Geoscientific Model Development
Geoscientific Model Development
GMD
Articles | Volume 16, issue 10
Articles | Volume 16, issue 10
https://doi.org/10.5194/gmd-16-2939-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-16-2939-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 16, issue 10
Methods for assessment of models
 | 
30 May 2023
Methods for assessment of models |  | 30 May 2023

An improved method of the Globally Resolved Energy Balance model by the Bayesian networks

Zhenxia Liu, Zengjie Wang, Jian Wang, Zhengfang Zhang, Dongshuang Li, Zhaoyuan Yu, Linwang Yuan, and Wen Luo

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This preprint is open for discussion and under review for Geoscientific Model Development (GMD).
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Cited articles

Akgul, Y. S. and Kambhamettu, C.: A coarse-to-fine deformable contour optimization framework, IEEE T. Pattern Anal., 25, 174–186, 2003. a
Alley, R. B., Emanuel, K. A., and Zhang, F.: Advances in weather prediction, Science, 363, 342–344, https://doi.org/10.1126/science.aav7274, 2019. a
Annan, J. D. and Hargreaves, J. C.: Using multiple observationally-based constraints to estimate climate sensitivity, Geophys. Res. Lett., 33, L06704, https://doi.org/10.1029/2005GL025259, 2006. a
Bellprat, O. and Doblas-Reyes, F.: Attribution of extreme weather and climate events overestimated by unreliable climate simulations, Geophys. Res. Lett., 43, 2158–2164, https://doi.org/10.1002/2015GL067189, 2016. a
Berrocal, V. J., Craigmile, P. F., and Guttorp, P.: Regional climate model assessment using statistical upscaling and downscaling techniques, Environmetrics, 23, 482–492, https://doi.org/10.1002/env.2145, 2012. a
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This study introduces an improved method of the Globally Resolved Energy Balance (GREB) model by the Bayesian network. The improved method constructs a coarse–fine structure that combines a dynamical model with a statistical model based on employing the GREB model as the global framework and utilizing Bayesian networks as the local optimization. The results show that the improved model has better applicability and stability on a global scale and maintains good robustness on the timescale.
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