The El Niño-Southern Oscillation (ENSO) and its teleconnections form the leading mode of interannual variability in the global climate system, yet the small sample size of ENSO events during which we have reliable Arctic observations makes constraining its influence on Arctic sea ice challenging. We compare the influence of ENSO on Arctic sea ice in six models from the Multi-Model Large Ensemble Archive to that in observations. Each model simulates reduced Arctic sea ice area and volume in the seasons following an El Niño compared to a La Niña. The spatial patterns of sea ice concentration and thickness responses to ENSO are spatially heterogeneous, with regions of increased and decreased sea ice. The small sample size of ENSO events in observations is shown to preclude a statistically significant sea ice response from being identified. While models agree with one another on many aspects of the sea ice response to ENSO, some features are model-dependent. For example, the CESM1-LE alone displays a delayed melting response in summer, driven by reduced surface albedo and increased shortwave absorption. A positive Arctic Oscillation and a deepened Aleutian Low are common responses to ENSO across models and observations. These patterns of atmospheric variability are quantitatively shown to be key in linking ENSO to Arctic sea ice in most models, acting primarily through sea ice dynamics to generate anomalous sea ice thickness and concentration patterns.

Arctic cyclones are an extremely common, year-round phenomenon, with substantial influence on sea ice. However, few studies address the heterogeneity in the spatial patterns in the atmosphere and sea ice during Arctic cyclones. We investigate these spatial patterns by compositing on cyclones from 1985-2016 using a novel, cyclone-centered approach that reveals conditions as functions of bearing and distance from cyclone centers. An axisymmetric, cold core model for the structure of Arctic cyclones has previously been proposed, however, we show that the structure of Arctic cyclones is comparable to those in the mid-latitudes, with cyclonic surface winds, a warm, moist sector to the east of cyclones and a cold, dry sector to the west. There is no consensus on the impact of Arctic cyclones on sea ice, as some studies have shown that Arctic cyclones lead to sea ice growth and others to sea ice loss. Instead, we find that sea ice decreases to the east of Arctic cyclones and increases to the west, with the greatest changes occurring in the marginal ice zone. Using a sea ice model forced with prescribed atmospheric reanalysis, we reveal the relative importance of the dynamic and thermodynamic forcing of Arctic cyclones on sea ice. The dynamic and thermodynamic responses of sea ice concentration to cyclones are comparable in magnitude, however dynamic processes dominate the response of sea ice thickness and are the primary driver of the east-west difference in the sea ice response to cyclones.

Predictability of sea ice during extreme sea ice loss events on subseasonal (daily to weekly) timescales is explored in dynamical forecast models. These extreme sea ice loss events (defined as the 5th percentile of the 5-day change in sea ice extent) exhibit substantial regional and seasonal variability—in the central Arctic Ocean basin, most subseasonal rapid ice loss occurs in the summer, but in the marginal seas, rapid sea ice loss occurs year-round. Dynamical forecast models are largely able to capture the seasonality of these extreme sea ice loss events. In most regions in the summertime, sea ice forecast skill is lower on extreme sea ice loss days than on non-extreme days, despite evidence that links these extreme events to large-scale atmospheric patterns; in the wintertime, the difference between extreme and non-extreme days is less pronounced. In a damped anomaly forecast benchmark estimate, the forecast error remains high following extreme sea ice loss events and does not return to typical error levels for many weeks; this signal is less robust in the dynamical forecast models but still present. Overall, these results suggest that sea ice forecast skill is generally lower during and after extreme sea ice loss events; and that while dynamical forecast models are capable of simulating extreme sea ice loss events with similar characteristics to what we observe, forecast skill from dynamical models is limited by biases in mean state and variability and errors in the initialization.

<p>The effects of Arctic cyclones on sea ice are the subject of many papers, however aside from individual case studies, few address the heterogeneity in the spatial pattern of the sea ice response.</p><p>We composite atmospheric conditions from ERA5 reanalysis and satellite sea ice concentrations on Arctic cyclones using a storm-centered approach to reveal the typical atmosphere and sea ice responses at different bearings and distances relative to an Arctic cyclone.</p><p>Asymmetry in the pattern of the sea ice concentration response to cyclones is revealed, with increased growth/reduced melt to the west of cyclones and decreased growth/increased melt to the east.</p><p>In part, this is explained by heterogeneity in the spatial patterns of atmospheric temperature and cloud fraction associated with cyclones, which result in heterogeneity in patterns of the surface energy fluxes.</p><p>Using the CICE sea ice model forced with prescribed atmospheric reanalysis from the Japan Meteorological Agency, we reveal the relative importance of the dynamic and thermodynamic forcing of cyclones on sea ice, as well as the spatial patterns of each. The dynamic and thermodynamic responses of sea ice concentration to cyclones are comparable in magnitude, however dynamic processes dominate the response of sea ice thickness.</p><p>These results highlight and explain important details often missed when answering “do cyclones cause an increase or decrease sea ice?”, as it appears the answer is both.</p>