Dependency of Feedbacks on Forcing and Climate State in Physics Parameter Ensembles

Climate sensitivity is one of the most important metrics for future climate projections. In previous studies the climate of the last glacial maximum has been used to constrain the range of climate sensitivity, and similarities and differences of temperature response to the forcing of the last glacial maximum and to idealized future forcing have been investigated. The feedback processes behind the response have not, however, been fully explored in a large model parameter space. In this study, the authors first examine the performance of various feedback analysis methods that identify important feedbacks for a physics parameter ensemble in experiments simulating both past and future climates. The selected methods are then used to reveal the relationship between the different ensemble experiments in terms of individual feedback processes. For the first time, all of the major feedback processes for an ensemble of paleoclimate simulations are evaluated. It is shown that the feedback and climate sensitivity parameters depend on the nature of the forcing and background climate state. The forcing dependency arises through the shortwave cloud feedback while the state dependency arises through the combined water vapor and lapse-rate feedback. The forcing dependency is, however, weakened when the feedback is estimated from the forcing that includes tropospheric adjustments. Despite these dependencies, past climate can still be used to provide a useful constraint on climate sensitivity as long as the limitation is properly taken into account because the strength of each feedback correlates reasonably well between the ensembles. It is, however, shown that the physics parameter ensemble does not cover the range of results simulated by structurally different models, which suggests the need for further study exploring both structural and parameter uncertainties.