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- Title
Climate model bias correction and the role of timescales.
- Authors
Haerter, J. O.; Hagemann, S.; Moseley, C.; Piani, C.
- 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.
- Subjects
CLIMATE change; HYDROLOGIC models; HYDROLOGY; PRECIPITATION anomalies; TIME series analysis; METHODOLOGY; DATA analysis
- Publication
Hydrology & Earth System Sciences, 2011, Vol 15, Issue 3, p1065
- ISSN
1027-5606
- Publication type
Article
- DOI
10.5194/hess-15-1065-2011