Climate sensitivity is the warming of global surface temperatures due to a doubling of atmospheric CO2. Previous estimates suggest a large uncertainty range for its values. Here we use temperature reconstructions from the Last Glacial Maximum (LGM; 20,000 years ago; see left figure) together with climate model simulations in order to estimate probability density functions of the climate sensitivity following the approach of Schmittner et al. (2011). The LGM was a period of low CO2 concentrations, large ice sheets over North America and northern Europe, lower sea level, and generally colder climate. Climate models with different climate sensitivities will be constructed and compared with the reconstructions using a Bayesian statistical method.
the National Science Foundation's Paleo Perspectives on Climate Change (P2C2) Program
We have developed a method to incorporate cloud feedbacks from complex climate models into an intermediate complexity model (Ullman and Schmittner, 2017). This method, which is based on regressing radiative fluxes at the top-of-the-atmosphere to local surface temperature changes, reproduces well the magnitudes and spread of cloud feedbacks in complex climate models. It is used together with the consideration of other uncertainties in a new ensemble of simulations of the LGM and future climate with the intermediate complexity University of Victoria (UVic) climate model.