Articles | Volume 15
08 Jun 2018
 | 08 Jun 2018

Bias adjustment for threshold-based climate indicators

Peter Hoffmann, Christoph Menz, and Arne Spekat

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Cited articles

Cannon, A.: Multivariate Bias Correction of Climate Model Output: Matching Marginal Distributions and Intervariable Dependence Structure, J. Climate, 29, 7045–7064,, 2016. a
Chen, J., Brissette, F., and Lucas-Picher, P.: Assessing the limits of bias-correcting climate model outputs for climate change impact studies, J. Geophys. Res.-Atmos., 120, 1123–136,, 2015. a
Christensen, J., Boberg, F., Christensen, O., and Lucas-Picher, P.: On the need for bias correction of regional climate change projections of temperature and precipitation, Geophys. Res. Lett., 35, L20709,, 2008. a
Chun, K., Wheater, H., and Barr, A.: A multivariate comparison of the BERMS flux-tower climate observations and Canadian Coupled Global Climate Model (CGCM3) outputs, J. Hydrol., 519, 1537–1550,, 2014. a
Ehret, U., Zehe, E., Wulfmeyer, V., Warrach-Sagi, K., and Liebert, J.: HESS Opinions “Should we apply bias correction to global and regional climate model data?”, Hydrol. Earth Syst. Sci., 16, 3391–3404,, 2012. a
Short summary
The adjustment of bias, i.e., systematic errors, of climate models are a necessity when comparing results of an ensemble of these models. Usually, the meteorological parameters such as temperature or rainfall amounts themselves are subject to bias adjustments. We present a new method to apply bias adjustment to so-called climate indicators which are derived from those parameters, e.g., the number of days warmer than 30 °C or the number of days with more than 20 mm of rain.