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Hydrology and Earth System Sciences An interactive open-access journal of the European Geosciences Union
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Volume 15, issue 3
Hydrol. Earth Syst. Sci., 15, 1065–1079, 2011
https://doi.org/10.5194/hess-15-1065-2011
© Author(s) 2011. This work is distributed under
the Creative Commons Attribution 3.0 License.
Hydrol. Earth Syst. Sci., 15, 1065–1079, 2011
https://doi.org/10.5194/hess-15-1065-2011
© Author(s) 2011. This work is distributed under
the Creative Commons Attribution 3.0 License.

Research article 28 Mar 2011

Research article | 28 Mar 2011

Climate model bias correction and the role of timescales

J. O. Haerter1, S. Hagemann1, C. Moseley1, and C. Piani2 J. O. Haerter et al.
  • 1Max Planck Institute for Meteorology, Hamburg, Germany
  • 2Abdus Salam International Centre for Theoretical Physics, Trieste, Italy

Abstract. It is well known that output from climate models cannot be used to force hydrological simulations without some form of preprocessing to remove the existing biases. In principle, statistical bias correction methodologies act on model output so the statistical properties of the corrected data match those of the observations. However, the improvements to the statistical properties of the data are limited to the specific timescale of the fluctuations that are considered. For example, a statistical bias correction methodology for mean daily temperature values might be detrimental to monthly statistics. Also, in applying bias corrections derived from present day to scenario simulations, an assumption is made on the stationarity of the bias over the largest timescales. First, we point out several conditions that have to be fulfilled by model data to make the application of a statistical bias correction meaningful. We then examine the effects of mixing fluctuations on different timescales and suggest an alternative statistical methodology, referred to here as a cascade bias correction method, that eliminates, or greatly reduces, the negative effects.

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