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We investigate the influence of bias correction of Global Climate Models (GCMs) prior to dynamical downscaling using regional climate models (RCMs), on the change in climate projected. We use 4 GCMs which are bias corrected against ERA-Interim re-analysis as a surrogate truth, and carry out bias corrected and non-bias corrected simulations over the CORDEX Australasia domain using the Weather Research and Forecasting model. Our results show that when considering the effect of bias correction on current and future climate separately, bias correction has a large influence on precipitation and temperature, especially for models which are known to have large biases. However, when considering the change in climate, i.e the Δ change (future minus current), we found that while differences between bias-corrected and non-corrected RCM simulations can be substantial (e.g. more than 1 ∘ C for temperatures) these differences are generally smaller than the models' inter-annual variability. Overall, averaged across all variables, bias corrected boundary conditions produce an overall reduction in the range, standard deviation and mean absolute deviation of the change in climate projected by the 4 models tested, over 61.5%, 62% and 58% of land area, with a larger reduction for precipitation as compared to temperature indices. In addition, we show that changes in the Δ change for DJF tasmax are broadly linked to precipitation changes and consequently soil moisture and surface sensible heat flux and changes in the Δ changefor JJA tasmin are linked to downward longwave heat flux. This study shows that bias correction of GCMs against re-analysis prior to dynamical downscaling can increase our confidence in projected future changes produced by downscaled ensembles. [ABSTRACT FROM AUTHOR]

Regional climate models (RCMs) are used to dynamically downscale global climate models (GCMs) to provide high-resolution projections of future climate change to better inform policy and decision making at the regional scale. However, biases from GCMs are transferred to RCMs and this can limit the usefulness of the regional climate projections. This paper investigates the influence of bias correcting 4 GCMs from the Coupled Model Intercomparison Project 3, for regional climate simulations over the CORDEX-Australasia domain using Weather Research and Forecasting. The GCM outputs are bias corrected against ERA-Interim reanalysis as a surrogate truth. Results show that over decadal time scales bias correction removes large systematic precipitation and temperature biases. However, bias correction also introduced biases where there were none, introduced biases of the opposite sign, or enhanced existing biases in other regions in some instances. The dynamical mechanisms driving the changes in the biases are explored. [ABSTRACT FROM AUTHOR]