Regression based bias correction function is used to improve the accuracy of downscaled annual maximum rainfalls using HadCM3-A2. By analysing the non-central moments of observed rainfalls, single time regime (from 30 min to 24 h) is identified which exist scaling behaviour and it is used to estimate the sub daily extreme rainfall depths from daily downscaled rainfalls. Finally, as 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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This paper presents a combined approach of spatial and temporal downscaling of future rainfall predicted by GCMs whereas most of the techniques in the literature are limited to spatial downscaling. This study uses rainfall data from several capital cities in Australia; Canberra, Sydney, Melbourne, Brisbane, Adelaide, Perth and Darwin regions. Statistical Downscaling Model (SDSM) is used for spatial downscaling and numerical model based on scaling invariant concept is used for temporal downscali