Probabilistic assessment of “dangerous” climate change and emissions pathways

Footnotes

• ↵ ‡ To whom correspondence should be addressed. E-mail: shs{at}stanford.edu.

• Author contributions: S.H.S. and M.D.M. designed research, performed research, contributed new reagents/analytic tools, analyzed data, and wrote the paper.

• This contribution is part of the special series of Inaugural Articles by members of the National Academy of Sciences elected on April 30, 2002.

• Abbreviations: DAI, dangerous anthropogenic interference; CDF, cumulative density function; CO₂e, CO₂ equivalent; SC, slow change; RC, rapid change; OS, overshoot scenario; IPCC, Intergovernmental Panel on Climate Change; TAR, Third Assessment Report; EU, European Union; PDF, probability density function; MEA, maximum exceedence amplitude; DY, degree years.

• See accompanying Profile on page 15725.

• ↵ § During the negotiations leading to the creation of the Kyoto Protocol, the Alliance of Small Island States submitted a draft protocol requiring 20% cuts in emissions by 2005 for industrialized nations. Clearly, the Kyoto targets are not as stringent as this target proposed by one stakeholder group.

• ↵ ¶ Research published after the TAR has indicated that some abrupt nonlinear global changes, such as breakdown of the Greenland or Western Antarctic ice sheets, may be triggered by lower temperature thresholds than those currently indicated in Fig. 1, column V (e.g., ref. 16). Therefore, a stakeholder basing his evaluation of DAI on Fig. 1, column V would likely produce a distribution for DAI thresholds lower than the one reported here if this information were taken into account, as it is likely to be in the next IPCC assessment in 2007.

• ↵ ∥ In this article, we make an effort, as in ref. 19, to differentiate between emissions scenarios, which represent descriptions of possible future states of the world and the characteristics relevant for emissions, emissions pathways, which represent time-evolving paths for global emissions of greenhouse gases and aerosols, and concentration profiles, which represent time-evolving trajectories for atmospheric concentrations of greenhouse gases and aerosols.

• ↵ ** O'Neill and Oppenheimer (20) compare the future temperature profiles generated by their emissions pathways to thresholds for individual climate impacts that may be considered dangerous, and consider the sensitivity of their results to three values for climate sensitivity, but they do not produce PDFs for their results.

• ↵ †† The two-box model is of the form: where T(t) is the temperature in the upper box in year t, T _LO(t) is the temperature in the lower box in year t, F(t) is the radiative forcing above preindustrial levels in year t, and λ, σ₁, σ₂, and σ₃ are constants as defined in ref. 29. We adjust σ₁ and σ₃ to use a 1-year time step by dividing σ₁ and σ₃ by 10.

• ↵ ‡‡ Our presentation of results is intended to demonstrate our probabilistic framework, and presenting separately the results using each climate sensitivity distribution requires, for each analysis step, either one very busy figure or three separate figures displaying essentially the same information. We believe such complexity would obscure the demonstration of our analysis methods while adding little intellectual value.

• ↵ §§ The DAI-EU threshold is defined as 2°C above preindustrial temperatures, while we present temperature distributions of temperature increase above 2000. Therefore, we express the DAI-EU threshold as 1.4°C, based on the central estimate of 0.6°C warming over the 20th century in the IPCC TAR (21).

• ↵ ¶¶ This is strictly true when using a simple climate model with a single equilibrium warming level for a given radiative forcing. Some nonlinear processes not included in our simple model can create multiple equilibria and path dependence (e.g., ref. 35). In such models, OS could imply lower thresholds for DAI than those we report here with this linear model.

• Copyright © 2005, The National Academy of Sciences