Articles | Volume 18, issue 20
https://doi.org/10.5194/gmd-18-7545-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-18-7545-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model description paper
| 
22 Oct 2025
Model description paper |
| 22 Oct 2025
| 22 Oct 2025
TECO-CNP Sv1.0: a coupled carbon-nitrogen-phosphorus model with data assimilation for subtropical forests
Fangxiu Wan
Zhejiang Tiantong Forest Ecosystem National Observation and Research Station, Research Center for Global Change and Ecological Forecasting, School of Ecological and Environmental Sciences, Institute of Eco-Chongming, East China Normal University, Shanghai, China
Chenyu Bian
Zhejiang Tiantong Forest Ecosystem National Observation and Research Station, Research Center for Global Change and Ecological Forecasting, School of Ecological and Environmental Sciences, Institute of Eco-Chongming, East China Normal University, Shanghai, China
Ensheng Weng
Center for Climate Systems Research, Columbia University, New York, NY 10964, USA
Yiqi Luo
School of Integrative Plant Science, College of Agriculture and Life Sciences, Cornell University, Ithaca, NY 14853, USA
Kun Huang
Zhejiang Tiantong Forest Ecosystem National Observation and Research Station, Research Center for Global Change and Ecological Forecasting, School of Ecological and Environmental Sciences, Institute of Eco-Chongming, East China Normal University, Shanghai, China
Jianyang Xia
CORRESPONDING AUTHOR
Zhejiang Tiantong Forest Ecosystem National Observation and Research Station, Research Center for Global Change and Ecological Forecasting, School of Ecological and Environmental Sciences, Institute of Eco-Chongming, East China Normal University, Shanghai, China
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Short summary
We developed TECO-CNP Sv1.0, a coupled carbon-nitrogen-phosphorus model with data assimilation for subtropical forests. The model effectively captures observed carbon, nitrogen, and phosphorus pools and fluxes, and significantly improves carbon flux estimates through data assimilation. TECO-CNP provides enhanced biogeochemical cycle representations, enabling more reliable predictions of ecosystem carbon cycle responses to global change through efficient parameter optimization.
We developed TECO-CNP Sv1.0, a coupled carbon-nitrogen-phosphorus model with data assimilation...
