Skip to main content

Lund University Publications

LUND UNIVERSITY LIBRARIES

Matrix Approach to Land Carbon Cycle Modeling

Luo, Yiqi ; Huang, Yuanyuan ; Sierra, Carlos A. ; Xia, Jianyang ; Ahlström, Anders LU orcid ; Chen, Yizhao ; Hararuk, Oleksandra ; Hou, Enqing ; Jiang, Lifen and Liao, Cuijuan , et al. (2022) In Journal of Advances in Modeling Earth Systems 14(7).
Abstract

Land ecosystems contribute to climate change mitigation by taking up approximately 30% of anthropogenically emitted carbon. However, estimates of the amount and distribution of carbon uptake across the world's ecosystems or biomes display great uncertainty. The latter hinders a full understanding of the mechanisms and drivers of land carbon uptake, and predictions of the future fate of the land carbon sink. The latter is needed as evidence to inform climate mitigation strategies such as afforestation schemes. To advance land carbon cycle modeling, we have developed a matrix approach. Land carbon cycle models use carbon balance equations to represent carbon exchanges among pools. Our approach organizes this set of equations into a single... (More)

Land ecosystems contribute to climate change mitigation by taking up approximately 30% of anthropogenically emitted carbon. However, estimates of the amount and distribution of carbon uptake across the world's ecosystems or biomes display great uncertainty. The latter hinders a full understanding of the mechanisms and drivers of land carbon uptake, and predictions of the future fate of the land carbon sink. The latter is needed as evidence to inform climate mitigation strategies such as afforestation schemes. To advance land carbon cycle modeling, we have developed a matrix approach. Land carbon cycle models use carbon balance equations to represent carbon exchanges among pools. Our approach organizes this set of equations into a single matrix equation without altering any processes of the original model. The matrix equation enables the development of a theoretical framework for understanding the general, transient behavior of the land carbon cycle. While carbon input and residence time are used to quantify carbon storage capacity at steady state, a third quantity, carbon storage potential, integrates fluxes with time to define dynamic disequilibrium of the carbon cycle under global change. The matrix approach can help address critical contemporary issues in modeling, including pinpointing sources of model uncertainty and accelerating spin-up of land carbon cycle models by tens of times. The accelerated spin-up liberates models from the computational burden that hinders comprehensive parameter sensitivity analysis and assimilation of observational data to improve model accuracy. Such computational efficiency offered by the matrix approach enables substantial improvement of model predictions using ever-increasing data availability. Overall, the matrix approach offers a step change forward for understanding and modeling the land carbon cycle.

(Less)
Please use this url to cite or link to this publication:
author
; ; ; ; ; ; ; ; and , et al. (More)
; ; ; ; ; ; ; ; ; ; ; ; ; and (Less)
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
biogeochemistry, carbon cycle, dynamical equation, terrestrial ecosystems, uncertainty analysis
in
Journal of Advances in Modeling Earth Systems
volume
14
issue
7
article number
e2022MS003008
publisher
Wiley-Blackwell
external identifiers
  • scopus:85135054580
ISSN
1942-2466
DOI
10.1029/2022MS003008
language
English
LU publication?
yes
id
3de5c41f-997e-436e-afb5-36a2414ffde6
date added to LUP
2022-11-29 14:25:11
date last changed
2022-11-30 10:12:53
@article{3de5c41f-997e-436e-afb5-36a2414ffde6,
  abstract     = {{<p>Land ecosystems contribute to climate change mitigation by taking up approximately 30% of anthropogenically emitted carbon. However, estimates of the amount and distribution of carbon uptake across the world's ecosystems or biomes display great uncertainty. The latter hinders a full understanding of the mechanisms and drivers of land carbon uptake, and predictions of the future fate of the land carbon sink. The latter is needed as evidence to inform climate mitigation strategies such as afforestation schemes. To advance land carbon cycle modeling, we have developed a matrix approach. Land carbon cycle models use carbon balance equations to represent carbon exchanges among pools. Our approach organizes this set of equations into a single matrix equation without altering any processes of the original model. The matrix equation enables the development of a theoretical framework for understanding the general, transient behavior of the land carbon cycle. While carbon input and residence time are used to quantify carbon storage capacity at steady state, a third quantity, carbon storage potential, integrates fluxes with time to define dynamic disequilibrium of the carbon cycle under global change. The matrix approach can help address critical contemporary issues in modeling, including pinpointing sources of model uncertainty and accelerating spin-up of land carbon cycle models by tens of times. The accelerated spin-up liberates models from the computational burden that hinders comprehensive parameter sensitivity analysis and assimilation of observational data to improve model accuracy. Such computational efficiency offered by the matrix approach enables substantial improvement of model predictions using ever-increasing data availability. Overall, the matrix approach offers a step change forward for understanding and modeling the land carbon cycle.</p>}},
  author       = {{Luo, Yiqi and Huang, Yuanyuan and Sierra, Carlos A. and Xia, Jianyang and Ahlström, Anders and Chen, Yizhao and Hararuk, Oleksandra and Hou, Enqing and Jiang, Lifen and Liao, Cuijuan and Lu, Xingjie and Shi, Zheng and Smith, Benjamin and Tao, Feng and Wang, Ying Ping}},
  issn         = {{1942-2466}},
  keywords     = {{biogeochemistry; carbon cycle; dynamical equation; terrestrial ecosystems; uncertainty analysis}},
  language     = {{eng}},
  number       = {{7}},
  publisher    = {{Wiley-Blackwell}},
  series       = {{Journal of Advances in Modeling Earth Systems}},
  title        = {{Matrix Approach to Land Carbon Cycle Modeling}},
  url          = {{http://dx.doi.org/10.1029/2022MS003008}},
  doi          = {{10.1029/2022MS003008}},
  volume       = {{14}},
  year         = {{2022}},
}