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
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
@article{b46efc5cb43d49eeb1af605d01e070e6,
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.",
keywords = "arctic, carbon use efficiency, climate warming, CO elevation, high latitudes, model intercomparison",
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",
note = "CENPERM[2017]",
year = "2017",
doi = "10.1002/2016jg003384",
language = "English",
volume = "122",
pages = "430--446",
journal = "Journal of Geophysical Research: Earth Surface",
issn = "2169-9003",
publisher = "American Geophysical Union",
number = "2",
}
TY - JOUR
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 -
