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Underestimated Interannual Variability of Terrestrial Vegetation Production by Terrestrial Ecosystem Models

Lin, Shangrong (author)
Sun Yat-sen University,Southern Marine Science and Engineering Guangdong Laboratory (Guangzhou)
Hu, Zhongmin (author)
Southern Marine Science and Engineering Guangdong Laboratory (Guangzhou),Hainan University
Wang, Yingping (author)
CSIRO Oceans and Atmosphere, Canberra
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Chen, Xiuzhi (author)
Southern Marine Science and Engineering Guangdong Laboratory (Guangzhou),Sun Yat-sen University
He, Bin (author)
Beijing Normal University
Song, Zhaoliang (author)
Tianjin University
Sun, Shaobo (author)
Tianjin University
Wu, Chaoyang (author)
Institute of Geographical Sciences and Natural Resources Research Chinese Academy of Sciences
Zheng, Yi (author)
Southern Marine Science and Engineering Guangdong Laboratory (Guangzhou),Sun Yat-sen University
Xia, Xiaosheng (author)
Sun Yat-sen University
Liu, Liyang (author)
University of Paris-Saclay
Tang, Jing (author)
Lund University,Lunds universitet,MERGE: ModElling the Regional and Global Earth system,Centrum för miljö- och klimatvetenskap (CEC),Naturvetenskapliga fakulteten,Institutionen för naturgeografi och ekosystemvetenskap,Centre for Environmental and Climate Science (CEC),Faculty of Science,Dept of Physical Geography and Ecosystem Science,University of Copenhagen
Sun, Qing (author)
University of Bern
Joos, Fortunat (author)
University of Bern
Yuan, Wenping (author)
Southern Marine Science and Engineering Guangdong Laboratory (Guangzhou),Sun Yat-sen University
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 (creator_code:org_t)
2023
2023
English.
In: Global Biogeochemical Cycles. - 0886-6236. ; 37:4
  • Journal article (peer-reviewed)
Abstract Subject headings
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  • Vegetation 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.

Subject headings

NATURVETENSKAP  -- Geovetenskap och miljövetenskap -- Naturgeografi (hsv//swe)
NATURAL SCIENCES  -- Earth and Related Environmental Sciences -- Physical Geography (hsv//eng)

Keyword

GPP
interannual variability
LAI
terrestrial ecosystem model

Publication and Content Type

art (subject category)
ref (subject category)

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