Articles | Volume 30, issue 9
https://doi.org/10.5194/hess-30-2651-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-30-2651-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
06 May 2026
Research article |
| 06 May 2026
| 06 May 2026
Introducing the Model Fidelity Metric (MFM) for robust and diagnostic land surface model evaluation
Zezhen Wu
School of Mathematics (Zhuhai), Sun Yat-sen University, Zhuhai, China
Zhongwang Wei
CORRESPONDING AUTHOR
School of Atmospheric Sciences, Sun Yat-sen University, Zhuhai, China
Xingjie Lu
School of Atmospheric Sciences, Sun Yat-sen University, Zhuhai, China
Nan Wei
School of Atmospheric Sciences, Sun Yat-sen University, Zhuhai, China
Lu Li
School of Atmospheric Sciences, Sun Yat-sen University, Zhuhai, China
Shupeng Zhang
School of Atmospheric Sciences, Sun Yat-sen University, Zhuhai, China
Hua Yuan
School of Atmospheric Sciences, Sun Yat-sen University, Zhuhai, China
Shaofeng Liu
School of Atmospheric Sciences, Sun Yat-sen University, Zhuhai, China
Yongjiu Dai
CORRESPONDING AUTHOR
School of Atmospheric Sciences, Sun Yat-sen University, Zhuhai, China
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Earth Syst. Sci. Data, 17, 2535–2551, https://doi.org/10.5194/essd-17-2535-2025, https://doi.org/10.5194/essd-17-2535-2025, 2025
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Hydrol. Earth Syst. Sci., 29, 2201–2218, https://doi.org/10.5194/hess-29-2201-2025, https://doi.org/10.5194/hess-29-2201-2025, 2025
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Qingliang Li, Gaosong Shi, Wei Shangguan, Vahid Nourani, Jianduo Li, Lu Li, Feini Huang, Ye Zhang, Chunyan Wang, Dagang Wang, Jianxiu Qiu, Xingjie Lu, and Yongjiu Dai
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Yi Nan, Zhihua He, Fuqiang Tian, Zhongwang Wei, and Lide Tian
Hydrol. Earth Syst. Sci., 26, 4147–4167, https://doi.org/10.5194/hess-26-4147-2022, https://doi.org/10.5194/hess-26-4147-2022, 2022
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Ziqi Lin, Yongjiu Dai, Umakant Mishra, Guocheng Wang, Wei Shangguan, Wen Zhang, and Zhangcai Qin
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2022-232, https://doi.org/10.5194/essd-2022-232, 2022
Manuscript not accepted for further review
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Spatial soil organic carbon (SOC) data is critical for predictions in carbon climate feedbacks and future climate trends, but no conclusion has yet been reached on which dataset to be used for specific purposes. We evaluated the SOC estimates from five widely used global soil datasets and a regional permafrost dataset, and identify uncertainties of SOC estimates by region, biome, and data sources, hoping to help improve SOC/soil data in the future.
Shuang Ma, Lifen Jiang, Rachel M. Wilson, Jeff P. Chanton, Scott Bridgham, Shuli Niu, Colleen M. Iversen, Avni Malhotra, Jiang Jiang, Xingjie Lu, Yuanyuan Huang, Jason Keller, Xiaofeng Xu, Daniel M. Ricciuto, Paul J. Hanson, and Yiqi Luo
Biogeosciences, 19, 2245–2262, https://doi.org/10.5194/bg-19-2245-2022, https://doi.org/10.5194/bg-19-2245-2022, 2022
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The relative ratio of wetland methane (CH4) emission pathways determines how much CH4 is oxidized before leaving the soil. We found an ebullition modeling approach that has a better performance in deep layer pore water CH4 concentration. We suggest using this approach in land surface models to accurately represent CH4 emission dynamics and response to climate change. Our results also highlight that both CH4 flux and belowground concentration data are important to constrain model parameters.
Yaoping Wang, Jiafu Mao, Mingzhou Jin, Forrest M. Hoffman, Xiaoying Shi, Stan D. Wullschleger, and Yongjiu Dai
Earth Syst. Sci. Data, 13, 4385–4405, https://doi.org/10.5194/essd-13-4385-2021, https://doi.org/10.5194/essd-13-4385-2021, 2021
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We developed seven global soil moisture datasets (1970–2016, monthly, half-degree, and multilayer) by merging a wide range of data sources, including in situ and satellite observations, reanalysis, offline land surface model simulations, and Earth system model simulations. Given the great value of long-term, multilayer, gap-free soil moisture products to climate research and applications, we believe this paper and the presented datasets would be of interest to many different communities.
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Short summary
Land surface models simulate exchanges at the Earth's surface. Traditional evaluation methods can be misleading because they may hide errors or be overly sensitive to outliers. We introduce the Model Fidelity Metric, which measures model performance in terms of accuracy, variability and distribution similarity. Tests with synthetic data and real streamflow observations show that this metric provides more stable and informative assessments of model performance.
Land surface models simulate exchanges at the Earth's surface. Traditional evaluation methods...
