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Title: Benchmarking carbon fluxes of the ISIMIP2a biome models

Abstract

The purpose of this study is to evaluate the eight ISIMIP2a biome models against independent estimates of long-term net carbon fluxes (i.e. Net Biome Productivity, NBP) over terrestrial ecosystems for the recent four decades (1971–2010). Here, we evaluate modeled global NBP against 1) the updated global residual land sink (RLS) plus land use emissions (E LUC) from the Global Carbon Project (GCP), presented as R + L in this study by Le Quéré et al (2015), and 2) the land CO 2 fluxes from two atmospheric inversion systems: Jena CarboScope s81_v3.8 and CAMS v15r2, referred to as F Jena and F CAMS respectively. The model ensemble-mean NBP (that includes seven models with land-use change) is higher than but within the uncertainty of R + L, while the simulated positive NBP trend over the last 30 yr is lower than that from R + L and from the two inversion systems. ISIMIP2a biome models well capture the interannual variation of global net terrestrial ecosystem carbon fluxes. Tropical NBP represents 31 ± 17% of global total NBP during the past decades, and the year-to-year variation of tropical NBP contributes most of the interannual variation of global NBP. According to the models, increasingmore » Net Primary Productivity (NPP) was the main cause for the generally increasing NBP. Significant global NBP anomalies from the long-term mean between the two phases of El Niño Southern Oscillation (ENSO) events are simulated by all models (p < 0.05), which is consistent with the R + L estimate (p = 0.06), also mainly attributed to NPP anomalies, rather than to changes in heterotrophic respiration (Rh). The global NPP and NBP anomalies during ENSO events are dominated by their anomalies in tropical regions impacted by tropical climate variability. Multiple regressions between R + L, F Jena and F CAMS interannual variations and tropical climate variations reveal a significant negative response of global net terrestrial ecosystem carbon fluxes to tropical mean annual temperature variation, and a non-significant response to tropical annual precipitation variation. According to the models, tropical precipitation is a more important driver, suggesting that some models do not capture the roles of precipitation and temperature changes adequately.« less

Authors:
 [1];  [2];  [3];  [4];  [5];  [6];  [2];  [7];  [8];  [9];  [9];  [8];  [10];  [11];  [6];  [12];  [11];  [13];  [14];  [4] more »;  [15];  [9];  [16];  [9];  [17];  [18];  [2];  [18];  [19];  [9] « less
  1. Laboratoire des Sciences du Climat et de l'Environnement (LSCE), Gif-sur-Yvette (France); Sorbonne Univ., Paris (France)
  2. Laboratoire des Sciences du Climat et de l'Environnement (LSCE), Gif-sur-Yvette (France)
  3. Laboratoire des Sciences du Climat et de l'Environnement (LSCE), Gif-sur-Yvette (France); Peking Univ., Beijing (China). College of Urban and Environmental Sciences, Sino-French Inst. of Earth System Sciences
  4. Peking Univ., Beijing (China). College of Urban and Environmental Sciences, Sino-French Inst. of Earth System Sciences
  5. Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Univ. of Maryland, College Park, MD (United States). Joint Global Change Research Inst.
  6. Univ. of Exeter (United Kingdom). College of Life and Environmental Sciences
  7. Univ. of Liege, (Belgium). Unit of Climate Modeling and Biogeochemical Cycles
  8. Univ. of Liege, (Belgium). Unit of Climate Modeling and Biogeochemical Cycles
  9. Potsdam Inst. for Climate Impact Research (Germany)
  10. Senckenberg Biodiversity and Climate Research Centre (BiK-F), Frankfurt (Germany); Goethe Univ., Frankfurt (Germany). Dept. of Physical Geography
  11. National Inst. for Environmental Studies, Tsukuba (Japan)
  12. Univ. of Liege, (Belgium). Lab. for Planetary and Atmospheric Physics (LPAP)
  13. Potsdam Inst. for Climate Impact Research (Germany); Humboldt Univ. of Berlin (Germany). Dept. of Geography
  14. Auburn Univ., AL (United States). School of Forestry and Wildlife Sciences, International Center for Climate and Global Change Research
  15. Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Univ. of Maryland, College Park, MD (United States). Joint Global Change Research Inst.
  16. Max Planck Inst. for Biogeochemistry, Jena (Germany)
  17. Senckenberg Biodiversity and Climate Research Centre (BiK-F), Frankfurt (Germany)
  18. Auburn Univ., AL (United States). School of Forestry and Wildlife Sciences, International Center for Climate and Global Change Research
  19. Univ. of Maryland, College Park, MD (United States). Dept. of Atmospheric and Oceanic Sciences
Publication Date:
Research Org.:
Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
Sponsoring Org.:
USDOE; National Aeronautic and Space Administration (NASA); National Science Foundation (NSF)
OSTI Identifier:
1353313
Report Number(s):
PNNL-SA-125310
Journal ID: ISSN 1748-9326
Grant/Contract Number:
AC05-76RL01830; NNX14AO73G; NNX14AF93G
Resource Type:
Journal Article: Accepted Manuscript
Journal Name:
Environmental Research Letters
Additional Journal Information:
Journal Volume: 12; Journal Issue: 4; Journal ID: ISSN 1748-9326
Publisher:
IOP Publishing
Country of Publication:
United States
Language:
English
Subject:
54 ENVIRONMENTAL SCIENCES; carbon fluxes; model evaluation; ENSO; terrestrial ecosystems; climate change; interannual variability; sensitivity

Citation Formats

Chang, Jinfeng, Ciais, Philippe, Wang, Xuhui, Piao, Shilong, Asrar, Ghassem, Betts, Richard, Chevallier, Frédéric, Dury, Marie, François, Louis, Frieler, Katja, Ros, Anselmo Garcia Cantu, Henrot, Alexandra-Jane, Hickler, Thomas, Ito, Akihiko, Morfopoulos, Catherine, Munhoven, Guy, Nishina, Kazuya, Ostberg, Sebastian, Pan, Shufen, Peng, Shushi, Rafique, Rashid, Reyer, Christopher, Rödenbeck, Christian, Schaphoff, Sibyll, Steinkamp, Jörg, Tian, Hanqin, Viovy, Nicolas, Yang, Jia, Zeng, Ning, and Zhao, Fang. Benchmarking carbon fluxes of the ISIMIP2a biome models. United States: N. p., 2017. Web. doi:10.1088/1748-9326/aa63fa.
Chang, Jinfeng, Ciais, Philippe, Wang, Xuhui, Piao, Shilong, Asrar, Ghassem, Betts, Richard, Chevallier, Frédéric, Dury, Marie, François, Louis, Frieler, Katja, Ros, Anselmo Garcia Cantu, Henrot, Alexandra-Jane, Hickler, Thomas, Ito, Akihiko, Morfopoulos, Catherine, Munhoven, Guy, Nishina, Kazuya, Ostberg, Sebastian, Pan, Shufen, Peng, Shushi, Rafique, Rashid, Reyer, Christopher, Rödenbeck, Christian, Schaphoff, Sibyll, Steinkamp, Jörg, Tian, Hanqin, Viovy, Nicolas, Yang, Jia, Zeng, Ning, & Zhao, Fang. Benchmarking carbon fluxes of the ISIMIP2a biome models. United States. doi:10.1088/1748-9326/aa63fa.
Chang, Jinfeng, Ciais, Philippe, Wang, Xuhui, Piao, Shilong, Asrar, Ghassem, Betts, Richard, Chevallier, Frédéric, Dury, Marie, François, Louis, Frieler, Katja, Ros, Anselmo Garcia Cantu, Henrot, Alexandra-Jane, Hickler, Thomas, Ito, Akihiko, Morfopoulos, Catherine, Munhoven, Guy, Nishina, Kazuya, Ostberg, Sebastian, Pan, Shufen, Peng, Shushi, Rafique, Rashid, Reyer, Christopher, Rödenbeck, Christian, Schaphoff, Sibyll, Steinkamp, Jörg, Tian, Hanqin, Viovy, Nicolas, Yang, Jia, Zeng, Ning, and Zhao, Fang. Tue . "Benchmarking carbon fluxes of the ISIMIP2a biome models". United States. doi:10.1088/1748-9326/aa63fa. https://www.osti.gov/servlets/purl/1353313.
@article{osti_1353313,
title = {Benchmarking carbon fluxes of the ISIMIP2a biome models},
author = {Chang, Jinfeng and Ciais, Philippe and Wang, Xuhui and Piao, Shilong and Asrar, Ghassem and Betts, Richard and Chevallier, Frédéric and Dury, Marie and François, Louis and Frieler, Katja and Ros, Anselmo Garcia Cantu and Henrot, Alexandra-Jane and Hickler, Thomas and Ito, Akihiko and Morfopoulos, Catherine and Munhoven, Guy and Nishina, Kazuya and Ostberg, Sebastian and Pan, Shufen and Peng, Shushi and Rafique, Rashid and Reyer, Christopher and Rödenbeck, Christian and Schaphoff, Sibyll and Steinkamp, Jörg and Tian, Hanqin and Viovy, Nicolas and Yang, Jia and Zeng, Ning and Zhao, Fang},
abstractNote = {The purpose of this study is to evaluate the eight ISIMIP2a biome models against independent estimates of long-term net carbon fluxes (i.e. Net Biome Productivity, NBP) over terrestrial ecosystems for the recent four decades (1971–2010). Here, we evaluate modeled global NBP against 1) the updated global residual land sink (RLS) plus land use emissions (ELUC) from the Global Carbon Project (GCP), presented as R + L in this study by Le Quéré et al (2015), and 2) the land CO2 fluxes from two atmospheric inversion systems: Jena CarboScope s81_v3.8 and CAMS v15r2, referred to as FJena and FCAMS respectively. The model ensemble-mean NBP (that includes seven models with land-use change) is higher than but within the uncertainty of R + L, while the simulated positive NBP trend over the last 30 yr is lower than that from R + L and from the two inversion systems. ISIMIP2a biome models well capture the interannual variation of global net terrestrial ecosystem carbon fluxes. Tropical NBP represents 31 ± 17% of global total NBP during the past decades, and the year-to-year variation of tropical NBP contributes most of the interannual variation of global NBP. According to the models, increasing Net Primary Productivity (NPP) was the main cause for the generally increasing NBP. Significant global NBP anomalies from the long-term mean between the two phases of El Niño Southern Oscillation (ENSO) events are simulated by all models (p < 0.05), which is consistent with the R + L estimate (p = 0.06), also mainly attributed to NPP anomalies, rather than to changes in heterotrophic respiration (Rh). The global NPP and NBP anomalies during ENSO events are dominated by their anomalies in tropical regions impacted by tropical climate variability. Multiple regressions between R + L, FJena and FCAMS interannual variations and tropical climate variations reveal a significant negative response of global net terrestrial ecosystem carbon fluxes to tropical mean annual temperature variation, and a non-significant response to tropical annual precipitation variation. According to the models, tropical precipitation is a more important driver, suggesting that some models do not capture the roles of precipitation and temperature changes adequately.},
doi = {10.1088/1748-9326/aa63fa},
journal = {Environmental Research Letters},
number = 4,
volume = 12,
place = {United States},
year = {Tue Mar 28 00:00:00 EDT 2017},
month = {Tue Mar 28 00:00:00 EDT 2017}
}

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