globalchange  > 影响、适应和脆弱性
DOI: 10.1111/gcb.13948
Scopus记录号: 2-s2.0-85035244643
论文题名:
Matrix approach to land carbon cycle modeling: A case study with the Community Land Model
作者: Huang Y.; Lu X.; Shi Z.; Lawrence D.; Koven C.D.; Xia J.; Du Z.; Kluzek E.; Luo Y.
刊名: Global Change Biology
ISSN: 13541013
出版年: 2018
卷: 24, 期:3
起始页码: 1394
结束页码: 1404
语种: 英语
英文关键词: carbon storage ; CO2 fertilization ; data assimilation ; residence time ; soil organic matter
Scopus关键词: biogeochemistry ; carbon balance ; carbon cycle ; carbon dioxide ; carbon sequestration ; data assimilation ; modeling ; residence time ; soil organic matter
英文摘要: The terrestrial carbon (C) cycle has been commonly represented by a series of C balance equations to track C influxes into and effluxes out of individual pools in earth system models (ESMs). This representation matches our understanding of C cycle processes well but makes it difficult to track model behaviors. It is also computationally expensive, limiting the ability to conduct comprehensive parametric sensitivity analyses. To overcome these challenges, we have developed a matrix approach, which reorganizes the C balance equations in the original ESM into one matrix equation without changing any modeled C cycle processes and mechanisms. We applied the matrix approach to the Community Land Model (CLM4.5) with vertically-resolved biogeochemistry. The matrix equation exactly reproduces litter and soil organic carbon (SOC) dynamics of the standard CLM4.5 across different spatial-temporal scales. The matrix approach enables effective diagnosis of system properties such as C residence time and attribution of global change impacts to relevant processes. We illustrated, for example, the impacts of CO2 fertilization on litter and SOC dynamics can be easily decomposed into the relative contributions from C input, allocation of external C into different C pools, nitrogen regulation, altered soil environmental conditions, and vertical mixing along the soil profile. In addition, the matrix tool can accelerate model spin-up, permit thorough parametric sensitivity tests, enable pool-based data assimilation, and facilitate tracking and benchmarking of model behaviors. Overall, the matrix approach can make a broad range of future modeling activities more efficient and effective. © 2017 John Wiley & Sons Ltd
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资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/110501
Appears in Collections:影响、适应和脆弱性
气候变化事实与影响

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作者单位: Department of Microbiology and Plant Biology, University of Oklahoma, Norman, OK, United States; Laboratoire des Sciences du Climat et de l'Environnement, Gif-sur-Yvette, France; Center for Ecosystem Science and Society, Northern Arizona University, Flagstaff, AZ, United States; Climate and Global Dynamics Division, National Center for Atmospheric Research, Boulder, CO, United States; Earth Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA, United States; Tiantong National Forest Ecosystem Observation and Research Station, School of Ecological and Environmental Sciences, East China Normal University, Shanghai, China; Research Center for Global Change and Ecological Forecasting, East China Normal University, Shanghai, China; Department of Earth System Science, Tsinghua University, Beijing, China

Recommended Citation:
Huang Y.,Lu X.,Shi Z.,et al. Matrix approach to land carbon cycle modeling: A case study with the Community Land Model[J]. Global Change Biology,2018-01-01,24(3)
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