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Matrix approach to land carbon cycle modeling: A case study with the Community Land Model
Authors:Yuanyuan Huang  Xingjie Lu  Zheng Shi  David Lawrence  Charles D Koven  Jianyang Xia  Zhenggang Du  Erik Kluzek  Yiqi Luo
Institution:1. Department of Microbiology and Plant Biology, University of Oklahoma, Norman, OK, USA;2. Now at Laboratoire des Sciences du Climat et de l'Environnement, Gif‐sur‐Yvette, FranceAuthors co‐lead the research.;3. Center for Ecosystem Science and Society, Northern Arizona University, Flagstaff, AZ, USAAuthors co‐lead the research.;4. Climate and Global Dynamics Division, National Center for Atmospheric Research, Boulder, CO, USA;5. Earth Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA;6. Tiantong National Forest Ecosystem Observation and Research Station, School of Ecological and Environmental Sciences, East China Normal University, Shanghai, China;7. Research Center for Global Change and Ecological Forecasting, East China Normal University, Shanghai, China;8. Center for Ecosystem Science and Society, Northern Arizona University, Flagstaff, AZ, USA;9. Department of Earth System Science, Tsinghua University, Beijing, China
Abstract: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.
Keywords:carbon storage  CO2 fertilization  data assimilation  residence time  soil organic matter
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