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Kyle C. Armour
,
Cecilia M. Bitz
, and
Gerard H. Roe

Abstract

The sensitivity of global climate with respect to forcing is generally described in terms of the global climate feedback—the global radiative response per degree of global annual mean surface temperature change. While the global climate feedback is often assumed to be constant, its value—diagnosed from global climate models—shows substantial time variation under transient warming. Here a reformulation of the global climate feedback in terms of its contributions from regional climate feedbacks is proposed, providing a clear physical insight into this behavior. Using (i) a state-of-the-art global climate model and (ii) a low-order energy balance model, it is shown that the global climate feedback is fundamentally linked to the geographic pattern of regional climate feedbacks and the geographic pattern of surface warming at any given time. Time variation of the global climate feedback arises naturally when the pattern of surface warming evolves, actuating feedbacks of different strengths in different regions. This result has substantial implications for the ability to constrain future climate changes from observations of past and present climate states. The regional climate feedbacks formulation also reveals fundamental biases in a widely used method for diagnosing climate sensitivity, feedbacks, and radiative forcing—the regression of the global top-of-atmosphere radiation flux on global surface temperature. Further, it suggests a clear mechanism for the “efficacies” of both ocean heat uptake and radiative forcing.

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Hansi A. Singh
,
David S. Battisti
, and
Cecilia M. Bitz

Abstract

A simple model for studying the Dansgaard–Oeschger (D-O) cycles of the last glacial period is presented, based on the T. Dokken et al. hypothesis for D-O cycles. The model is a column model representing the Nordic seas and is composed of ocean boxes stacked below a one-layer sea ice model with an energy-balance atmosphere; no changes in the large-scale ocean overturning circulation are invoked. Parameterizations are included for latent heat polynyas and sea ice export from the column. The resulting heuristic model was found to cycle between stadial and interstadial states at times scales similar to those seen in the proxy observational data, with the presence or absence of perennial sea ice in the Nordic seas being the defining characteristic for each of these states. The major discrepancy between the modeled oscillations and the proxy record is in the length of the interstadial phase, which is shorter than that observed. The modeled oscillations were found to be robust to parameter changes, including those related to the ocean heat flux convergence (OHFC) into the column. Production of polynya ice was found to be an essential ingredient for such sustained oscillatory behavior. A simple parameterization of natural variability in the OHFC enhances the robustness of the modeled oscillations. The authors conclude by discussing the implications of such a hypothesis for the state of the Nordic seas today and its state during the Last Glacial Maximum and contrasting the model to other hypotheses that invoke large-scale changes in the Atlantic meridional overturning circulation for explaining millennial-scale variability in the climate system. An extensive time-scale analysis will be presented in the future.

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Edward Blanchard-Wrigglesworth
,
Kyle C. Armour
,
Cecilia M. Bitz
, and
Eric DeWeaver

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.

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Kelly E. McCusker
,
David S. Battisti
, and
Cecilia M. Bitz

Abstract

Stratospheric sulfate aerosol injection has been proposed to counteract anthropogenic greenhouse gas warming and prevent regional climate emergencies. Global warming is projected to be largest in the polar regions, where consequences to climate change could be emergent, but where the climate response to global warming is also most uncertain. The Community Climate System Model, version 3, is used to evaluate simulations with enhanced CO2 and prescribed stratospheric sulfate to investigate the effects on regional climate. To further explore the sensitivity of these regions to ocean dynamics, a suite of simulations with and without ocean dynamics is run.

The authors find that, when global average warming is roughly canceled by aerosols, temperature changes in the polar regions are still 20%–50% of the changes in a warmed world. Atmospheric circulation anomalies are also not canceled, which affects the regional climate response. It is also found that agreement between simulations with and without ocean dynamics is poorest in the high latitudes. The polar climate is determined by processes that are highly parameterized in climate models. Thus, one should expect that the projected climate response to geoengineering will be at least as uncertain in these regions as it is to increasing greenhouse gases. In the context of climate emergencies, such as melting arctic sea ice and polar ice sheets and a food crisis due to a heated tropics, the authors find that, while it may be possible to avoid tropical climate crises, preventing polar climate emergencies is not certain. A coordinated effort across modeling centers is required to generate a more robust depiction of a geoengineered climate.

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Camille Li
,
David S. Battisti
, and
Cecilia M. Bitz

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.

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Marika M. Holland
,
Cecilia M. Bitz
, and
Elizabeth C. Hunke

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.

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Marika M. Holland
,
Cecilia M. Bitz
,
Elizabeth C. Hunke
,
William H. Lipscomb
, and
Julie L. Schramm

Abstract

The sea ice simulation of the Community Climate System Model version 3 (CCSM3) T42-gx1 and T85-gx1 control simulations is presented and the influence of the parameterized sea ice thickness distribution (ITD) on polar climate conditions is examined. This includes an analysis of the change in mean climate conditions and simulated sea ice feedbacks when an ITD is included. It is found that including a representation of the subgrid-scale ITD results in larger ice growth rates and thicker sea ice. These larger growth rates represent a higher heat loss from the ocean ice column to the atmosphere, resulting in warmer surface conditions. Ocean circulation, most notably in the Southern Hemisphere, is also modified by the ITD because of the influence of enhanced high-latitude ice formation on the ocean buoyancy flux and resulting deep water formation. Changes in atmospheric circulation also result, again most notably in the Southern Hemisphere.

There are indications that the ITD also modifies simulated sea ice–related feedbacks. In regions of similar ice thickness, the surface albedo changes at 2XCO2 conditions are larger when an ITD is included, suggesting an enhanced surface albedo feedback. The presence of an ITD also modifies the ice thickness–ice strength relationship and the ice thickness–ice growth rate relationship, both of which represent negative feedbacks on ice thickness. The net influence of the ITD on polar climate sensitivity and variability results from the interaction of these and other complex feedback processes.

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Robin Clancy
,
Cecilia M. Bitz
,
Edward Blanchard-Wrigglesworth
,
Marie C. McGraw
, and
Steven M. Cavallo

Abstract

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 to 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 midlatitudes, 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.

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Marie C. McGraw
,
Eduardo Blanchard-Wrigglesworth
,
Robin P. Clancy
, and
Cecilia M. Bitz

Abstract

The predictability of sea ice during extreme sea ice loss events on subseasonal (daily to weekly) time scales 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 nonextreme days, despite evidence that links these extreme events to large-scale atmospheric patterns; in the wintertime, the difference between extreme and nonextreme 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 also 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.

Significance Statement

We studied weather model forecasts of changes in Arctic sea ice extent on day-to-day time scales in different regions and seasons. We were especially interested in extreme sea ice loss days, or days in which sea ice melts very quickly or is reduced due to diverging forces such as winds, ocean currents, and waves. We find that forecast models generally capture the observed timing of extreme sea ice loss days. We also find that forecasts of sea ice extent are worse on extreme sea ice loss days compared to typical days, and that forecast errors remain elevated following extreme sea ice loss events.

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Lily C. Hahn
,
Kyle C. Armour
,
David S. Battisti
,
Ian Eisenman
, and
Cecilia M. Bitz

Abstract

Arctic surface warming under greenhouse gas forcing peaks in winter and reaches its minimum during summer in both observations and model projections. Many mechanisms have been proposed to explain this seasonal asymmetry, but disentangling these processes remains a challenge in the interpretation of general circulation model (GCM) experiments. To isolate these mechanisms, we use an idealized single-column sea ice model (SCM) that captures the seasonal pattern of Arctic warming. SCM experiments demonstrate that as sea ice melts and exposes open ocean, the accompanying increase in effective surface heat capacity alone can produce the observed pattern of peak warming in early winter (shifting to late winter under increased forcing) by slowing the seasonal heating rate, thus delaying the phase and reducing the amplitude of the seasonal cycle of surface temperature. To investigate warming seasonality in more complex models, we perform GCM experiments that individually isolate sea ice albedo and thermodynamic effects under CO2 forcing. These also show a key role for the effective heat capacity of sea ice in promoting seasonal asymmetry through suppressing summer warming, in addition to precluding summer climatological inversions and a positive summer lapse-rate feedback. Peak winter warming in GCM experiments is further supported by a positive winter lapse-rate feedback, due to cold initial surface temperatures and strong surface-trapped warming that are enabled by the albedo effects of sea ice alone. While many factors contribute to the seasonal pattern of Arctic warming, these results highlight changes in effective surface heat capacity as a central mechanism supporting this seasonality.

Significance Statement

Under increasing concentrations of atmospheric greenhouse gases, the strongest Arctic warming has occurred during early winter, but the reasons for this seasonal pattern of warming are not well understood. We use experiments in both simple and complex models with certain sea ice processes turned on and off to disentangle potential drivers of seasonality in Arctic warming. When sea ice melts and open ocean is exposed, surface temperatures are slower to reach the warm-season maximum and slower to cool back down below freezing in early winter. We find that this process alone can produce the observed pattern of maximum Arctic warming in early winter, highlighting a fundamental mechanism for the seasonality of Arctic warming.

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