Underestimated Interannual Variability of Terrestrial Vegetation Production by Terrestrial Ecosystem Models

Author:

Lin Shangrong12ORCID,Hu Zhongmin23ORCID,Wang Yingping4ORCID,Chen Xiuzhi12ORCID,He Bin5ORCID,Song Zhaoliang6ORCID,Sun Shaobo6ORCID,Wu Chaoyang7ORCID,Zheng Yi12,Xia Xiaosheng1ORCID,Liu Liyang8,Tang Jing910ORCID,Sun Qing11ORCID,Joos Fortunat11,Yuan Wenping12ORCID

Affiliation:

1. School of Atmospheric Sciences Guangdong Province Data Center of Terrestrial and Marine Ecosystems Carbon Cycle Sun Yat‐sen University Zhuhai China

2. Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai) Guangdong China

3. College of Ecology and Environment Hainan University Haikou China

4. CSIRO, Oceans and Atmosphere VIC Aspendale Australia

5. College of Global Change and Earth System Science Beijing Normal University Beijing China

6. Institute of Surface‐Earth System Science School of Earth System Science Tianjin University Tianjin China

7. The Key Laboratory of Land Surface Pattern and Simulation Institute of Geographical Sciences and Natural Resources Research Chinese Academy of Sciences Beijing China

8. Laboratoire des Sciences du Climat et de l’Environnement IPSL CEA‐CNRS‐UVSQ Université Paris‐Saclay Gif‐sur‐Yvette France

9. Department of Physical Geography and Ecosystem Science Lund University Lund Sweden

10. Department of Biology University of Copenhagen Copenhagen Denmark

11. Climate and Environmental Physics Physics Institute University of Bern Bern Switzerland

Abstract

AbstractVegetation gross primary production (GPP) is the largest terrestrial carbon flux and plays an important role in regulating the carbon sink. Current terrestrial ecosystem models (TEMs) are indispensable tools for evaluating and predicting GPP. However, to which degree the TEMs can capture the interannual variability (IAV) of GPP remains unclear. With large data sets of remote sensing, in situ observations, and predictions of TEMs at a global scale, this study found that the current TEMs substantially underestimate the GPP IAV in comparison to observations at global flux towers. Our results also showed the larger underestimations of IAV in GPP at nonforest ecosystem types than forest types, especially in arid and semiarid grassland and shrubland. One cause of the underestimation is that the IAV in GPP predicted by models is strongly dependent on canopy structure, that is, leaf area index (LAI), and the models underestimate the changes of canopy physiology responding to climate change. On the other hand, the simulated interannual variations of LAI are much less than the observed. Our results highlight the importance of improving TEMs by precisely characterizing the contribution of canopy physiological changes on the IAV in GPP and of clarifying the reason for the underestimated IAV in LAI. With these efforts, it may be possible to accurately predict the IAV in GPP and the stability of the global carbon sink in the context of global climate change.

Funder

China National Funds for Distinguished Young Scientists

National Natural Science Foundation of China

Publisher

American Geophysical Union (AGU)

Subject

Atmospheric Science,General Environmental Science,Environmental Chemistry,Global and Planetary Change

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