Articles | Volume 21, issue 9
https://doi.org/10.5194/hess-21-4379-2017
https://doi.org/10.5194/hess-21-4379-2017
Research article
 | 
07 Sep 2017
Research article |  | 07 Sep 2017

The effect of GCM biases on global runoff simulations of a land surface model

Lamprini V. Papadimitriou, Aristeidis G. Koutroulis, Manolis G. Grillakis, and Ioannis K. Tsanis

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Cited articles

Best, M. J., Pryor, M., Clark, D. B., Rooney, G. G., Essery, R. L. H., Ménard, C. B., Edwards, J. M., Hendry, M. A., Porson, A., Gedney, N., Mercado, L. M., Sitch, S., Blyth, E., Boucher, O., Cox, P. M., Grimmond, C. S. B., and Harding, R. J.: The Joint UK Land Environment Simulator (JULES), model description – Part 1: Energy and water fluxes, Geosci. Model Dev., 4, 677–699, https://doi.org/10.5194/gmd-4-677-2011, 2011.
Blyth, E., Clark, D. B., Ellis, R., Huntingford, C., Los, S., Pryor, M., Best, M., and Sitch, S.: A comprehensive set of benchmark tests for a land surface model of simultaneous fluxes of water and carbon at both the global and seasonal scale, Geosci. Model Dev., 4, 255–269, https://doi.org/10.5194/gmd-4-255-2011, 2011.
Brikowski, T. H.: Applying multi-parameter runoff elasticity to assess water availability in a changing climate: An example from Texas, USA, Hydrol. Process., 29, 1746–1756, https://doi.org/10.1002/hyp.10297, 2015.
Bromwich, D. H., Otieno, F. O., Hines, K. M., Manning, K. W., and Shilo, E.: Comprehensive evaluation of polar weather research and forecasting model performance in the Antarctic, J. Geophys. Res.-Atmos., 118, 274–292, https://doi.org/10.1029/2012JD018139, 2013.
Christensen, J. H., Boberg, F., Christensen, O. B., and Lucas-Picher, P.: On the need for bias correction of regional climate change projections of temperature and precipitation, Geophys. Res. Lett., 35, L20709, https://doi.org/10.1029/2008GL035694, 2008.
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Bias correction of climate model outputs has become a standard procedure accompanying climate change impact studies. However, it introduces a new level of uncertainty in the modelling chain which remains relatively unexplored. In this work we present a new framework for the quantification and categorization of the effect of bias correction on global hydrological simulations and we derive information on the sensitivity and magnitude of the effect of GCM biases on runoff, at the global scale.
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