Terrestrial ecosystem model performance in simulating productivity and its vulnerability to climate change in the northern permafrost region

Jianyang Xia; A. David McGuire; David Lawrence; Eleanor  Burke; Guangsheng  Chen; Xiaodong Chen; Christine Delire; Charles Koven; Andrew MacDougall; Shushi Peng; Annette Rinke; Kazuyuki Saito; Wenxin Zhang; Ramdane Alkama; Theodore J. Bohn; Philippe Ciais; Bertrand Decharme; Isabelle Gouttevin; Tomohiro Hajima; Daniel J Hayes; Kun Huang; Duoying Ji; Gerhard Krinner; Dennis P. Lettenmaier; Paul A. Miller; John C. Moore; Benjamin Smith; Tetsuo Sueyoshi; Zheng-Zheng Shi; Liming Yan; Junyi Liang; Lifen Jiang; Qian Zhang; Yiqi Luo

doi:10.1002/2016jg003384

Terrestrial ecosystem model performance in simulating productivity and its vulnerability to climate change in the northern permafrost region

Jianyang Xia^*, A. David McGuire, David Lawrence, Eleanor Burke, Guangsheng Chen, Xiaodong Chen, Christine Delire, Charles Koven, Andrew MacDougall, Shushi Peng, Annette Rinke, Kazuyuki Saito, Wenxin Zhang, Ramdane Alkama, Theodore J. Bohn, Philippe Ciais, Bertrand Decharme, Isabelle Gouttevin, Tomohiro Hajima, Daniel J HayesKun Huang, Duoying Ji, Gerhard Krinner, Dennis P. Lettenmaier, Paul A. Miller, John C. Moore, Benjamin Smith, Tetsuo Sueyoshi, Zheng-Zheng Shi, Liming Yan, Junyi Liang, Lifen Jiang, Qian Zhang, Yiqi Luo

^*Corresponding author af dette arbejde

LUKKET: Geografi

32 Citationer (Scopus)

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 (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°C (V_{cmax_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 GPP_max as well as their sensitivity to climate change.

Originalsprog	Engelsk
Tidsskrift	Journal of Geophysical Research: Earth Surface
Vol/bind	122
Udgave nummer	2
Sider (fra-til)	430-446
Antal sider	17
ISSN	2169-9003
DOI	https://doi.org/10.1002/2016jg003384
Status	Udgivet - 2017

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Xia, J., McGuire, A. D., Lawrence, D., Burke, E., Chen, G., Chen, X., Delire, C., Koven, C., MacDougall, A., Peng, S., Rinke, A., Saito, K., Zhang, W., Alkama, R., Bohn, T. J., Ciais, P., Decharme, B., Gouttevin, I., Hajima, T., ... Luo, Y. (2017). Terrestrial ecosystem model performance in simulating productivity and its vulnerability to climate change in the northern permafrost region. Journal of Geophysical Research: Earth Surface, 122(2), 430-446. https://doi.org/10.1002/2016jg003384

Terrestrial ecosystem model performance in simulating productivity and its vulnerability to climate change in the northern permafrost region. / Xia, Jianyang; McGuire, A. David; Lawrence, David et al.
I: Journal of Geophysical Research: Earth Surface, Bind 122, Nr. 2, 2017, s. 430-446.

Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › peer review

Xia, J, McGuire, AD, Lawrence, D, Burke, E, Chen, G, Chen, X, Delire, C, Koven, C, MacDougall, A, Peng, S, Rinke, A, Saito, K, Zhang, W, Alkama, R, Bohn, TJ, Ciais, P, Decharme, B, Gouttevin, I, Hajima, T, Hayes, DJ, Huang, K, Ji, D, Krinner, G, Lettenmaier, DP, Miller, PA, Moore, JC, Smith, B, Sueyoshi, T, Shi, Z-Z, Yan, L, Liang, J, Jiang, L, Zhang, Q & Luo, Y 2017, 'Terrestrial ecosystem model performance in simulating productivity and its vulnerability to climate change in the northern permafrost region', Journal of Geophysical Research: Earth Surface, bind 122, nr. 2, s. 430-446. https://doi.org/10.1002/2016jg003384

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title = "Terrestrial ecosystem model performance in simulating productivity and its vulnerability to climate change in the northern permafrost region",

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 (Vcmax_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.",

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T1 - Terrestrial ecosystem model performance in simulating productivity and its vulnerability to climate change in the northern permafrost region

AU - Xia, Jianyang

AU - McGuire, A. David

AU - Lawrence, David

AU - Burke, Eleanor

AU - Chen, Guangsheng

AU - Chen, Xiaodong

AU - Delire, Christine

AU - Koven, Charles

AU - MacDougall, Andrew

AU - Peng, Shushi

AU - Rinke, Annette

AU - Saito, Kazuyuki

AU - Zhang, Wenxin

AU - Alkama, Ramdane

AU - Bohn, Theodore J.

AU - Ciais, Philippe

AU - Decharme, Bertrand

AU - Gouttevin, Isabelle

AU - Hajima, Tomohiro

AU - Hayes, Daniel J

AU - Huang, Kun

AU - Ji, Duoying

AU - Krinner, Gerhard

AU - Lettenmaier, Dennis P.

AU - Miller, Paul A.

AU - Moore, John C.

AU - Smith, Benjamin

AU - Sueyoshi, Tetsuo

AU - Shi, Zheng-Zheng

AU - Yan, Liming

AU - Liang, Junyi

AU - Jiang, Lifen

AU - Zhang, Qian

AU - Luo, Yiqi

N1 - CENPERM[2017]

PY - 2017

Y1 - 2017

N2 - 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 (Vcmax_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.

AB - 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 (Vcmax_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.

KW - arctic

KW - carbon use efficiency

KW - climate warming

KW - CO elevation

KW - high latitudes

KW - model intercomparison

U2 - 10.1002/2016jg003384

DO - 10.1002/2016jg003384

M3 - Journal article

AN - SCOPUS:85013413231

SN - 2169-9003

VL - 122

SP - 430

EP - 446

JO - Journal of Geophysical Research: Earth Surface

JF - Journal of Geophysical Research: Earth Surface

IS - 2

ER -

Terrestrial ecosystem model performance in simulating productivity and its vulnerability to climate change in the northern permafrost region

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