Geoscientific Model Development
Geoscientific Model Development
GMD
Articles | Volume 19, issue 5
Articles | Volume 19, issue 5
https://doi.org/10.5194/gmd-19-2197-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-19-2197-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 19, issue 5
Model evaluation paper
 | 
17 Mar 2026
Model evaluation paper |  | 17 Mar 2026

Assessing and enhancing Noah-MP land surface modeling over tropical forests using machine learning techniques

Yanyan Cheng, Yaomin Wang, Kalli Furtado, Cenlin He, Fei Chen, Alan D. Ziegler, Song Chen, Matteo Detto, Yuna Mao, Baoxiang Pan, Yoshiko Kosugi, Marryanna Lion, Shoji Noguchi, Satoru Takanashi, Lulie Melling, and Baoqing Zhang

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Short summary
Tropical land surface processes shape the Earth's climate, but models often lack accuracy in the tropics due to limited data for validation. We improved the Noah with Multi-Parameterizations (Noah-MP) land surface model for the tropics using data from forests in Panama and Malaysia. Calibration enhanced simulations of energy and water fluxes, and revealed key vegetation and soil parameters, as well as future directions for model improvement in tropical regions.
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