Articles | Volume 16, issue 4
https://doi.org/10.5194/bg-16-917-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/bg-16-917-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
27 Feb 2019
Research article |
| 27 Feb 2019
| 27 Feb 2019
Evaluating the simulated mean soil carbon transit times by Earth system models using observations
Jing Wang
Zhejiang Tiantong Forest Ecosystem National Observation and Research
Station, Shanghai Key Lab for Urban Ecological Processes and
Eco-Restoration, School of Ecological and Environmental Sciences, East China
Normal University, Shanghai 200241, China
Jianyang Xia
CORRESPONDING AUTHOR
Zhejiang Tiantong Forest Ecosystem National Observation and Research
Station, Shanghai Key Lab for Urban Ecological Processes and
Eco-Restoration, School of Ecological and Environmental Sciences, East China
Normal University, Shanghai 200241, China
State Key Laboratory of Estuarine and Coastal Research, Research
Center for Global Change and Ecological Forecasting, East China Normal
University, Shanghai 200241, China
Xuhui Zhou
Zhejiang Tiantong Forest Ecosystem National Observation and Research
Station, Shanghai Key Lab for Urban Ecological Processes and
Eco-Restoration, School of Ecological and Environmental Sciences, East China
Normal University, Shanghai 200241, China
State Key Laboratory of Estuarine and Coastal Research, Research
Center for Global Change and Ecological Forecasting, East China Normal
University, Shanghai 200241, China
Kun Huang
Zhejiang Tiantong Forest Ecosystem National Observation and Research
Station, Shanghai Key Lab for Urban Ecological Processes and
Eco-Restoration, School of Ecological and Environmental Sciences, East China
Normal University, Shanghai 200241, China
Jian Zhou
Zhejiang Tiantong Forest Ecosystem National Observation and Research
Station, Shanghai Key Lab for Urban Ecological Processes and
Eco-Restoration, School of Ecological and Environmental Sciences, East China
Normal University, Shanghai 200241, China
Yuanyuan Huang
Laboratoire des Sciences du Climat et de l'Environnement, 91191
Gif-sur-Yvette, France
Lifen Jiang
Center for ecosystem science and society, Northern Arizona University,
Arizona, Flagstaff, AZ 86011, USA
Xia Xu
College of Biology and the Environment, Nanjing Forestry University,
Nanjing 210037, China
Junyi Liang
Environmental Sciences Division & Climate Change Science Institute,
Oak Ridge National Laboratory, Oak Ridge, Tennessee 37830, USA
Ying-Ping Wang
CSIRO Ocean and Atmosphere, PMB 1, Aspendale, Victoria 3195,
Australia
Xiaoli Cheng
Wuhan Botanical Garden, Chinese Academy of Sciences, Wuhan 430074,
Hubei Province, China
Center for ecosystem science and society, Northern Arizona University,
Arizona, Flagstaff, AZ 86011, USA
Department of Earth System Science, Tsinghua University, Beijing
100084, China
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Cited
10 citations as recorded by crossref.
- A traceability analysis system for model evaluation on land carbon dynamics: design and applications J. Zhou et al. 10.1186/s13717-021-00281-w
- Divergent future trends in global land greening and carbon sequestration under climate change scenarios C. Bian & J. Xia 10.1088/1748-9326/ad8508
- Comparing machine learning-derived global estimates of soil respiration and its components with those from terrestrial ecosystem models H. Lu et al. 10.1088/1748-9326/abf526
- Inner Mongolia grasslands act as a weak regional carbon sink: A new estimation based on upscaling eddy covariance observations C. You et al. 10.1016/j.agrformet.2023.109719
- Compartment Models with Memory T. Ginn & L. Schreyer 10.1137/21M1437160
- Emergent Climatic Controls on Soil Carbon Turnover and Its Variability in Warm Climates H. Huang et al. 10.1029/2023GL105291
- Uncertainty and Emergent Constraints on Enhanced Ecosystem Carbon Stock by Land Greening C. Bian et al. 10.1029/2022MS003397
- Biotic and Abiotic Factors Controlling Spatial Variation of Mean Carbon Turnover Time in Forest Soil J. Wang et al. 10.1029/2023JG007438
- Depth-dependent soil C-N-P stoichiometry in a mature subtropical broadleaf forest Y. Qiao et al. 10.1016/j.geoderma.2020.114357
- Nutrient Limitations Lead to a Reduced Magnitude of Disequilibrium in the Global Terrestrial Carbon Cycle N. Wei et al. 10.1029/2021JG006764
10 citations as recorded by crossref.
- A traceability analysis system for model evaluation on land carbon dynamics: design and applications J. Zhou et al. 10.1186/s13717-021-00281-w
- Divergent future trends in global land greening and carbon sequestration under climate change scenarios C. Bian & J. Xia 10.1088/1748-9326/ad8508
- Comparing machine learning-derived global estimates of soil respiration and its components with those from terrestrial ecosystem models H. Lu et al. 10.1088/1748-9326/abf526
- Inner Mongolia grasslands act as a weak regional carbon sink: A new estimation based on upscaling eddy covariance observations C. You et al. 10.1016/j.agrformet.2023.109719
- Compartment Models with Memory T. Ginn & L. Schreyer 10.1137/21M1437160
- Emergent Climatic Controls on Soil Carbon Turnover and Its Variability in Warm Climates H. Huang et al. 10.1029/2023GL105291
- Uncertainty and Emergent Constraints on Enhanced Ecosystem Carbon Stock by Land Greening C. Bian et al. 10.1029/2022MS003397
- Biotic and Abiotic Factors Controlling Spatial Variation of Mean Carbon Turnover Time in Forest Soil J. Wang et al. 10.1029/2023JG007438
- Depth-dependent soil C-N-P stoichiometry in a mature subtropical broadleaf forest Y. Qiao et al. 10.1016/j.geoderma.2020.114357
- Nutrient Limitations Lead to a Reduced Magnitude of Disequilibrium in the Global Terrestrial Carbon Cycle N. Wei et al. 10.1029/2021JG006764
Latest update: 03 Nov 2024
Short summary
Soil is critical in mitigating climate change mainly because soil carbon turns over much slower in soils than vegetation and the atmosphere. However, Earth system models (ESMs) have large uncertainty in simulating carbon dynamics due to their biased estimation of soil carbon transit time (τsoil). Here, the τsoil estimates from 12 ESMs that participated in CMIP5 were evaluated by a database of measured τsoil. We detected a large spatial variation in measured τsoil across the globe.
Soil is critical in mitigating climate change mainly because soil carbon turns over much slower...
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