Abstract
Climate feedbacks have been found to strongly impact the observed amplified Arctic warming. However, Arctic amplification is modeled with a wide spread which partly arises from intermodel differences of the various feedbacks. To explain the spread in modeled Arctic warming, feedback uncertainties and their origins are investigated in 13 climate models in an experiment with abruptly quadrupled CO2. While intermodel differences in the cloud feedback, being strongest in the Tropics, have been found to determine the spread of global mean effective climate sensitivity, we find that in the Arctic the cloud feedback is not responsible for the spread of Arctic warming as its contribution is too small. Instead, the spread of Arctic warming is explained by differing estimates of surface albedo and Planck feedbacks which show the largest intermodel differences. Our results indicate that these uncertainties not only arise from different degrees of simulated Arctic warming but also are partly related to the large differences in initial sea ice cover and surface temperatures which contribute to the increased spread in estimated warming compared to lower latitudes. Further investigations of feedback dependencies to the base state are needed to constrain the impact of initial uncertainties and to obtain robust results. The most significant distinction between models is the sign of the total feedback parameter. While all models investigated here simulate a negative global mean total feedback, only half of them also show negative Arctic feedbacks which implies that Arctic local feedbacks alone suffice to stably adjust Arctic surface temperatures in response to a radiative perturbation. The other half exhibits positive total Arctic feedbacks indicating local runaway systems which need to be balanced by decreased meridional heat transports. Whether or not a model features such a behaviour depends upon the strength of the simulated positive surface albedo versus the negative Planck feedback.
Acknowledgments
We gratefully acknowledge the funding by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) – Project Number 268020496 – TRR 172, within the Transregional Collaborative Research Center “ArctiC Amplification: Climate Relevant Atmospheric and SurfaCe Processes, and Feedback Mechanisms (AC)3 “in sub-project E01 “Assessment of Arctic feedback processes in climate models” (INST 268/331-1). We acknowledge the World Climate Research Program’s Working Group on Coupled Modelling, which is responsible for CMIP, and we thank the climate modeling groups (listed in of this paper) for producing and making available their model output. For CMIP the U.S. Department of Energy’s Program for Climate Model Diagnosis and Intercomparison provides coordinating support and led development of software infrastructure in partnership with the Global Organization for Earth System Science Portals. Furthermore, we thank Dr. Felix Pithan for useful discussions and two anonymous reviewers for their comments on the manuscript.
Disclosure statement
No potential conflict of interest was reported by the authors.