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Title: Matrix approach to land carbon cycle modeling: A case study with the Community Land Model

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 CO 2 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. Inmore » 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. Altogether, the matrix approach can make a broad range of future modeling activities more efficient and effective.« less

Authors:
ORCiD logo [1];  [2];  [3];  [4];  [5];  [6];  [6];  [4];  [7]
  1. Univ. of Oklahoma, Norman, OK (United States); Lab. des Sciences du Climat et de l'Environnement, Gif-sur-Yvette (France)
  2. Univ. of Oklahoma, Norman, OK (United States); Northern Arizona Univ., Flagstaff, AZ (United States)
  3. Univ. of Oklahoma, Norman, OK (United States)
  4. National Center for Atmospheric Research, Boulder, CO (United States)
  5. Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
  6. East Chine Normal Univ., Shanghai (China)
  7. Univ. of Oklahoma, Norman, OK (United States); Northern Arizona Univ., Flagstaff, AZ (United States); Tsinghua Univ., Beijing (China)
Publication Date:
Research Org.:
Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
Sponsoring Org.:
USDOE Office of Science (SC), Biological and Environmental Research (BER) (SC-23)
OSTI Identifier:
1477267
Alternate Identifier(s):
OSTI ID: 1410578
Grant/Contract Number:  
AC02-05CH11231; DE‐SC0008270; DE‐SC00114085
Resource Type:
Accepted Manuscript
Journal Name:
Global Change Biology
Additional Journal Information:
Journal Volume: 24; Journal Issue: 3; Journal ID: ISSN 1354-1013
Publisher:
Wiley
Country of Publication:
United States
Language:
English
Subject:
59 BASIC BIOLOGICAL SCIENCES; carbon storage; CO 2 fertilization; data assimilation; residence time; soil organic matter

Citation Formats

Huang, Yuanyuan, Lu, Xingjie, Shi, Zheng, Lawrence, David, Koven, Charles D., Xia, Jianyang, Du, Zhenggang, Kluzek, Erik, and Luo, Yiqi. Matrix approach to land carbon cycle modeling: A case study with the Community Land Model. United States: N. p., 2017. Web. doi:10.1111/gcb.13948.
Huang, Yuanyuan, Lu, Xingjie, Shi, Zheng, Lawrence, David, Koven, Charles D., Xia, Jianyang, Du, Zhenggang, Kluzek, Erik, & Luo, Yiqi. Matrix approach to land carbon cycle modeling: A case study with the Community Land Model. United States. doi:10.1111/gcb.13948.
Huang, Yuanyuan, Lu, Xingjie, Shi, Zheng, Lawrence, David, Koven, Charles D., Xia, Jianyang, Du, Zhenggang, Kluzek, Erik, and Luo, Yiqi. Fri . "Matrix approach to land carbon cycle modeling: A case study with the Community Land Model". United States. doi:10.1111/gcb.13948. https://www.osti.gov/servlets/purl/1477267.
@article{osti_1477267,
title = {Matrix approach to land carbon cycle modeling: A case study with the Community Land Model},
author = {Huang, Yuanyuan and Lu, Xingjie and Shi, Zheng and Lawrence, David and Koven, Charles D. and Xia, Jianyang and Du, Zhenggang and Kluzek, Erik and Luo, Yiqi},
abstractNote = {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. Altogether, the matrix approach can make a broad range of future modeling activities more efficient and effective.},
doi = {10.1111/gcb.13948},
journal = {Global Change Biology},
number = 3,
volume = 24,
place = {United States},
year = {2017},
month = {10}
}

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