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Title: Variability in the sensitivity among model simulations of permafrost and carbon dynamics in the permafrost region between 1960 and 2009

Abstract

A significant portion of the large amount of carbon (C) currently stored in soils of the permafrost region in the Northern Hemisphere has the potential to be emitted as the greenhouse gases CO2 and CH4 under a warmer climate. In this study we evaluated the variability in the sensitivity of permafrost and C in recent decades among land surface model simulations over the permafrost region between 1960 and 2009. The 15 model simulations all predict a loss of near-surface permafrost (within 3 m) area over the region, but there are large differences in the magnitude of the simulated rates of loss among the models (0.2 to 58.8 × 103 km2 yr–1). Sensitivity simulations indicated that changes in air temperature largely explained changes in permafrost area, although interactions among changes in other environmental variables also played a role. All of the models indicate that both vegetation and soil C storage together have increased by 156 to 954 Tg C yr–1 between 1960 and 2009 over the permafrost region even though model analyses indicate that warming alone would decrease soil C storage. Increases in gross primary production (GPP) largely explain the simulated increases in vegetation and soil C. The sensitivity of GPPmore » to increases in atmospheric CO2 was the dominant cause of increases in GPP across the models, but comparison of simulated GPP trends across the 1982–2009 period with that of a global GPP data set indicates that all of the models overestimate the trend in GPP. Disturbance also appears to be an important factor affecting C storage, as models that consider disturbance had lower increases in C storage than models that did not consider disturbance. Furthermore, to improve the modeling of C in the permafrost region, there is the need for the modeling community to standardize structural representation of permafrost and carbon dynamics among models that are used to evaluate the permafrost C feedback and for the modeling and observational communities to jointly develop data sets and methodologies to more effectively benchmark models.« less

Authors:
 [1];  [2];  [3];  [1];  [4];  [5];  [6];  [7];  [8];  [9];  [10];  [11];  [1];  [1];  [12];  [13];  [14];  [15];  [16];  [17] more »;  [18];  [16];  [5];  [19];  [14];  [7];  [20];  [21];  [22];  [23];  [15];  [20];  [1];  [24];  [10];  [24];  [15];  [14];  [25] « less
  1. Univ. of Alaska Fairbanks, Fairbanks, AK (United States)
  2. Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
  3. National Center for Atmospheric Research, Boulder, CO (United States)
  4. Normal Univ., Shanghai (China)
  5. Stockholm Univ., Stockholm (Sweden)
  6. Met Office Hadley Centre, Exeter (United Kingdom)
  7. Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
  8. Univ. of Washington, Seattle, WA (United States)
  9. Unite Mixte de Rechereche CNRS/Meteo-France (UMR 3589), Toulouse Cedex (France)
  10. Univ. of Colorado, Boulder, CO (United States)
  11. Univ. of Victoria, Victoria, BC (Canada)
  12. CEA-CNRS-UVSQ, Gif-sur-Yvette (France); Univ.-Grenoble Alpes/CNRS, Grenoble (France)
  13. Alfred Wegener Institute Helmholtz Centre for Polar and Marine Research, Potsdam (Germany); Beijing Normal Univ., Beijing (China)
  14. Japan Agency for Marine-Earth Science and Technology, Yokohama (Japan)
  15. Lund Univ., Lund (Sweden)
  16. GAME, Unite Mixte de Recherche CNRS/Meteo-France (UMR 3589), Toulouse Cedex (France)
  17. Arizona State Univ., Tempe, AZ (United States)
  18. CEA-CNRS-UVSQ, Gif-sur-Yvette (France)
  19. Univ.-Grenoble Alpes/CNRS, Grenoble (France); Irstea, Villeurbanne Cedex (France)
  20. Beijing Normal Univ., Beijing (China)
  21. Univ.-Grenoble Alpes/CNRS, Grenoble (France)
  22. Univ. of California, Los Angeles, CA (United States)
  23. Univ. of Oklahoma, Norman, OK (United States)
  24. Northern Arizona Univ., Flagstaff, AZ (United States)
  25. Purdue Univ., West Lafayette, IN (United States)
Publication Date:
Research Org.:
Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
Sponsoring Org.:
USDOE Office of Science (SC), Biological and Environmental Research (BER)
OSTI Identifier:
1324174
Alternate Identifier(s):
OSTI ID: 1439996
Grant/Contract Number:  
AC05-00OR22725; AC02-05CH11231
Resource Type:
Accepted Manuscript
Journal Name:
Global Biogeochemical Cycles
Additional Journal Information:
Journal Volume: 30; Journal Issue: 7; Journal ID: ISSN 0886-6236
Publisher:
American Geophysical Union (AGU)
Country of Publication:
United States
Language:
English
Subject:
58 GEOSCIENCES

Citation Formats

McGuire, A. David, Koven, Charles, Lawrence, David M., Clein, Joy S., Xia, Jiangyang, Beer, Christian, Burke, Eleanor, Chen, Guangsheng, Chen, Xiaodong, Delire, Christine, Jafarov, Elchin, MacDougall, Andrew H., Marchenko, Sergey, Nicolsky, Dmitry, Peng, Shushi, Rinke, Annette, Saito, Kazuyuki, Zhang, Wenxin, Alkama, Ramdane, Bohn, Theodore J., Ciais, Philippe, Decharme, Bertrand, Ekici, Altug, Gouttevin, Isabelle, Hajima, Tomohiro, Hayes, Daniel J., Ji, Duoying, Krinner, Gerhard, Lettenmaier, Dennis P., Luo, Yiqi, Miller, Paul A., Moore, John C., Romanovsky, Vladimir, Schädel, Christina, Schaefer, Kevin, Schuur, Edward A. G., Smith, Benjamin, Sueyoshi, Tetsuo, and Zhuang, Qianlai. Variability in the sensitivity among model simulations of permafrost and carbon dynamics in the permafrost region between 1960 and 2009. United States: N. p., 2016. Web. doi:10.1002/2016GB005405.
McGuire, A. David, Koven, Charles, Lawrence, David M., Clein, Joy S., Xia, Jiangyang, Beer, Christian, Burke, Eleanor, Chen, Guangsheng, Chen, Xiaodong, Delire, Christine, Jafarov, Elchin, MacDougall, Andrew H., Marchenko, Sergey, Nicolsky, Dmitry, Peng, Shushi, Rinke, Annette, Saito, Kazuyuki, Zhang, Wenxin, Alkama, Ramdane, Bohn, Theodore J., Ciais, Philippe, Decharme, Bertrand, Ekici, Altug, Gouttevin, Isabelle, Hajima, Tomohiro, Hayes, Daniel J., Ji, Duoying, Krinner, Gerhard, Lettenmaier, Dennis P., Luo, Yiqi, Miller, Paul A., Moore, John C., Romanovsky, Vladimir, Schädel, Christina, Schaefer, Kevin, Schuur, Edward A. G., Smith, Benjamin, Sueyoshi, Tetsuo, & Zhuang, Qianlai. Variability in the sensitivity among model simulations of permafrost and carbon dynamics in the permafrost region between 1960 and 2009. United States. doi:10.1002/2016GB005405.
McGuire, A. David, Koven, Charles, Lawrence, David M., Clein, Joy S., Xia, Jiangyang, Beer, Christian, Burke, Eleanor, Chen, Guangsheng, Chen, Xiaodong, Delire, Christine, Jafarov, Elchin, MacDougall, Andrew H., Marchenko, Sergey, Nicolsky, Dmitry, Peng, Shushi, Rinke, Annette, Saito, Kazuyuki, Zhang, Wenxin, Alkama, Ramdane, Bohn, Theodore J., Ciais, Philippe, Decharme, Bertrand, Ekici, Altug, Gouttevin, Isabelle, Hajima, Tomohiro, Hayes, Daniel J., Ji, Duoying, Krinner, Gerhard, Lettenmaier, Dennis P., Luo, Yiqi, Miller, Paul A., Moore, John C., Romanovsky, Vladimir, Schädel, Christina, Schaefer, Kevin, Schuur, Edward A. G., Smith, Benjamin, Sueyoshi, Tetsuo, and Zhuang, Qianlai. Fri . "Variability in the sensitivity among model simulations of permafrost and carbon dynamics in the permafrost region between 1960 and 2009". United States. doi:10.1002/2016GB005405. https://www.osti.gov/servlets/purl/1324174.
@article{osti_1324174,
title = {Variability in the sensitivity among model simulations of permafrost and carbon dynamics in the permafrost region between 1960 and 2009},
author = {McGuire, A. David and Koven, Charles and Lawrence, David M. and Clein, Joy S. and Xia, Jiangyang and Beer, Christian and Burke, Eleanor and Chen, Guangsheng and Chen, Xiaodong and Delire, Christine and Jafarov, Elchin and MacDougall, Andrew H. and Marchenko, Sergey and Nicolsky, Dmitry and Peng, Shushi and Rinke, Annette and Saito, Kazuyuki and Zhang, Wenxin and Alkama, Ramdane and Bohn, Theodore J. and Ciais, Philippe and Decharme, Bertrand and Ekici, Altug and Gouttevin, Isabelle and Hajima, Tomohiro and Hayes, Daniel J. and Ji, Duoying and Krinner, Gerhard and Lettenmaier, Dennis P. and Luo, Yiqi and Miller, Paul A. and Moore, John C. and Romanovsky, Vladimir and Schädel, Christina and Schaefer, Kevin and Schuur, Edward A. G. and Smith, Benjamin and Sueyoshi, Tetsuo and Zhuang, Qianlai},
abstractNote = {A significant portion of the large amount of carbon (C) currently stored in soils of the permafrost region in the Northern Hemisphere has the potential to be emitted as the greenhouse gases CO2 and CH4 under a warmer climate. In this study we evaluated the variability in the sensitivity of permafrost and C in recent decades among land surface model simulations over the permafrost region between 1960 and 2009. The 15 model simulations all predict a loss of near-surface permafrost (within 3 m) area over the region, but there are large differences in the magnitude of the simulated rates of loss among the models (0.2 to 58.8 × 103 km2 yr–1). Sensitivity simulations indicated that changes in air temperature largely explained changes in permafrost area, although interactions among changes in other environmental variables also played a role. All of the models indicate that both vegetation and soil C storage together have increased by 156 to 954 Tg C yr–1 between 1960 and 2009 over the permafrost region even though model analyses indicate that warming alone would decrease soil C storage. Increases in gross primary production (GPP) largely explain the simulated increases in vegetation and soil C. The sensitivity of GPP to increases in atmospheric CO2 was the dominant cause of increases in GPP across the models, but comparison of simulated GPP trends across the 1982–2009 period with that of a global GPP data set indicates that all of the models overestimate the trend in GPP. Disturbance also appears to be an important factor affecting C storage, as models that consider disturbance had lower increases in C storage than models that did not consider disturbance. Furthermore, to improve the modeling of C in the permafrost region, there is the need for the modeling community to standardize structural representation of permafrost and carbon dynamics among models that are used to evaluate the permafrost C feedback and for the modeling and observational communities to jointly develop data sets and methodologies to more effectively benchmark models.},
doi = {10.1002/2016GB005405},
journal = {Global Biogeochemical Cycles},
number = 7,
volume = 30,
place = {United States},
year = {2016},
month = {7}
}

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    Works referencing / citing this record:

    Uncertainties in coupled regional Arctic climate simulations associated with the used land surface model: Atmosphere and Permafrost in HIRHAM5-CLM4
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    • DOI: 10.1002/eap.1755

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    • Ecological Applications, Vol. 28, Issue 6
    • DOI: 10.1002/eap.1768

    Interactions Between Land-Use Change and Climate-Carbon Cycle Feedbacks
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    Statistical Forecasting of Current and Future Circum-Arctic Ground Temperatures and Active Layer Thickness
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    • Aalto, J.; Karjalainen, O.; Hjort, J.
    • Geophysical Research Letters, Vol. 45, Issue 10
    • DOI: 10.1029/2018gl078007

    Degrading permafrost puts Arctic infrastructure at risk by mid-century
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    Carbon budgets for 1.5 and 2 °C targets lowered by natural wetland and permafrost feedbacks
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    Circumpolar permafrost maps and geohazard indices for near-future infrastructure risk assessments
    journal, March 2019

    • Karjalainen, Olli; Aalto, Juha; Luoto, Miska
    • Scientific Data, Vol. 6, Issue 1
    • DOI: 10.1038/sdata.2019.37

    ORCHIDEE-MICT (v8.4.1), a land surface model for the high latitudes: model description and validation
    journal, January 2018

    • Guimberteau, Matthieu; Zhu, Dan; Maignan, Fabienne
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    • DOI: 10.5194/gmd-11-121-2018

    Effects of short-term variability of meteorological variables on soil temperature in permafrost regions
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