Articles | Volume 19, issue 10
https://doi.org/10.5194/hess-19-4055-2015
https://doi.org/10.5194/hess-19-4055-2015
Research article
 | 
06 Oct 2015
Research article |  | 06 Oct 2015

The effect of empirical-statistical correction of intensity-dependent model errors on the temperature climate change signal

A. Gobiet, M. Suklitsch, and G. Heinrich

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Short summary
The effect of empirical-statistical bias correction methods, like quantile mapping (QM), on the simulated climate change signals (CCS) is currently strongly discussed and is often regarded as deficiency of bias correction methods. We demonstrate that, quite the contrary, QM can lead to an improved CCS and also has the potential to serve as an empirical constraint on model uncertainty in climate projections.