globalchange  > 气候减缓与适应
DOI: 10.1175/JCLI-D-17-0357.1
Scopus ID: 2-s2.0-85047058579
Title:
Sources of uncertainty in modeled land carbon storage within and across three MIPs: Diagnosis with three new techniques
Author: Zhou S.; Liang J.; Luc X.; Lid Q.; Jiang L.; Zhang Y.; Schwalm C.R.; Fisher J.B.; Tjiputra J.; Sitch S.; Ahlström A.; Huntzinger D.N.; Huang Y.; Wang G.; Luo Y.
Source Publication: Journal of Climate
ISSN: 8948755
Publishing Year: 2018
Volume: 31, Issue:7
pages begin: 2833
pages end: 2851
Language: 英语
Keyword: Carbon cycle ; Land surface model ; Model evaluation/performance
Scopus Keyword: Climate change ; Ecosystems ; Regional planning ; Uncertainty analysis ; Carbon cycles ; Coupled Model Intercomparison Project ; Land surface modeling ; Model evaluation/performance ; Model inter comparisons ; Net primary productivity ; Terrestrial carbon cycle ; Three dimensional (3-D) modeling ; Forestry ; carbon cycle ; carbon sequestration ; land surface ; net primary production ; nitrogen cycle ; three-dimensional modeling ; uncertainty analysis
English Abstract: Terrestrial carbon cycle models have incorporated increasingly more processes as a means to achieve more-realistic representations of ecosystem carbon cycling. Despite this, there are large across-model variations in the simulation and projection of carbon cycling. Several model intercomparison projects (MIPs), for example, the fifth phase of the Coupled Model Intercomparison Project (CMIP5) (historical simulations), Trends in Net Land-Atmosphere Carbon Exchange (TRENDY), and Multiscale Synthesis and Terrestrial Model Intercomparison Project (MsTMIP), have sought to understand intermodel differences. In this study, the authors developed a suite of new techniques to conduct post-MIP analysis to gain insights into uncertainty sources across 25 models in the three MIPs. First, terrestrial carbon storage dynamics were characterized by a three-dimensional (3D) model output space with coordinates of carbon residence time, net primary productivity (NPP), and carbon storage potential. The latter represents the potential of an ecosystem to lose or gain carbon. This space can be used to measure how and why model output differs. Models with a nitrogen cycle generally exhibit lower annual NPP in comparison with other models, and mostly negative carbon storage potential. Second, a transient traceability framework was used to decompose any given carbon cycle model into traceable components and identify the sources of model differences. The carbon residence time (or NPP) was traced to baseline carbon residence time (or baseline NPP related to the maximum carbon input), environmental scalars, and climate forcing. Third, by applying a variance decomposition method, the authors show that the intermodel differences in carbon storage can be mainly attributed to the baseline carbon residence time and baseline NPP (>90% in the three MIPs). The three techniques developed in this study offer a novel approach to gain more insight from existing MIPs and can point out directions for future MIPs. Since this study is conducted at the global scale for an overview on intermodel differences, future studies should focus more on regional analysis to identify the sources of uncertainties and improve models at the specified mechanism level. © 2018 American Meteorological Society.
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被引频次[WOS]:4   [查看WOS记录]     [查看WOS中相关记录]
Document Type: 期刊论文
Identifier: http://119.78.100.158/handle/2HF3EXSE/111584
Appears in Collections:气候减缓与适应

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Affiliation: State Key Laboratory of Hydroscience and Engineering, Department of Hydraulic Engineering, Tsinghua University, Beijing, China; Department of Microbiology and Plant Biology, University of Oklahoma, Norman, OK, United States; Department of Biological Sciences, Northern Arizona University, Flagstaff, AZ, United States; Department of Earth System Science, Tsinghua University, Beijing, China; Center for Spatial Analysis, University of Oklahoma, Norman, OK, United States; Woods Hole Research Center, Falmouth, MA, United States; Center for Ecosystem Science and Society, Northern Arizona University, Flagstaff, AZ, United States; Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, United States; Uni Research Climate, Bjerknes Centre for Climate Research, Bergen, Norway; College of Life and Environmental Sciences, University of Exeter, Exeter, United Kingdom; Department of Earth System Science, Stanford University, Stanford, CA, United States; Department of Physical Geography and Ecosystem Science, Lund University, Lund, Sweden; School of Earth Sciences and Environmental Sustainability, Northern Arizona University, Flagstaff, AZ, United States; Department of Civil Engineering, Construction Management and Environmental Engineering, Northern Arizona University, Flagstaff, AZ, United States; College of Ecological and Environmental Engineering, Qinghai University, Qinghai, China; Department of Earth and Environmental Engineering, Columbia University, New York, NY, United States

Recommended Citation:
Zhou S.,Liang J.,Luc X.,et al. Sources of uncertainty in modeled land carbon storage within and across three MIPs: Diagnosis with three new techniques[J]. Journal of Climate,2018-01-01,31(7)
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