Articles | Volume 19, issue 10
https://doi.org/10.5194/hess-19-4055-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/hess-19-4055-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
The effect of empirical-statistical correction of intensity-dependent model errors on the temperature climate change signal
Wegener Center for Climate and Global Change (WegCenter), University of Graz, Graz, Austria
Central Institute for Meteorology and Geodynamics (ZAMG), Department of forecasting models, Vienna, Austria
M. Suklitsch
Central Institute for Meteorology and Geodynamics (ZAMG), Department of forecasting models, Vienna, Austria
G. Heinrich
Wegener Center for Climate and Global Change (WegCenter), University of Graz, Graz, Austria
now at: Department of Geography and Regional Science, University of Graz, Graz, Austria
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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.
The effect of empirical-statistical bias correction methods, like quantile mapping (QM), on the...