Articles | Volume 15, issue 12
https://doi.org/10.5194/gmd-15-5021-2022
https://doi.org/10.5194/gmd-15-5021-2022
Model evaluation paper
 | 
01 Jul 2022
Model evaluation paper |  | 01 Jul 2022

Using a surrogate-assisted Bayesian framework to calibrate the runoff-generation scheme in the Energy Exascale Earth System Model (E3SM) v1

Donghui Xu, Gautam Bisht, Khachik Sargsyan, Chang Liao, and L. Ruby Leung

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Cited articles

Alkama, R., Decharme, B., Douville, H., and Ribes, A.: Trends in Global and Basin-Scale Runoff over the Late Twentieth Century: Methodological Issues and Sources of Uncertainty, J. Climate, 24, 3000–3014, https://doi.org/10.1175/2010JCLI3921.1, 2011. 
Alkama, R., Marchand, L., Ribes, A., and Decharme, B.: Detection of global runoff changes: results from observations and CMIP5 experiments, Hydrol. Earth Syst. Sci., 17, 2967–2979, https://doi.org/10.5194/hess-17-2967-2013, 2013. 
Andreadis, K. M., Schumann, G. J.-P., and Pavelsky, T.: A simple global river bankfull width and depth database, Water Resour. Res., 49, 7164–7168, https://doi.org/10.1002/wrcr.20440, 2013. 
Bechtold, B.: Violin Plots for Matlab, Github Project, Zenodo [code], https://doi.org/10.5281/zenodo.4559847, 2016. 
Beck, H. E., van Dijk, A. I. J. M., Miralles, D. G., de Jeu, R. A. M., Bruijnzeel, L. A., McVicar, T. R., and Schellekens, J.: Global patterns in base flow index and recession based on streamflow observations from 3394 catchments, Water Resour. Res., 49, 7843–7863, https://doi.org/10.1002/2013WR013918, 2013. 
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Short summary
The runoff outputs in Earth system model simulations involve high uncertainty, which needs to be constrained by parameter calibration. In this work, we used a surrogate-assisted Bayesian framework to efficiently calibrate the runoff-generation processes in the Energy Exascale Earth System Model v1 at a global scale. The model performance was improved compared to the default parameter after calibration, and the associated parametric uncertainty was significantly constrained.