Terrestrial ecosystem model performance in simulating productivity and its vulnerability to climate change in the northern permafrost region. Issue 2 (22nd February 2017)
- Record Type:
- Journal Article
- Title:
- Terrestrial ecosystem model performance in simulating productivity and its vulnerability to climate change in the northern permafrost region. Issue 2 (22nd February 2017)
- Main Title:
- Terrestrial ecosystem model performance in simulating productivity and its vulnerability to climate change in the northern permafrost region
- Authors:
- Xia, Jianyang
McGuire, A. David
Lawrence, David
Burke, Eleanor
Chen, Guangsheng
Chen, Xiaodong
Delire, Christine
Koven, Charles
MacDougall, Andrew
Peng, Shushi
Rinke, Annette
Saito, Kazuyuki
Zhang, Wenxin
Alkama, Ramdane
Bohn, Theodore J.
Ciais, Philippe
Decharme, Bertrand
Gouttevin, Isabelle
Hajima, Tomohiro
Hayes, Daniel J.
Huang, Kun
Ji, Duoying
Krinner, Gerhard
Lettenmaier, Dennis P.
Miller, Paul A.
Moore, John C.
Smith, Benjamin
Sueyoshi, Tetsuo
Shi, Zheng
Yan, Liming
Liang, Junyi
Jiang, Lifen
Zhang, Qian
Luo, Yiqi
… (more) - Abstract:
- Abstract: 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 ± 6 g C m −2 yr −1 ), most models produced higher NPP (309 ± 12 g C m −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 C m −2 yr −1 ), which mainly resulted from differences in simulated maximum monthly GPP (GPPmax ). 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°C ( V c max_25 ), respectively. The models also varied in their sensitivities of NPP, GPP, and CUE to historical changes in climate and atmospheric CO2 concentration. These results indicateAbstract: 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 ± 6 g C m −2 yr −1 ), most models produced higher NPP (309 ± 12 g C m −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 C m −2 yr −1 ), which mainly resulted from differences in simulated maximum monthly GPP (GPPmax ). 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°C ( V c max_25 ), respectively. The models 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 GPPmax as well as their sensitivity to climate change. Key Points: Current land models generate very high NPP over the permafrost regions, which mainly results from the overestimated CUE in the models Modeled GPP is comparable to flux tower‐based estimate, but there is a twofold discrepancy among models Models highly varied in their sensitivities of NPP, GPP, and CUE to historical changes in climate and atmospheric CO2 concentration … (more)
- Is Part Of:
- Journal of geophysical research. Volume 122:Issue 2(2017)
- Journal:
- Journal of geophysical research
- Issue:
- Volume 122:Issue 2(2017)
- Issue Display:
- Volume 122, Issue 2 (2017)
- Year:
- 2017
- Volume:
- 122
- Issue:
- 2
- Issue Sort Value:
- 2017-0122-0002-0000
- Page Start:
- 430
- Page End:
- 446
- Publication Date:
- 2017-02-22
- Subjects:
- arctic -- carbon use efficiency -- climate warming -- CO2 elevation -- high latitudes -- model intercomparison
Geobiology -- Periodicals
Biogeochemistry -- Periodicals
Biotic communities -- Periodicals
Geophysics -- Periodicals
577.14 - Journal URLs:
- http://onlinelibrary.wiley.com/journal/10.1002/(ISSN)2169-8961 ↗
http://onlinelibrary.wiley.com/ ↗ - DOI:
- 10.1002/2016JG003384 ↗
- Languages:
- English
- ISSNs:
- 2169-8953
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 4995.003000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 1709.xml