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.

区域气候模型（RCM）用于动态缩减全球气候模型（GCM），以提供未来气候变化的高分辨率预测，从而更好地为区域规模的政策和决策提供依据。但是，来自GCM的偏差已转移到RCM，这可能会限制区域气候预测的用处。本文研究了耦合模型比较项目3的4个GCM偏差校正对天气研究和预报对CORDEX-Australasia域进行区域气候模拟的影响。对GCM输出进行了针对ERA-Interim重新分析的偏差校正（作为替代真实）。结果表明，超过十年的时间尺度偏差校正消除了较大的系统降水和温度偏差。但是，偏差校正还会在没有偏差的地方引入偏差，引入了相反符号的偏差，或在某些情况下增强了其他区域中现有的偏差。探索了驱动偏差变化的动力学机制。