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Uncertainty Quantification of Extratropical Forest Biomass in CMIP5 Models over the Northern Hemisphere

Simplified representations of processes influencing forest biomass in Earth system models (ESMs) contribute to large uncertainty in projections. We evaluate forest biomass from eight ESMs outputs archived in the Coupled Model Intercomparison Project Phase 5 (CMIP5) using the biomass data synthesized...

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Autores principales: Yang, Cheng-En, Mao, Jiafu, Hoffman, Forrest M., Ricciuto, Daniel M., Fu, Joshua S., Jones, Chris D., Thurner, Martin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6053416/
https://www.ncbi.nlm.nih.gov/pubmed/30026558
http://dx.doi.org/10.1038/s41598-018-29227-7
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author Yang, Cheng-En
Mao, Jiafu
Hoffman, Forrest M.
Ricciuto, Daniel M.
Fu, Joshua S.
Jones, Chris D.
Thurner, Martin
author_facet Yang, Cheng-En
Mao, Jiafu
Hoffman, Forrest M.
Ricciuto, Daniel M.
Fu, Joshua S.
Jones, Chris D.
Thurner, Martin
author_sort Yang, Cheng-En
collection PubMed
description Simplified representations of processes influencing forest biomass in Earth system models (ESMs) contribute to large uncertainty in projections. We evaluate forest biomass from eight ESMs outputs archived in the Coupled Model Intercomparison Project Phase 5 (CMIP5) using the biomass data synthesized from radar remote sensing and ground-based observations across northern extratropical latitudes. ESMs exhibit large biases in the forest distribution, forest fraction, and mass of carbon pools that contribute to uncertainty in forest total biomass (biases range from −20 Pg C to 135 Pg C). Forest total biomass is primarily positively correlated with precipitation variations, with surface temperature becoming equally important at higher latitudes, in both simulations and observations. Relatively small differences in forest biomass between the pre-industrial period and the contemporary period indicate uncertainties in forest biomass were introduced in the pre-industrial model equilibration (spin-up), suggesting parametric or structural model differences are a larger source of uncertainty than differences in transient responses. Our findings emphasize the importance of improved (1) models of carbon allocation to biomass compartments, (2) distribution of vegetation types in models, and (3) reproduction of pre-industrial vegetation conditions, in order to reduce the uncertainty in forest biomass simulated by ESMs.
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spelling pubmed-60534162018-07-23 Uncertainty Quantification of Extratropical Forest Biomass in CMIP5 Models over the Northern Hemisphere Yang, Cheng-En Mao, Jiafu Hoffman, Forrest M. Ricciuto, Daniel M. Fu, Joshua S. Jones, Chris D. Thurner, Martin Sci Rep Article Simplified representations of processes influencing forest biomass in Earth system models (ESMs) contribute to large uncertainty in projections. We evaluate forest biomass from eight ESMs outputs archived in the Coupled Model Intercomparison Project Phase 5 (CMIP5) using the biomass data synthesized from radar remote sensing and ground-based observations across northern extratropical latitudes. ESMs exhibit large biases in the forest distribution, forest fraction, and mass of carbon pools that contribute to uncertainty in forest total biomass (biases range from −20 Pg C to 135 Pg C). Forest total biomass is primarily positively correlated with precipitation variations, with surface temperature becoming equally important at higher latitudes, in both simulations and observations. Relatively small differences in forest biomass between the pre-industrial period and the contemporary period indicate uncertainties in forest biomass were introduced in the pre-industrial model equilibration (spin-up), suggesting parametric or structural model differences are a larger source of uncertainty than differences in transient responses. Our findings emphasize the importance of improved (1) models of carbon allocation to biomass compartments, (2) distribution of vegetation types in models, and (3) reproduction of pre-industrial vegetation conditions, in order to reduce the uncertainty in forest biomass simulated by ESMs. Nature Publishing Group UK 2018-07-19 /pmc/articles/PMC6053416/ /pubmed/30026558 http://dx.doi.org/10.1038/s41598-018-29227-7 Text en © The Author(s) 2018 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Yang, Cheng-En
Mao, Jiafu
Hoffman, Forrest M.
Ricciuto, Daniel M.
Fu, Joshua S.
Jones, Chris D.
Thurner, Martin
Uncertainty Quantification of Extratropical Forest Biomass in CMIP5 Models over the Northern Hemisphere
title Uncertainty Quantification of Extratropical Forest Biomass in CMIP5 Models over the Northern Hemisphere
title_full Uncertainty Quantification of Extratropical Forest Biomass in CMIP5 Models over the Northern Hemisphere
title_fullStr Uncertainty Quantification of Extratropical Forest Biomass in CMIP5 Models over the Northern Hemisphere
title_full_unstemmed Uncertainty Quantification of Extratropical Forest Biomass in CMIP5 Models over the Northern Hemisphere
title_short Uncertainty Quantification of Extratropical Forest Biomass in CMIP5 Models over the Northern Hemisphere
title_sort uncertainty quantification of extratropical forest biomass in cmip5 models over the northern hemisphere
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6053416/
https://www.ncbi.nlm.nih.gov/pubmed/30026558
http://dx.doi.org/10.1038/s41598-018-29227-7
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