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https://doi.org/10.5194/egusphere-2022-138
https://doi.org/10.5194/egusphere-2022-138
02 Aug 2022
 | 02 Aug 2022

An improved method of the Globally Resolved Energy Balance Model by the Bayes network

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

Abstract. This study introduces an improved method of the Globally Resolved Energy Balance Model(GREB) by the Bayes network. Starting from the climate elements relationship included in the GREB model, we reconstruct the model by the Bayes network to solve the problem of low model accuracy due to over-reliance on boundary conditions and initial conditions and the inability to use observed data for dynamic correction of model parameters. The improved model is applied to the simulation of surface average temperature and atmospheric average temperature based on the 3.75°×3.75° global data sets by Environmental Prediction (NCEP)/ National Center for Atmospheric Research(NCAR) from 1985 to 2014. The results illustrate that the improved model has higher average accuracy and lower spatial differentiation than the original GREB model. And the improved method provides a strong support for other dynamic model improvements.

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Journal article(s) based on this preprint

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
Geosci. Model Dev., 16, 2939–2955, https://doi.org/10.5194/gmd-16-2939-2023,https://doi.org/10.5194/gmd-16-2939-2023, 2023
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The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.

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This study introduces an improved method of the Globally Resolved Energy Balance Model by the...
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