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

作者：Jianyang Xia, A. David McGuire, David M. Lawrence, Eleanor Burke, Guangsheng Chen, Xiaodong Chen, Christine Delire, Charles D. Koven, Andrew MacDougall, Shushi Peng, Annette Rinke, Kazuyuki Saitô, Wenxin Zhang, Ramdane Alkama, T. J. Bohn, P. Ciais, Bertrand Decharme, Isabelle Gouttevin, T. Hajima, Daniel J. Hayes, Kun Huang, Duoying Ji, Gerhard Krinner, Dennis P. Lettenmaier, Paul Miller, John C. Moore, Benjamin Smith, Tetsuo Sueyoshi, Zheng Shi, Liming Yan, Junyi Liang, L. Jiang, Qian Zhang, Yiqi Luo · 发表于：Journal of Geophysical Research Biogeosciences · 年份：2017 · DOI：10.1002/2016jg003384 · 被引用次数：67 · 研究领域：Climate change and permafrost、Cryospheric studies and observations、Climate variability and models

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 c max_25 ), respectively. The models also varied in their sensitivities of NPP, GPP, and CUE to historical changes in climate and atmospheric CO 2 concentration. These results indicate that...