Abstract

The simulation of Arctic sea ice and surface winds changes significantly when Community Climate System Model version 3 (CCSM3) resolution is increased from T42 (∼2.8°) to T85 (∼1.4°). At T42 resolution, Arctic sea ice is too thick off the Siberian coast and too thin along the Canadian coast. Both of these biases are reduced at T85 resolution. The most prominent surface wind difference is the erroneous North Polar summer anticyclone, present at T42 but absent at T85.

An offline sea ice model is used to study the effect of the surface winds on sea ice thickness. In this model, the surface wind stress is prescribed alternately from reanalysis and the T42 and T85 simulations. In the offline model, CCSM3 surface wind biases have a dramatic effect on sea ice distribution: with reanalysis surface winds annual-mean ice thickness is greatest along the Canadian coast, but with CCSM3 winds thickness is greater on the Siberian side. A significant difference between the two CCSM3-forced offline simulations is the thickness of the ice along the Canadian archipelago, where the T85 winds produce thicker ice than their T42 counterparts. Seasonal forcing experiments, with CCSM3 winds during spring and summer and reanalysis winds in fall and winter, relate the Canadian thickness difference to spring and summer surface wind differences. These experiments also show that the ice buildup on the Siberian coast at both resolutions is related to the fall and winter surface winds.

The Arctic atmospheric circulation is examined further through comparisons of the winter sea level pressure (SLP) and eddy geopotential height. At both resolutions the simulated Beaufort high is quite weak, weaker at higher resolution. Eddy heights show that the wintertime Beaufort high in reanalysis has a barotropic vertical structure. In contrast, high CCSM3 SLP in Arctic winter is found in association with cold lower-tropospheric temperatures and a baroclinic vertical structure.

In reanalysis, the summertime Arctic surface circulation is dominated by a polar cyclone, which is accompanied by surface inflow and a deep Ferrel cell north of the traditional polar cell. The Arctic Ferrel cell is accompanied by a northward flux of zonal momentum and a polar lobe of the zonal-mean jet. These features do not appear in the CCSM3 simulations at either resolution.

Abstract

Skillful Arctic sea ice forecasts may be possible for lead times of months or even years owing to the persistence of thickness anomalies. In this study sea ice thickness variability is characterized in fully coupled GCMs and sea ice–ocean-only models (IOMs) that are forced with an estimate of observations derived from atmospheric reanalysis and satellite measurements. Overall, variance in sea ice thickness is greatest along Arctic Ocean coastlines. Sea ice thickness anomalies have a typical time scale of about 6–20 months, a time scale that lengthens about a season when accounting for ice transport, and a typical length scale of about 500–1000 km. The range of these scales across GCMs implies that an estimate of the number of thickness monitoring locations needed to characterize the full Arctic basin sea ice thickness variability field is model dependent and would vary between 3 and 14. Models with a thinner mean ice state tend to have ice-thickness anomalies that are generally shorter lived and smaller in amplitude but have larger spatial scales. Additionally, sea ice thickness variability in IOMs is damped relative to GCMs in part due to strong negative coupling between the dynamic and thermodynamic processes that affect sea ice thickness. The significance for designing prediction systems is discussed.

Abstract

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 with that in observations. Each model simulates reduced Arctic sea ice area and volume in the seasons following an El Niño relative to a La Niña. The 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.

Abstract

This study explores the role of sea ice freshwater and salt fluxes in modulating twenty-first-century surface warming in the Southern Ocean via analysis of sensitivity experiments in the Community Climate System Model, version 3 (CCSM3). In particular, the role of a change in these fluxes in causing surface cooling, expanding sea ice, and increasing deep oceanic storage of heat in the Southern Ocean is investigated. The results indicate that in response to the doubling of CO₂ concentrations in the atmosphere in CCSM3, net freshwater input from sea ice to the ocean increases south of 58°S (owing to less growth) and decreases from 48° to 58°S (owing to less melt). The freshwater source from changing precipitation in the model is considerably less than from sea ice south of 58°S, but it serves to compensate for the reduction in sea ice melt near the ice edge, leaving almost no net freshwater flux change between about 48° and 58°S. As a result, freshwater input principally from sea ice reduces ocean convection, which in turns reduces the entrainment of heat into the mixed layer and reduces the upward heat transport along isopycnals below about 1000 m. The reduced upward heat transport (from all sources) causes deep-ocean heating south of 60°S and below 500-m depth, with a corresponding surface cooling in large parts of the Southern Ocean in the model. These results indicate that changing sea ice freshwater and salt fluxes are a major component of the twenty-first-century delay in surface warming of the Southern Ocean and weak reduction in Antarctic sea ice in model projections.

Abstract

Rain on snow (ROS) events are rare in most parts of the circumpolar Arctic, but have been shown to have great impact on soil surface temperatures and serve as triggers for avalanches in the midlatitudes, and they have been implicated in catastrophic die-offs of ungulates. The study of ROS is inherently challenging due to the difficulty of both measuring rain and snow in the Arctic and representing ROS events in numerical weather predictions and climate models. In this paper these challenges are addressed, and the occurrence of these events is characterized across the Arctic. Incidents of ROS in Canadian meteorological station data and in the 40-yr ECMWF Re-Analysis (ERA-40) are compared to evaluate the suitability of these datasets for characterizing ROS. The ERA-40 adequately represents the large-scale synoptic fields of ROS, but too often has a tendency toward drizzle. Using the ERA-40, a climatology of ROS events is created for thresholds that impact ungulate populations and permafrost. It is found that ROS events with the potential to harm ungulate mammals are widespread, but the large events required to impact permafrost are limited to the coastal margins of Beringia and the island of Svalbard. The synoptic conditions that led to ROS events on Banks Island in October of 2003, which killed an estimated 20 000 musk oxen, and on Svalbard, which led to significant permafrost warming in December of 1995, are examined. Compositing analyses are used to show the prevailing synoptic conditions that lead to ROS in four disparate parts of the Arctic. Analysis of ROS in the daily output of a fully coupled GCM under a future climate change scenario finds an increase in the frequency and areal extent of these events for many parts of the Arctic over the next 50 yr and that expanded regions of permafrost become vulnerable to ROS.

Abstract

The temporal characteristics of Arctic sea ice extent and area are analyzed in terms of their lagged correlation in observations and a GCM ensemble. Observations and model output generally match, exhibiting a red-noise spectrum, where significant correlation (or memory) is lost within 2–5 months. September sea ice extent is significantly correlated with extent of the previous August and July, and thus these months show a predictive skill of the summer minimum extent. Beyond this initial loss of memory, there is an increase in correlation—a reemergence of memory—that is more ubiquitous in the model than observations. There are two distinct modes of memory reemergence in the model. The first, a summer-to-summer reemergence arises within the model from the persistence of thickness anomalies and their influence on ice area. The second, which is also seen in observations, is associated with anomalies in the growth season that originate in the melt season. This reemergence stems from the several-month persistence of SSTs. In the model memory reemergence is enhanced by the sea ice albedo feedback. The same mechanisms that give rise to reemergence also enhance the 1-month lagged correlation during summer and winter. The study finds the least correlation between successive months when the sea ice is most rapidly advancing or retreating.

Abstract

North Atlantic sea ice anomalies are thought to play an important role in the abrupt Dansgaard–Oeschger (D–O) cycles of the last glacial period. This model study investigates the impacts of changes in North Atlantic sea ice extent in glacial climates to help provide geographical constraints on their involvement in D–O cycles. Based on a coupled climate model simulation of the Last Glacial Maximum (21 ka), the Nordic seas and western North Atlantic (broadly, south of Greenland) are identified as two plausible regions for large and persistent displacements of the sea ice edge in the glacial North Atlantic. Sea ice retreat scenarios targeting these regions are designed to represent ice cover changes associated with the cold-to-warm (stadial-to-interstadial) transitions of D–O cycles. The atmospheric responses to sea ice retreat in the Nordic seas and in the western North Atlantic are tested individually and together using an atmospheric general circulation model. The Nordic seas ice retreat causes 10°C of winter warming and a 50% increase in snow accumulation at Greenland Summit; concomitant ice retreat in the western North Atlantic has little additional effect. The results suggest that displacements of the winter sea ice edge in the Nordic seas are important for creating the observed climate signals associated with D–O cycles in the Greenland ice cores.

Abstract

The mechanisms forcing variability in Southern Ocean sea ice and sea surface temperature from 600 years of a control climate coupled model integration are discussed. As in the observations, the leading mode of simulated variability exhibits a dipole pattern with positive anomalies in the Pacific sector associated with negative anomalies in the Atlantic. It is found that in the Pacific ocean circulation changes associated with variable wind forcing modify the ocean heat flux convergence and sea ice transport, resulting in sea surface temperature and sea ice anomalies. The Pacific ice and ocean anomalies persist over a number of years due to reductions in ocean shortwave absorption reinforcing the initial anomalies. In the Atlantic sector, no single process dominates in forcing the anomalies. Instead there are contributions from changing ocean and sea ice circulation and surface heat fluxes. While the absorbed solar radiation in the Atlantic is modified by the changing surface albedo, the anomalies are much shorter-lived than in the Pacific because the ocean circulation transports them northward, removing them from ice formation regions. Sea ice and ocean anomalies associated with the El Niño–Southern Oscillation and the Southern Annular Mode both exhibit a dipole pattern and contribute to the leading mode of ice and ocean variability.

Abstract

The response of the Southern Ocean to a repeating seasonal cycle of ozone loss is studied in two coupled climate models and is found to comprise both fast and slow processes. The fast response is similar to the interannual signature of the southern annular mode (SAM) on sea surface temperature (SST), onto which the ozone hole forcing projects in the summer. It comprises enhanced northward Ekman drift, inducing negative summertime SST anomalies around Antarctica, earlier sea ice freeze-up the following winter, and northward expansion of the sea ice edge year-round. The enhanced northward Ekman drift, however, results in upwelling of warm waters from below the mixed layer in the region of seasonal sea ice. With sustained bursts of westerly winds induced by ozone hole depletion, this warming from below eventually dominates over the cooling from anomalous Ekman drift. The resulting slow time-scale response (years to decades) leads to warming of SSTs around Antarctica and ultimately a reduction in sea ice cover year-round. This two-time-scale behavior—rapid cooling followed by slow but persistent warming—is found in the two coupled models analyzed: one with an idealized geometry and the other with a complex global climate model with realistic geometry. Processes that control the time scale of the transition from cooling to warming and their uncertainties are described. Finally the implications of these results are discussed for rationalizing previous studies of the effect of the ozone hole on SST and sea ice extent.

Abstract

A new method, called contour shifting, is proposed for correcting the bias in forecasts of contours such as sea ice concentration above certain thresholds. Retrospective comparisons of observations and dynamical model forecasts are used to build a statistical spatiotemporal model of how predicted contours typically differ from observed contours. Forecasted contours from a dynamical model are then adjusted to correct for expected errors in their location. The statistical model changes over time to reflect the changing error patterns that result from reducing sea ice cover in the satellite era in both models and observations. For an evaluation period from 2001 to 2013, these bias-corrected forecasts are on average more accurate than the unadjusted dynamical model forecasts for all forecast months in the year at four different lead times. The total area, which is incorrectly categorized as containing sea ice or not, is reduced by 3.3 × 10⁵ km² (or 21.3%) on average. The root-mean-square error of forecasts of total sea ice area is also reduced for all lead times.