Articles | Volume 23, issue 10
Hydrol. Earth Syst. Sci., 23, 4033–4050, 2019
https://doi.org/10.5194/hess-23-4033-2019
Hydrol. Earth Syst. Sci., 23, 4033–4050, 2019
https://doi.org/10.5194/hess-23-4033-2019
Research article
30 Sep 2019
Research article | 30 Sep 2019

Does the weighting of climate simulations result in a better quantification of hydrological impacts?

Hui-Min Wang et al.

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Cited articles

Abramowitz, G., Herger, N., Gutmann, E., Hammerling, D., Knutti, R., Leduc, M., Lorenz, R., Pincus, R., and Schmidt, G. A.: ESD Reviews: Model dependence in multi-model climate ensembles: weighting, sub-selection and out-of-sample testing, Earth Syst. Dynam. 10, 91–105, https://doi.org/10.5194/esd-10-91-2019, 2019. 
Alder, J. R. and Hostetler, S. W.: The Dependence of Hydroclimate Projections in Snow-Dominated Regions of the Western United States on the Choice of Statistically Downscaled Climate Data, Water Resour. Res., 55, 2279–2300, https://doi.org/10.1029/2018wr023458, 2019. 
Arsenault, R., Gatien, P., Renaud, B., Brissette, F., and Martel, J.-L.: A comparative analysis of 9 multi-model averaging approaches in hydrological continuous streamflow simulation, J. Hydrol., 529, 754–767, https://doi.org/10.1016/j.jhydrol.2015.09.001, 2015. 
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Short summary
When using large ensembles of global climate models in hydrological impact studies, there are pragmatic questions on whether it is necessary to weight climate models and how to weight them. We use eight methods to weight climate models straightforwardly, based on their performances in hydrological simulations, and investigate the influences of the assigned weights. This study concludes that using bias correction and equal weighting is likely viable and sufficient for hydrological impact studies.