 Despite significant progress in recent years, output from global and regional circulation models remains susceptible to biases that limit their direct use in climate change impact studies. To address these limitations, bias correction, BC, or the adjustment of model output toward observed data, has become a standard practice. However, current applications of BC methods can be questioned due to their lack of transparency and potential negative effects on model performance. This paper argues that BC should only be applied when there is evidence that it improves the accuracy of model output and that it should be done in a manner that preserves the underlying physics of the model. Furthermore, the authors suggest that more research needs to be conducted into the effectiveness of different BC techniques and that the end goal of reducing uncertainty in climate change predictions should be pursued through increasing model resolution and using ensemble prediction systems. This article was authored by J. Liebert, K. Warwick-Sagee, V. Wolfmeier, and others. We are article.tv, links in the description below.