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The role of residence time in diagnostic models of global carbon storage capacity: model decomposition based on a traceable scheme
As a key factor that determines carbon storage capacity, residence time (τ(E)) is not well constrained in terrestrial biosphere models. This factor is recognized as an important source of model uncertainty. In this study, to understand how τ(E) influences terrestrial carbon storage prediction in dia...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4635433/ https://www.ncbi.nlm.nih.gov/pubmed/26541245 http://dx.doi.org/10.1038/srep16155 |
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author | Yizhao, Chen Jianyang, Xia Zhengguo, Sun Jianlong, Li Yiqi, Luo Chengcheng, Gang Zhaoqi, Wang |
author_facet | Yizhao, Chen Jianyang, Xia Zhengguo, Sun Jianlong, Li Yiqi, Luo Chengcheng, Gang Zhaoqi, Wang |
author_sort | Yizhao, Chen |
collection | PubMed |
description | As a key factor that determines carbon storage capacity, residence time (τ(E)) is not well constrained in terrestrial biosphere models. This factor is recognized as an important source of model uncertainty. In this study, to understand how τ(E) influences terrestrial carbon storage prediction in diagnostic models, we introduced a model decomposition scheme in the Boreal Ecosystem Productivity Simulator (BEPS) and then compared it with a prognostic model. The result showed that τ(E) ranged from 32.7 to 158.2 years. The baseline residence time (τ′(E)) was stable for each biome, ranging from 12 to 53.7 years for forest biomes and 4.2 to 5.3 years for non-forest biomes. The spatiotemporal variations in τ(E) were mainly determined by the environmental scalar (ξ). By comparing models, we found that the BEPS uses a more detailed pool construction but rougher parameterization for carbon allocation and decomposition. With respect to ξ comparison, the global difference in the temperature scalar (ξ(t)) averaged 0.045, whereas the moisture scalar (ξ(w)) had a much larger variation, with an average of 0.312. We propose that further evaluations and improvements in τ′(E) and ξ(w) predictions are essential to reduce the uncertainties in predicting carbon storage by the BEPS and similar diagnostic models. |
format | Online Article Text |
id | pubmed-4635433 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | Nature Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-46354332015-11-25 The role of residence time in diagnostic models of global carbon storage capacity: model decomposition based on a traceable scheme Yizhao, Chen Jianyang, Xia Zhengguo, Sun Jianlong, Li Yiqi, Luo Chengcheng, Gang Zhaoqi, Wang Sci Rep Article As a key factor that determines carbon storage capacity, residence time (τ(E)) is not well constrained in terrestrial biosphere models. This factor is recognized as an important source of model uncertainty. In this study, to understand how τ(E) influences terrestrial carbon storage prediction in diagnostic models, we introduced a model decomposition scheme in the Boreal Ecosystem Productivity Simulator (BEPS) and then compared it with a prognostic model. The result showed that τ(E) ranged from 32.7 to 158.2 years. The baseline residence time (τ′(E)) was stable for each biome, ranging from 12 to 53.7 years for forest biomes and 4.2 to 5.3 years for non-forest biomes. The spatiotemporal variations in τ(E) were mainly determined by the environmental scalar (ξ). By comparing models, we found that the BEPS uses a more detailed pool construction but rougher parameterization for carbon allocation and decomposition. With respect to ξ comparison, the global difference in the temperature scalar (ξ(t)) averaged 0.045, whereas the moisture scalar (ξ(w)) had a much larger variation, with an average of 0.312. We propose that further evaluations and improvements in τ′(E) and ξ(w) predictions are essential to reduce the uncertainties in predicting carbon storage by the BEPS and similar diagnostic models. Nature Publishing Group 2015-11-06 /pmc/articles/PMC4635433/ /pubmed/26541245 http://dx.doi.org/10.1038/srep16155 Text en Copyright © 2015, Macmillan Publishers Limited http://creativecommons.org/licenses/by/4.0/ This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ |
spellingShingle | Article Yizhao, Chen Jianyang, Xia Zhengguo, Sun Jianlong, Li Yiqi, Luo Chengcheng, Gang Zhaoqi, Wang The role of residence time in diagnostic models of global carbon storage capacity: model decomposition based on a traceable scheme |
title | The role of residence time in diagnostic models of global carbon storage capacity: model decomposition based on a traceable scheme |
title_full | The role of residence time in diagnostic models of global carbon storage capacity: model decomposition based on a traceable scheme |
title_fullStr | The role of residence time in diagnostic models of global carbon storage capacity: model decomposition based on a traceable scheme |
title_full_unstemmed | The role of residence time in diagnostic models of global carbon storage capacity: model decomposition based on a traceable scheme |
title_short | The role of residence time in diagnostic models of global carbon storage capacity: model decomposition based on a traceable scheme |
title_sort | role of residence time in diagnostic models of global carbon storage capacity: model decomposition based on a traceable scheme |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4635433/ https://www.ncbi.nlm.nih.gov/pubmed/26541245 http://dx.doi.org/10.1038/srep16155 |
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