Articles | Volume 17, issue 7
https://doi.org/10.5194/gmd-17-2509-2024
© Author(s) 2024. 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-17-2509-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Development and technical paper
| 
04 Apr 2024
Development and technical paper |
| 04 Apr 2024
| 04 Apr 2024
A new temperature–photoperiod coupled phenology module in LPJ-GUESS model v4.1: optimizing estimation of terrestrial carbon and water processes
Shouzhi Chen
College of Water Sciences, Beijing Normal University, Beijing 100875, China
College of Water Sciences, Beijing Normal University, Beijing 100875, China
Plants and Ecosystems, Department of Biology, University of Antwerp, Antwerp, Belgium
Mingwei Li
College of Water Sciences, Beijing Normal University, Beijing 100875, China
Zitong Jia
College of Water Sciences, Beijing Normal University, Beijing 100875, China
Yishuo Cui
College of Water Sciences, Beijing Normal University, Beijing 100875, China
Center for Volatile Interactions, Department of Biology, University of Copenhagen, Copenhagen, Denmark
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Cited
15 citations as recorded by crossref.
- Advanced multi-temporal analyses reveal solar radiation as an underappreciated driver of vegetation green-up across African ecosystems A. Yawe et al. https://doi.org/10.1016/j.gloplacha.2026.105667
- Effect of growing season length on gross primary productivity increased in the Jinsha River watershed M. Li et al. https://doi.org/10.1093/jpe/rtae108
- Is spring break coming early? Effects of climate change on Alabama's native plant flowering phenology1 S. Zamora et al. https://doi.org/10.3159/TORREY-D-25-00013.1
- Spatiotemporal Variations in Vegetation Phenology in the Qinling Mountains and Their Responses to Climate Variability H. Li et al. https://doi.org/10.3390/rs17244051
- Threshold identification of vegetation coverage based on GAM M. Bai & F. Li https://doi.org/10.2166/hydro.2026.148
- Carbon Gain, Carbon Use, and Persistence: How Elevated CO₂ and Warming Reshape High‐Elevation Plants P. Nautiyal & M. Nautiyal https://doi.org/10.1111/pce.70533
- Advancing ecohydrological modelling: coupling LPJ-GUESS with ParFlow for integrated vegetation and surface-subsurface hydrology simulations Z. Jia et al. https://doi.org/10.5194/gmd-19-1727-2026
- Optimal canopy light-use strategy shapes global greenness dynamics Z. Zhu et al. https://doi.org/10.1038/s41467-026-76896-4
- A general physiologically driven representation of leaf turnover in grasslands in the QUINCY land surface model (revision: 974a6b7f) J. Seitz et al. https://doi.org/10.5194/gmd-19-8289-2026
- Age-specific timing of bud burst in subtropical Carya illinoinensis and Torreya grandis under current and future climatic conditions S. Diao et al. https://doi.org/10.1016/j.agrformet.2026.111264
- Asymmetric climate sensitivities reshape structural–functional spring phenology mismatch in Northern Hemisphere forests X. Sun et al. https://doi.org/10.1016/j.agrformet.2026.111337
- Data-model integration in global change manipulative experiments: progresses, challenges and future directions H. Lyu et al. https://doi.org/10.1093/jpe/rtag033
- Lengthened autumn growing season contributes substantially to Earth’s greening J. Tian et al. https://doi.org/10.1038/s41467-026-75885-x
- The impact of phenological shifts on carbon uptake across major terrestrial biomes G. Mulualem & J. Dash https://doi.org/10.1186/s13021-026-00450-4
- A vegetation phenology dataset developed by integrating multiple sources using the reliability ensemble averaging method Y. Cui et al. https://doi.org/10.5194/essd-17-4005-2025
15 citations as recorded by crossref.
- Advanced multi-temporal analyses reveal solar radiation as an underappreciated driver of vegetation green-up across African ecosystems A. Yawe et al. https://doi.org/10.1016/j.gloplacha.2026.105667
- Effect of growing season length on gross primary productivity increased in the Jinsha River watershed M. Li et al. https://doi.org/10.1093/jpe/rtae108
- Is spring break coming early? Effects of climate change on Alabama's native plant flowering phenology1 S. Zamora et al. https://doi.org/10.3159/TORREY-D-25-00013.1
- Spatiotemporal Variations in Vegetation Phenology in the Qinling Mountains and Their Responses to Climate Variability H. Li et al. https://doi.org/10.3390/rs17244051
- Threshold identification of vegetation coverage based on GAM M. Bai & F. Li https://doi.org/10.2166/hydro.2026.148
- Carbon Gain, Carbon Use, and Persistence: How Elevated CO₂ and Warming Reshape High‐Elevation Plants P. Nautiyal & M. Nautiyal https://doi.org/10.1111/pce.70533
- Advancing ecohydrological modelling: coupling LPJ-GUESS with ParFlow for integrated vegetation and surface-subsurface hydrology simulations Z. Jia et al. https://doi.org/10.5194/gmd-19-1727-2026
- Optimal canopy light-use strategy shapes global greenness dynamics Z. Zhu et al. https://doi.org/10.1038/s41467-026-76896-4
- A general physiologically driven representation of leaf turnover in grasslands in the QUINCY land surface model (revision: 974a6b7f) J. Seitz et al. https://doi.org/10.5194/gmd-19-8289-2026
- Age-specific timing of bud burst in subtropical Carya illinoinensis and Torreya grandis under current and future climatic conditions S. Diao et al. https://doi.org/10.1016/j.agrformet.2026.111264
- Asymmetric climate sensitivities reshape structural–functional spring phenology mismatch in Northern Hemisphere forests X. Sun et al. https://doi.org/10.1016/j.agrformet.2026.111337
- Data-model integration in global change manipulative experiments: progresses, challenges and future directions H. Lyu et al. https://doi.org/10.1093/jpe/rtag033
- Lengthened autumn growing season contributes substantially to Earth’s greening J. Tian et al. https://doi.org/10.1038/s41467-026-75885-x
- The impact of phenological shifts on carbon uptake across major terrestrial biomes G. Mulualem & J. Dash https://doi.org/10.1186/s13021-026-00450-4
- A vegetation phenology dataset developed by integrating multiple sources using the reliability ensemble averaging method Y. Cui et al. https://doi.org/10.5194/essd-17-4005-2025
Saved (final revised paper)
Latest update: 15 Oct 2026
Short summary
It is still a challenge to achieve an accurate simulation of vegetation phenology in the dynamic global vegetation models (DGVMs). We implemented and coupled the spring and autumn phenology models into one of the DGVMs, LPJ-GUESS, and substantially improved the accuracy in capturing the start and end dates of growing seasons. Our study highlights the importance of getting accurate phenology estimations to reduce the uncertainties in plant distribution and terrestrial carbon and water cycling.
It is still a challenge to achieve an accurate simulation of vegetation phenology in the dynamic...
