Articles | Volume 24, issue 6
https://doi.org/10.5194/hess-24-2963-2020
https://doi.org/10.5194/hess-24-2963-2020
Research article
 | 
08 Jun 2020
Research article |  | 08 Jun 2020

Bias in dynamically downscaled rainfall characteristics for hydroclimatic projections

Nicholas J. Potter, Francis H. S. Chiew, Stephen P. Charles, Guobin Fu, Hongxing Zheng, and Lu Zhang

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Cited articles

Addor, N. and Seibert, J.: Bias correction for hydrological impact studies – beyond the daily perspective, Hydrol. Process., 28, 4823–4828, https://doi.org/10.1002/hyp.10238, 2014. 
Andrys, J., Lyons, T. J., and Kal, J.: Evaluation of a WRF ensemble using GCM boundary conditions to quantify mean and extreme climate for the southwest of Western Australia (1970–1999), Intl. J. Climatol., 36, 4406–4424, https://doi.org/10.1002/joc.4641, 2016. 
Bárdossy, A. and Pegram, G.: Multiscale spatial recorrelation of RCM precipitation to produce unbiased climate change scenarios over large areas and small, Water Resour. Res., 48, W09502, https://doi.org/10.1029/2011WR011524, 2012. 
Bell, V. A. and Moore, R. J.: The sensitivity of catchment runoff models to rainfall data at different spatial scales, Hydrol. Earth Syst. Sci., 4, 653–667, https://doi.org/10.5194/hess-4-653-2000, 2000. 
Bennett, J. C., Grose, M. R., Corney, S. P., White, C. J., Holz, G. K., Katzfey, J. J., Post, D. A., and Bindoff, N. L.: Performance of an empirical bias-correction of a high-resolution climate dataset, Int. J. Climatol., 34, 2189–2204, https://doi.org/10.1002/joc.3830, 2014. 
Short summary
There is a growing need for information about possible changes to water resource availability in the future due to climate change. Large-scale outputs from global climate models need to be translated to finer-resolution spatial scales before hydrological modelling. Biases in this downscaled data often need to be corrected. We show that usual bias correction methods can retain residual biases in multi-day occurrences of rainfall, which can result in biases in modelled runoff.