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

Abstract

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. Lastly, our findings emphasize the importance of improved models of carbon allocation to biomass compartments, distribution of vegetation types in models, and reproduction of pre-industrial vegetation conditions, in order to reduce the uncertainty in forest biomass simulated by ESMs.

Authors:
ORCiD logo; ORCiD logo; ORCiD logo; ORCiD logo; ; ORCiD logo; ORCiD logo
Publication Date:
Research Org.:
Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Oak Ridge Leadership Computing Facility (OLCF)
Sponsoring Org.:
USDOE Office of Science (SC)
OSTI Identifier:
1460139
Alternate Identifier(s):
OSTI ID: 1464025
Grant/Contract Number:  
[AC05-00OR22725]
Resource Type:
Published Article
Journal Name:
Scientific Reports
Additional Journal Information:
[Journal Name: Scientific Reports Journal Volume: 8 Journal Issue: 1]; Journal ID: ISSN 2045-2322
Publisher:
Nature Publishing Group
Country of Publication:
United Kingdom
Language:
English
Subject:
54 ENVIRONMENTAL SCIENCES

Citation Formats

Yang, Cheng-En, Mao, Jiafu, Hoffman, Forrest M., Ricciuto, Daniel M., Fu, Joshua S., Jones, Chris D., and Thurner, Martin. Uncertainty Quantification of Extratropical Forest Biomass in CMIP5 Models over the Northern Hemisphere. United Kingdom: N. p., 2018. Web. doi:10.1038/s41598-018-29227-7.
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. United Kingdom. doi:10.1038/s41598-018-29227-7.
Yang, Cheng-En, Mao, Jiafu, Hoffman, Forrest M., Ricciuto, Daniel M., Fu, Joshua S., Jones, Chris D., and Thurner, Martin. Thu . "Uncertainty Quantification of Extratropical Forest Biomass in CMIP5 Models over the Northern Hemisphere". United Kingdom. doi:10.1038/s41598-018-29227-7.
@article{osti_1460139,
title = {Uncertainty Quantification of Extratropical Forest Biomass in CMIP5 Models over the Northern Hemisphere},
author = {Yang, Cheng-En and Mao, Jiafu and Hoffman, Forrest M. and Ricciuto, Daniel M. and Fu, Joshua S. and Jones, Chris D. and Thurner, Martin},
abstractNote = {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. Lastly, our findings emphasize the importance of improved models of carbon allocation to biomass compartments, distribution of vegetation types in models, and reproduction of pre-industrial vegetation conditions, in order to reduce the uncertainty in forest biomass simulated by ESMs.},
doi = {10.1038/s41598-018-29227-7},
journal = {Scientific Reports},
number = [1],
volume = [8],
place = {United Kingdom},
year = {2018},
month = {7}
}

Journal Article:
Free Publicly Available Full Text
Publisher's Version of Record
DOI: 10.1038/s41598-018-29227-7

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Cited by: 3 works
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