Terrestrial ecosystem model performance in simulating productivity and its vulnerability to climate change in the northern permafrost region
Realistic projection of future climate-carbon (C) cycle feedbacks requires better understanding and an improved representation of the C cycle in permafrost regions in the current generation of Earth system models. Here we evaluated 10 terrestrial ecosystem models for their estimates of net primary p...
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ftncar:oai:drupal-site.org:articles_19633 2023-09-05T13:22:30+02:00 Terrestrial ecosystem model performance in simulating productivity and its vulnerability to climate change in the northern permafrost region Xia, Jianyang (author) McGuire, A. David (author) Lawrence, David (author) Burke, Eleanor (author) Chen, Guangsheng (author) Chen, Xiaodong (author) Delire, Christine (author) Koven, Charles (author) MacDougall, Andrew (author) Peng, Shushi (author) Rinke, Annette (author) Saito, Kazuyuki (author) Zhang, Wenxin (author) Alkama, Ramdane (author) Bohn, Theodore J. (author) Ciais, Philippe (author) Decharme, Bertrand (author) Gouttevin, Isabelle (author) Hajima, Tomohiro (author) Hayes, Daniel J. (author) Huang, Kun (author) Ji, Duoying (author) Krinner, Gerhard (author) Lettenmaier, Dennis P. (author) Miller, Paul A. (author) Moore, John C. (author) Smith, Benjamin (author) Sueyoshi, Tetsuo (author) Shi, Zheng (author) Yan, Liming (author) Liang, Junyi (author) Jiang, Lifen (author) Zhang, Qian (author) Luo, Yiqi (author) 2017-02 https://doi.org/10.1002/2016JG003384 en eng Journal of Geophysical Research: Biogeosciences--J. Geophys. Res. Biogeosci.--21698953 articles:19633 ark:/85065/d75b049t doi:10.1002/2016JG003384 Copyright 2017 American Geophysical Union. article Text 2017 ftncar https://doi.org/10.1002/2016JG003384 2023-08-14T18:45:54Z Realistic projection of future climate-carbon (C) cycle feedbacks requires better understanding and an improved representation of the C cycle in permafrost regions in the current generation of Earth system models. Here we evaluated 10 terrestrial ecosystem models for their estimates of net primary productivity (NPP) and responses to historical climate change in permafrost regions in the Northern Hemisphere. In comparison with the satellite estimate from the Moderate Resolution Imaging Spectroradiometer (MODIS; 246 +/- 6gCm(-2) yr (-1)), most models produced higher NPP (309 +/- 12 g Cm-2 yr(-1)) over the permafrost region during 2000-2009. By comparing the simulated gross primary productivity (GPP) with a flux tower-based database, we found that although mean GPP among the models was only overestimated by 10% over 1982-2009, there was a twofold discrepancy among models (380 to 800 g Cm-2 yr(-1)), which mainly resulted from differences in simulated maximum monthly GPP (GPP(max)). Most models overestimated C use efficiency (CUE) as compared to observations at both regional and site levels. Further analysis shows that model variability of GPP and CUE are nonlinearly correlated to variability in specific leaf area and the maximum rate of carboxylation by the enzyme Rubisco at 25 degrees C (V-cmax_(25)), respectively. Themodels also varied in their sensitivities of NPP, GPP, and CUE to historical changes in climate and atmospheric CO2 concentration. These results indicate that model predictive ability of the C cycle in permafrost regions can be improved by better representation of the processes controlling CUE and GPP(max) as well as their sensitivity to climate change. Article in Journal/Newspaper permafrost OpenSky (NCAR/UCAR - National Center for Atmospheric Research/University Corporation for Atmospheric Research) Journal of Geophysical Research: Biogeosciences 122 2 430 446 |
institution |
Open Polar |
collection |
OpenSky (NCAR/UCAR - National Center for Atmospheric Research/University Corporation for Atmospheric Research) |
op_collection_id |
ftncar |
language |
English |
description |
Realistic projection of future climate-carbon (C) cycle feedbacks requires better understanding and an improved representation of the C cycle in permafrost regions in the current generation of Earth system models. Here we evaluated 10 terrestrial ecosystem models for their estimates of net primary productivity (NPP) and responses to historical climate change in permafrost regions in the Northern Hemisphere. In comparison with the satellite estimate from the Moderate Resolution Imaging Spectroradiometer (MODIS; 246 +/- 6gCm(-2) yr (-1)), most models produced higher NPP (309 +/- 12 g Cm-2 yr(-1)) over the permafrost region during 2000-2009. By comparing the simulated gross primary productivity (GPP) with a flux tower-based database, we found that although mean GPP among the models was only overestimated by 10% over 1982-2009, there was a twofold discrepancy among models (380 to 800 g Cm-2 yr(-1)), which mainly resulted from differences in simulated maximum monthly GPP (GPP(max)). Most models overestimated C use efficiency (CUE) as compared to observations at both regional and site levels. Further analysis shows that model variability of GPP and CUE are nonlinearly correlated to variability in specific leaf area and the maximum rate of carboxylation by the enzyme Rubisco at 25 degrees C (V-cmax_(25)), respectively. Themodels also varied in their sensitivities of NPP, GPP, and CUE to historical changes in climate and atmospheric CO2 concentration. These results indicate that model predictive ability of the C cycle in permafrost regions can be improved by better representation of the processes controlling CUE and GPP(max) as well as their sensitivity to climate change. |
author2 |
Xia, Jianyang (author) McGuire, A. David (author) Lawrence, David (author) Burke, Eleanor (author) Chen, Guangsheng (author) Chen, Xiaodong (author) Delire, Christine (author) Koven, Charles (author) MacDougall, Andrew (author) Peng, Shushi (author) Rinke, Annette (author) Saito, Kazuyuki (author) Zhang, Wenxin (author) Alkama, Ramdane (author) Bohn, Theodore J. (author) Ciais, Philippe (author) Decharme, Bertrand (author) Gouttevin, Isabelle (author) Hajima, Tomohiro (author) Hayes, Daniel J. (author) Huang, Kun (author) Ji, Duoying (author) Krinner, Gerhard (author) Lettenmaier, Dennis P. (author) Miller, Paul A. (author) Moore, John C. (author) Smith, Benjamin (author) Sueyoshi, Tetsuo (author) Shi, Zheng (author) Yan, Liming (author) Liang, Junyi (author) Jiang, Lifen (author) Zhang, Qian (author) Luo, Yiqi (author) |
format |
Article in Journal/Newspaper |
title |
Terrestrial ecosystem model performance in simulating productivity and its vulnerability to climate change in the northern permafrost region |
spellingShingle |
Terrestrial ecosystem model performance in simulating productivity and its vulnerability to climate change in the northern permafrost region |
title_short |
Terrestrial ecosystem model performance in simulating productivity and its vulnerability to climate change in the northern permafrost region |
title_full |
Terrestrial ecosystem model performance in simulating productivity and its vulnerability to climate change in the northern permafrost region |
title_fullStr |
Terrestrial ecosystem model performance in simulating productivity and its vulnerability to climate change in the northern permafrost region |
title_full_unstemmed |
Terrestrial ecosystem model performance in simulating productivity and its vulnerability to climate change in the northern permafrost region |
title_sort |
terrestrial ecosystem model performance in simulating productivity and its vulnerability to climate change in the northern permafrost region |
publishDate |
2017 |
url |
https://doi.org/10.1002/2016JG003384 |
genre |
permafrost |
genre_facet |
permafrost |
op_relation |
Journal of Geophysical Research: Biogeosciences--J. Geophys. Res. Biogeosci.--21698953 articles:19633 ark:/85065/d75b049t doi:10.1002/2016JG003384 |
op_rights |
Copyright 2017 American Geophysical Union. |
op_doi |
https://doi.org/10.1002/2016JG003384 |
container_title |
Journal of Geophysical Research: Biogeosciences |
container_volume |
122 |
container_issue |
2 |
container_start_page |
430 |
op_container_end_page |
446 |
_version_ |
1776203024436297728 |