Assessment of Arctic and Antarctic Sea Ice Predictability in CMIP5 Decadal Hindcasts
Abstract. This paper examines the ability of coupled global climate models to predict decadal variability of Arctic and Antarctic sea ice. We analyze decadal hindcasts/predictions of 11 CMIP5 models. Decadal hindcasts exhibit a large multi-model spread in the simulated sea ice extent, with some models deviating significantly from the observations. For the models having large biases and using full-field initialization, the predicted sea ice extent quickly drifts away from the initial constraint, deteriorating the decadal predictive skill. The anomaly correlation analysis between the decadal hindcast and observed sea ice suggests that in the Arctic, for most models, the areas showing significant predictive skill become broader associated with increasing lead times. This area expansion is largely because nearly all the models are capable of predicting the observed decreasing Arctic sea ice cover. Sea ice extent in the north Pacific has better predictive skill than that in the north Atlantic (particularly at a lead-time of 3–7 years), but there is a re-emerging predictive skill in the north Atlantic at a lead-time of 6–8 years. In contrast to the Arctic, Antarctic sea ice decadal hindcasts do not show broad predictive skill at any time scales, and there is no obvious improvement linking the areal extent of significant predictive skill to lead-time increase. This might be because nearly all the models predict a retreating Antarctic sea ice cover, opposite to the observations. For the Arctic, the predictive skill of the MMEE outperforms most models and the persistence prediction at longer time scales, which is not the case for the Antarctic.