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| Main Authors: | , , , , , , , , |
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| Format: | Dataset Open Access |
| Language: | en |
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PANGAEA
2017
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| Online Access: | https://doi.org/10.1594/PANGAEA.881568 |
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| _version_ | 1867171002021052416 |
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| author | Huang, Yuanyuan Lu, Xingjie Shi, Zheng Lawrence, David M Koven, Charles D Xia, Jianyang Du, Zhenggang Kluzek, Erik Luo, Yiqi |
| author_facet | Huang, Yuanyuan Lu, Xingjie Shi, Zheng Lawrence, David M Koven, Charles D Xia, Jianyang Du, Zhenggang Kluzek, Erik Luo, Yiqi |
| collection | Datos científicos de ciencias marinas y ambientales |
| contents | 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. |
| format | Dataset Open Access |
| id | pangaea_https___doi_org_10_1594_PANGAEA_881568 |
| institution | PANGAEA |
| language | en |
| publishDate | 2017 |
| publisher | PANGAEA |
| record_format | pangaea |
| spellingShingle | Matrix approach to land carbon cycle modeling: A case study with Community Land Model, link to input data in NetCDF format Huang, Yuanyuan Lu, Xingjie Shi, Zheng Lawrence, David M Koven, Charles D Xia, Jianyang Du, Zhenggang Kluzek, Erik Luo, Yiqi 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. |
| title | Matrix approach to land carbon cycle modeling: A case study with Community Land Model, link to input data in NetCDF format |
| topic | |
| url | https://doi.org/10.1594/PANGAEA.881568 |