Model Structure and Climate Data Uncertainty in Historical Simulations of the Terrestrial Carbon Cycle (1850–2014)
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- National Center for Atmospheric Research Boulder CO USA
- Computational Earth Sciences Group Oak Ridge National Laboratory Oak Ridge TN USA, Department of Civil and Environmental Engineering University of Tennessee, Knoxville Knoxville TN USA
- Computational Earth Sciences Group Oak Ridge National Laboratory Oak Ridge TN USA
The divergence among Earth system models in the terrestrial carbon cycle has prompted interest in how to reduce uncertainty. Previous studies have identified model structural uncertainty arising from process parameterizations and parameter values. The current study highlights the importance of climate forcing in generating carbon cycle uncertainty. We use simulations in which three models (Community Land Model version 4 (CLM4), CLM4.5, CLM5) with substantially different carbon cycles are forced with two climate reconstructions (CRUNCEPv7, Global Soil Wetness Project 3 version 1 (GSWP3v1)) to examine the contributions of model structure and climate to uncertainty in the carbon cycle over the period 1850–2014. Climate uncertainty for global annual net biome production exceeds one third of total uncertainty (defined as the sum of climate and model structure uncertainty) in the first half of the twentieth century, but declines after the 1950s. Global annual gross primary productivity, net primary productivity, heterotrophic respiration, and vegetation and soil carbon stocks have substantial climate uncertainty (relative to total uncertainty) throughout the simulation period. Climate forcing contributes more than one half of total uncertainty for these carbon cycle fluxes and stocks throughout boreal North America and Eurasia, some midlatitude regions, and in eastern Amazonia and western equatorial Africa during the decade 2000–2009. Comparison with observationally based data sets of the carbon cycle using model benchmarking methods provides insight into strengths and deficiencies among models and climate forcings, but we caution against overreliance on benchmarking to discriminate among models. The conceptualization of uncertainty arising from this study implies embracing multiple feasible model simulations rather than focusing on which model or simulation is best.
- Research Organization:
- Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)
- Sponsoring Organization:
- USDOE; USDOE Office of Science (SC), Biological and Environmental Research (BER). Earth and Environmental Systems Science; National Aeronautics and Space Administration (NASA); National Science Foundation (NSF); USDA Division
- Grant/Contract Number:
- DE‐AC05‐00OR22725; AC05‐00OR22725; NNX17AK19G; 2015‐67003‐23485; 1852977
- OSTI ID:
- 1572126
- Alternate ID(s):
- OSTI ID: 1572127; OSTI ID: 1785485; OSTI ID: 1820878
- Journal Information:
- Global Biogeochemical Cycles, Journal Name: Global Biogeochemical Cycles Vol. 33 Journal Issue: 10; ISSN 0886-6236
- Publisher:
- American Geophysical Union (AGU)Copyright Statement
- Country of Publication:
- United States
- Language:
- English
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