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 for this work

Geography

32 Citations (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.

Original language	English
Journal	Journal of Geophysical Research: Earth Surface
Volume	122
Issue number	2
Pages (from-to)	430-446
Number of pages	17
ISSN	2169-9003
DOIs	https://doi.org/10.1002/2016jg003384
Publication status	Published - 2017

Keywords

arctic
carbon use efficiency
climate warming
CO elevation
high latitudes
model intercomparison

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1002/2016jg003384

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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.
In: Journal of Geophysical Research: Earth Surface, Vol. 122, No. 2, 2017, p. 430-446.

Research output: Contribution to journal › Journal article › Research › 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, vol. 122, no. 2, pp. 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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author = "Jianyang Xia and McGuire, {A. David} and David Lawrence and Eleanor Burke and Guangsheng Chen and Xiaodong Chen and Christine Delire and Charles Koven and Andrew MacDougall and Shushi Peng and Annette Rinke and Kazuyuki Saito and Wenxin Zhang and Ramdane Alkama and Bohn, {Theodore J.} and Philippe Ciais and Bertrand Decharme and Isabelle Gouttevin and Tomohiro Hajima and Hayes, {Daniel J} and Kun Huang and Duoying Ji and Gerhard Krinner and Lettenmaier, {Dennis P.} and Miller, {Paul A.} and Moore, {John C.} and Benjamin Smith and Tetsuo Sueyoshi and Zheng-Zheng Shi and Liming Yan and Junyi Liang and Lifen Jiang and Qian Zhang and Yiqi Luo",

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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]

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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

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DO - 10.1002/2016jg003384

M3 - Journal article

AN - SCOPUS:85013413231

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VL - 122

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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

Abstract

Keywords

UN SDGs

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