Research Highlights

Recent highlights of our science

Causes and Implications of Persistent Atmospheric CO2 Biases in ESMs

February 14, 2014

An emergent constraint based on carbon inventories was applied to constrain future atmsopheric CO2 projections from CMIP5 ESMs.

Future vs. Contemporary Atmospheric Carbon Dioxide Mole Fraction
(a) Future (2060) versus contemporary (2010) atmospheric CO2 mole fractionfit for CMIP5 emissions-forced simulations of RCP 8.5 and (b) future (2100) versus contemporary (2010) atmospheric CO2 mole fraction for the same set of model simulations. The observed atmospheric CO2 mole fraction is represented by the vertical line at 384.6 ppm with an uncertainty range (±0.5 ppm) shown in gray. The linear regression model is represented by the blue line surrounded by red dashed lines indicating a 95% confidence interval. While a point is plotted for the historical observed atmoshperic CO2 and the RCP 8.5 concentration trajetory derived from a reduced form model without explicit feedbacks, that point is not included in the linear regression.

  • Much of the model-to-model variation in projected CO2 during the 21st century is tied to biases that existed during the observational era.
  • Model differences in the representation of concetration–carbon feedbacks and other slowly changing carbon cycle processes appear to be the primary driver of this variability.
  • Range of temperature increases at 2100 slightly reduced, from 5.1 ± 2.2°C for the full ensemble, to 5.0 ± 1.9°C after applying the emergent constraint.

Probability Density of Atmospheric Carbon Dioxide Mole Fraction
The probability density of CO2 mole fraction predictions from the contermporary CO2 tuned model (CCTM) peaks lower than the probability density for the multi-model mean for (a) 2060 and (b) 2100. In addition, the width of the probability density is much smaller for the CCTM, by almost a factor of 6 at 2060 and almost a factor of 5 at 2100, indicating a significant reduction in the range of uncertainty for the CCTM prediction.

Best estimate using Mauna Loa CO2

At 2060: 600 ± 14 ppm, 21 ppm below the multi-model mean
At 2100: 947 ± 35 ppm, 32 ppm below the multi-model mean

Hoffman, Forrest M., James T. Randerson, Vivek K. Arora, Qing Bao, Patricia Cadule, Duoying Ji, Chris D. Jones, Michio Kawamiya, Samar Khatiwala, Keith Lindsay, Atsushi Obata, Elena Shevliakova, Katharina D. Six, Jerry F. Tjiputra, Evgeny M. Volodin, and Tongwen Wu. February 14, 2014. “Causes and Implications of Persistent Atmospheric Carbon Dioxide Biases in Earth System Models.” J. Geophys. Res. Biogeosci., 119(2):141–162. doi:10.1002/2013JG002381.
Most downloaded JGR-B paper for February 2014!

Emergent Constraint Developed from CMIP5 ESMs
Click to download this highlight slide