Articles | Volume 19, issue 1
https://doi.org/10.5194/gmd-19-57-2026
© Author(s) 2026. This work is distributed under the Creative Commons Attribution 4.0 License.
Model description paper
| 
06 Jan 2026
Model description paper |
| 06 Jan 2026
| 06 Jan 2026
NoahPy: a differentiable Noah land surface model for simulating permafrost thermo-hydrology
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This preprint is open for discussion and under review for Geoscientific Model Development (GMD).
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Cited articles
Abdelhamed, M. S., Elshamy, M. E., Razavi, S., and Wheater, H. S.: Challenges in Hydrologic-Land Surface Modeling of Permafrost Signatures – A Canadian Perspective, Journal of Advances in Modeling Earth Systems, 15, e2022MS003013, https://doi.org/10.1029/2022MS003013, 2023.
Asher, M. J., Croke, B. F. W., Jakeman, A. J., and Peeters, L. J. M.: A review of surrogate models and their application to groundwater modeling, Water Resources Research, 51, 5957–5973, https://doi.org/10.1002/2015WR016967, 2015.
Bi, K., Xie, L., Zhang, H., Chen, X., Gu, X., and Tian, Q.: Accurate medium-range global weather forecasting with 3D neural networks, Nature, 619, 533–538, https://doi.org/10.1038/s41586-023-06185-3, 2023.
Bonavita, M. and Laloyaux, P.: Machine Learning for Model Error Inference and Correction, Journal of Advances in Modeling Earth Systems, 12, e2020MS002232, https://doi.org/10.1029/2020MS002232, 2020.
Brandhorst, N. and Neuweiler, I.: Impact of parameter updates on soil moisture assimilation in a 3D heterogeneous hillslope model, Hydrology and Earth System Sciences, 27, 1301–1323, https://doi.org/10.5194/hess-27-1301-2023, 2023.
