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Surface temperatures in the Arctic are increasing more than twice as fast as the global average due to Arctic amplification. This warming gives rise to new types of extreme events that can have particularly large impacts. Here, we study the interplay of mean warming and changes in internal variability to better understand and constrain the intensity and frequency of temperature extremes in the Arctic, both regionally and seasonally.For this study, we analyze projected mean and extreme surface air temperatures in the Arctic for different levels of global warming based on output data from multiple single-model initial-condition large ensembles, with the Max Planck Institute Grand Ensemble (MPI-GE) at the core of the analysis. We use a time-slice approach to construct representative samples of the pre-industrial climate and the climate at different levels of global warming, including the Paris Agreement targets of 1.5 °C and 2 °C.Considering pan-Arctic temperatures, we find that the mean warming is strongest in winter (~3.5 times annual mean global warming) and lowest in summer (~1.05 times annual mean global warming), which leads to a weakening of the Arctic seasonal cycle with global warming. Moreover, the change in the return levels of extreme temperatures is particularly strong for cold extremes, rendering extremely cold temperatures seldom in a warming Arctic. The level of global warming is strongly impacting the frequency of extreme events. For example, warm extremes that occur every 100 years at 1.5 °C of global warming, occur more than once in 10 years at 2 °C of global warming, and cold extremes that occur every 10 years at 1.5 °C global warming, occur only about every 200 years at 2 °C of global warming (based on MPI-GE data). The response of Arctic mean temperatures to global warming results from a local temperature response that varies substantially for different regions and types of surfaces (land, ice sheet, open ocean, sea ice). We find the most drastic warming, accompanied by a strong reduction of variability, in winter temperatures over the northern Barents Sea linked to its ‘Atlantification’. Lastly, we also note a considerable difference in the Arctic temperature response for the same level of global warming in a transient versus a quasi-equilibrium climate state.The results of our study allow us to quantify expected changes in the Arctic temperature range with global warming and also to determine when and where, for example, climate mitigation measures are most likely to be visible.

To investigate the inherent predictability of sea ice and its representation in climate models, we compare the seasonal-to-interannual memory of Arctic sea ice as given by lagged correlations of sea-ice area anomalies in large model ensembles (Max Planck Institute Grand Ensemble and Coupled Model Intercomparison Project phase 6) and multiple observational products. We find that state-of-the-art climate models significantly overestimate the memory of pan-Arctic sea-ice area from the summer months into the following year. This cannot be explained by internal variability. We further show that the observed summer memory can be disentangled regionally into a reemergence of positive correlations in the perennial ice zone and negative correlations in the seasonal ice zone; the latter giving rise to the discrepancy between observations and model simulations. These findings could explain some of the predictability gap between potential and operational forecast skill of Arctic sea-ice area identified in previous studies.

The strong decline of Arctic sea ice in recent years has raised growing interest in seasonal-to-interannual predictions of Arctic sea ice. Previous studies have revealed a large predictability gap between potential and operational forecast skill of Arctic sea ice, which could indicate a strong potential for improvement of operational sea ice predictions or hint at a systematic overestimation of sea ice memory in current climate models.Here, we assess and compare memory of Arctic sea ice in terms of lagged correlations of sea ice area anomalies on seasonal to interannual time scales in a large model ensemble (MPI Grand Ensemble) as well as several reanalysis and observational products. While the different datasets show good agreement for short-term memory on time scales of a few months on which persistence is the dominant source of memory, we find substantial differences between model and observational memory behaviour on longer time scales. In particular, we find that memory from the summer sea ice minimum into the following year is significantly overestimated in the model, as lagged correlation values in all observational datasets are outside the range of model variability. Reanalysis data show correlation values that lie in between observational and model mean values, underpinning the hybrid nature of reanalyses combining observations and model behaviour. Extending the analysis of sea ice memory to a regional scale provides further information on the spatial origin of specific memory features in the different datasets and helps in understanding differences between model and real-world behaviour on a physical process level.

Deep water renewal and ventilation of the Baltic Sea is commonly considered to occur solely via saltwater inflows from the North Sea. However, recent analysis of geophysical and sediment proxy data suggests convective deep water formation during wintertime as a second process that has contributed to the ventilation of the northern and central Baltic Sea bottom waters during cold climate periods. Here, we investigate the role of deep water formation in the northern Baltic Sea in a regional ocean circulation model. Selecting the particularly cold winter 1986/1987 as a reference period, we perform sensitivity experiments in which the atmospheric temperature forcing is changed and/or localized brine rejection on subgrid scales is accounted for through a parameterization. We study the sinking and circulation of water masses via passive tracers introduced into the model. Generally, our model results support the established view that convective deep water formation does not play a major role in Baltic Sea deep water renewal. While a reduction of air temperatures does not qualitatively change the sinking and circulation of water masses in our experiments, brine rejection could potentially lead to localized deep water formation. However, the impact is too weak to possibly change the large-scale deep water exchange between the Baltic proper and the northern Baltic sub-basins. Although being in line with established knowledge, through consideration of the model limitations, our results provide insights on how and under which circumstances convective deep water formation could potentially have occurred during cold climate periods. ©2020. The Authors.