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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Hydraulic redistribution (HR) is a passive process in which water can move between wet and dry regions in the root zone by flowing through plant root systems. In this modeling study, we showed that adding HR to a process-based model improved soil moisture predictions, particularly in the top 30 cm. HR rates declined with increasing rainfall magnitude and frequency, but HR rates were also influenced by the length of dry spells between rainfall events.
Kate Marvel, Benjamin Cook, Ensheng Weng, Ram Singh, and Edward Cook
Adv. Stat. Clim. Meteorol. Oceanogr., 12, 43–57, https://doi.org/10.5194/ascmo-12-43-2026, https://doi.org/10.5194/ascmo-12-43-2026, 2026
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Using information derived from tree-rings, we reconstruct possible combinations of past temperatures and precipitation amounts. This lets us put current changes in context and shows, for example, that the 1930s were likely the driest decade on record in central Kansas, while the late 20th century was likely the wettest period on record in the North American southwest.
Mazen Nakad, Mahmoud Mbarak, Jihad Karaki, Tehreem Qureshi, Matteo Detto, Benjamin I. Cook, Marcos Longo, Géraldine Derroire, Xiangtao Xu, Jeremy Lichstein, Zong-Liang Yang, Pierre Gentine, and Ensheng Weng
EGUsphere, https://doi.org/10.5194/egusphere-2026-145, https://doi.org/10.5194/egusphere-2026-145, 2026
This preprint is open for discussion and under review for Biogeosciences (BG).
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Because long-term drought and heat experiments are hard to run in tropical forests, we used a computer model to test how less rain and warmer, drier air affect forest growth and water loss at three sites. Forest productivity stayed stable until rainfall dropped below a threshold, but warmer air reduced carbon uptake even when soils were moist. Persistent heat and drought caused far larger declines than brief pulses, raising risks for future carbon storage.
Haodi Xu, Joshua Fan, Feng Tao, Lifen Jiang, Fengqi You, Benjamin Z. Houlton, Ying Sun, Carla P. Gomes, and Yiqi Luo
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Zhuoying Deng, Tingyu Li, Jinghua Chen, Shaoqiang Wang, Kun Huang, Peng Gu, Haoyu Peng, and Zhihui Chen
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2025-99, https://doi.org/10.5194/essd-2025-99, 2025
Preprint withdrawn
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We developed an efficient retrieval method and produced a long-term global SIF and ET dataset (0.1°, hourly, from 1982 to 2022), which has been validated using global EC flux towers and popular satellite products. Our dataset will provide new insights for monitoring the diurnal variations of carbon and water cycles and deepen our understanding of their changes over the past 40 years.
Hongkai Gao, Markus Hrachowitz, Lan Wang-Erlandsson, Fabrizio Fenicia, Qiaojuan Xi, Jianyang Xia, Wei Shao, Ge Sun, and Hubert H. G. Savenije
Hydrol. Earth Syst. Sci., 28, 4477–4499, https://doi.org/10.5194/hess-28-4477-2024, https://doi.org/10.5194/hess-28-4477-2024, 2024
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The concept of the root zone is widely used but lacks a precise definition. Its importance in Earth system science is not well elaborated upon. Here, we clarified its definition with several similar terms to bridge the multi-disciplinary gap. We underscore the key role of the root zone in the Earth system, which links the biosphere, hydrosphere, lithosphere, atmosphere, and anthroposphere. To better represent the root zone, we advocate for a paradigm shift towards ecosystem-centred modelling.
Song Wang, Carlos Sierra, Yiqi Luo, Jinsong Wang, Weinan Chen, Yahai Zhang, Aizhong Ye, and Shuli Niu
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Nitrogen is important for plant growth and carbon uptake, which is uaually limited in nature and can constrain carbon storage and impact efforts to combat climate change. We developed a new method of combining data and models to determine if and how much an ecosystem is nitrogen limited. This new method can help determine if and to what extent an ecosystem is nitrogen-limited, providing insight into nutrient limitations on a global scale and guiding ecosystem management decisions.
Ensheng Weng, Igor Aleinov, Ram Singh, Michael J. Puma, Sonali S. McDermid, Nancy Y. Kiang, Maxwell Kelley, Kevin Wilcox, Ray Dybzinski, Caroline E. Farrior, Stephen W. Pacala, and Benjamin I. Cook
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Xin Huang, Dan Lu, Daniel M. Ricciuto, Paul J. Hanson, Andrew D. Richardson, Xuehe Lu, Ensheng Weng, Sheng Nie, Lifen Jiang, Enqing Hou, Igor F. Steinmacher, and Yiqi Luo
Geosci. Model Dev., 14, 5217–5238, https://doi.org/10.5194/gmd-14-5217-2021, https://doi.org/10.5194/gmd-14-5217-2021, 2021
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In the data-rich era, data assimilation is widely used to integrate abundant observations into models to reduce uncertainty in ecological forecasting. However, applications of data assimilation are restricted by highly technical requirements. To alleviate this technical burden, we developed a model-independent data assimilation (MIDA) module which is friendly to ecologists with limited programming skills. MIDA also supports a flexible switch of different models or observations in DA analysis.
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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...
