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Review article - Peer-reviewed, 2022

Matrix Approach to Land Carbon Cycle Modeling

Luo, Yiqi; Huang, Yuanyuan; Sierra, Carlos A.; Xia, Jianyang; Ahlstrom, Anders; Chen, Yizhao; Hararuk, Oleksandra; Hou, Enqing; Jiang, Lifen; Liao, Cuijuan; Lu, Xingjie; Shi, Zheng; Smith, Benjamin; Tao, Feng; Wang, Ying-Ping


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.


biogeochemistry; carbon cycle; dynamical equation; terrestrial ecosystems; uncertainty analysis

Published in

Journal of Advances in Modeling Earth Systems (Electronics)
2022, volume: 14, number: 7, article number: e2022MS003008

Authors' information

Luo, Yiqi
Northern Arizona University
Luo, Yiqi
Cornell University
Huang, Yuanyuan
Commonwealth Scientific and Industrial Research Organisation (CSIRO)
Swedish University of Agricultural Sciences, Department of Ecology
Sierra, Carlos A. (Sierra, Carlos)
Max Planck Society
Xia, Jianyang
East China Normal University
Ahlstrom, Anders
Lund University
Chen, Yizhao
Nanjing Forestry University
Hararuk, Oleksandra
Natural Resources Canada
Hou, Enqing
South China Botanical Garden, CAS
Jiang, Lifen
Northern Arizona University
Liao, Cuijuan
Tsinghua University
Lu, Xingjie
Sun Yat Sen University
Shi, Zheng
University of Oklahoma - Norman
Smith, Benjamin
Western Sydney University
Smith, Benjamin
Lund University
Tao, Feng
Tsinghua University
Wang, Ying-Ping
Commonwealth Scientific and Industrial Research Organisation (CSIRO)

Sustainable Development Goals

SDG13 Climate action

UKÄ Subject classification

Other Earth and Related Environmental Sciences
Meteorology and Atmospheric Sciences
Climate Research

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