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Are Terrestrial Biosphere Models Fit for Simulating the Global Land Carbon Sink?

Journal Article · · Journal of Advances in Modeling Earth Systems
DOI:https://doi.org/10.1029/2021ms002946· OSTI ID:1871882
 [1];  [1];  [2];  [3];  [3];  [4];  [5];  [6];  [7];  [8];  [9];  [10];  [11];  [12];  [13];  [14];  [15];  [16]
  1. Environment and Climate Change Canada, Victoria, BC (Canada). Climate Processes Section
  2. Environment and Climate Change Canada, Victoria, BC (Canada). Canadian Centre for Climate Modelling and Analysis
  3. Univ. of Exeter (United Kingdom)
  4. Karlsruhe Inst. of Technology, Garmisch‐Partenkirchen (Germany). Inst. of Meteorology and Climate Research
  5. Laboratoire des Sciences du Climat et de l’Environnement, Gif-sur-Yvette (France)
  6. Univ. of Illinois at Urbana-Champaign, IL (United States)
  7. Université de Toulouse (France); French National Research Institute for Agriculture, Food and Environment (INRAE), Champenoux (France)
  8. Univ. of Bern (Switzerland), Physics Inst., Oeschger Centre for Climate Change Research
  9. National Center for Atmospheric Research (NCAR), Boulder, CO (United States)
  10. Vrije Univ., Amsterdam (Netherlands)
  11. Max Planck Institute for Meteorology, Hamburg (Germany)
  12. Auburn Univ., AL (United States)
  13. Univ. Paris-Saclay, Gif-sur-Yvette (France). Laboratoire des Sciences du Climat et de l’Environnement
  14. Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Climate Change Science Inst.
  15. Sun Yat-sen Univ., Zhuhai (China). Key Laboratory for Climate Change and Natural Disaster Studies, Zhuhai Key Laboratory of Dynamics Urban Climate and Ecology
  16. Max Planck Institute for Biogeochemistry, Jena (Germany)
+ Show Author Affiliations
The Global Carbon Project estimates that the terrestrial biosphere has absorbed about one-third of anthropogenic CO2 emissions during the 1959–2019 period. This sink-estimate is produced by an ensemble of terrestrial biosphere models and is consistent with the land uptake inferred from the residual of emissions and ocean uptake. The purpose of our study is to understand how well terrestrial biosphere models reproduce the processes that drive the terrestrial carbon sink. One challenge is to decide what level of agreement between model output and observation-based reference data is adequate considering that reference data are prone to uncertainties. To define such a level of agreement, we compute benchmark scores that quantify the similarity between independently derived reference data sets using multiple statistical metrics. Models are considered to perform well if their model scores reach benchmark scores. Our results show that reference data can differ considerably, causing benchmark scores to be low. Model scores are often of similar magnitude as benchmark scores, implying that model performance is reasonable given how different reference data are. While model performance is encouraging, ample potential for improvements remains, including a reduction in a positive leaf area index bias, improved representations of processes that govern soil organic carbon in high latitudes, and an assessment of causes that drive the inter-model spread of gross primary productivity in boreal regions and humid tropics. The success of future model development will increasingly depend on our capacity to reduce and account for observational uncertainties.
Research Organization:
Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)
Sponsoring Organization:
European Union Horizon 2020; USDOE Office of Science (SC), Biological and Environmental Research (BER)
Grant/Contract Number:
AC05-00OR22725
OSTI ID:
1871882
Journal Information:
Journal of Advances in Modeling Earth Systems, Journal Name: Journal of Advances in Modeling Earth Systems Journal Issue: 5 Vol. 14; ISSN 1942-2466
Publisher:
American Geophysical Union (AGU)Copyright Statement
Country of Publication:
United States
Language:
English

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Related Subjects

58 GEOSCIENCES
biogeochemical cycles, processes, and modeling
biosphere/atmosphere interactions
carbon cycling