Dr. Chris Forest
Center for Global Change Science
Massachusetts Institute of Technology

The prediction of climate change for the 21st century requires a comprehensive probabilistic approach. We must consider uncertainty in both the climate system response and future forcings. On large-scales, the uncertainty in climate system response to forcings is characterized by the climate sensitivity (the equilibrium surface temperature change in response to a doubling of CO2 concentrations) and the rate of heat uptake into the deep-ocean. Together, these two climate system properties determine the transient response to climate forcings. To quantify these uncertainties, we use the observed temperature changes in the 20th century to estimate the joint probability distribution for these quantities. Specifically, we use a Bayesian hierarchical model to estimate the distribution for the climate system properties in the MIT Integrated Global System Model (IGSM). This also allows us to consider the IPCC AR4 climate models within this context. Unfortunately, these distributions alone are not sufficient to predict climate change because the uncertain future anthropogenic forcings must also be included. This is provided by probabilistic emissions scenarios from the emissions model component of the MIT IGSM. By combining these results, predictions for 21st century climate change will be presented for reference and stabilization scenarios that incorporate these multiple sources of uncertainty.