Uncertainty Quantification of Extratropical Forest Biomass in CMIP5 Models over the Northern Hemisphere
Abstract
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. 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.
- Publication Date:
- Research Org.:
- Oak Ridge National Laboratory (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. https://doi.org/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. https://doi.org/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 = {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. 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.},
doi = {10.1038/s41598-018-29227-7},
journal = {Scientific Reports},
number = 1,
volume = 8,
place = {United Kingdom},
year = {Thu Jul 19 00:00:00 EDT 2018},
month = {Thu Jul 19 00:00:00 EDT 2018}
}
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