Effects of sea ice dynamics on the Antarctic sea ice distribution in a coupled ocean atmosphere model

Ogura, Tomoo; Abe‐Ouchi, Ayako; Hasumi, Hiroyasu

doi:10.1029/2003jc002022

Cited by 9 publications

(6 citation statements)

References 36 publications

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“…In their heat budget analysis, Nihashi and Ohshima (2001) showed that heat through the open water area from the atmosphere is comparable to the latent heat of sea ice melting in the whole Antarctic sea ice zone and much larger than the estimated heat from the deeper ocean. The importance of the ice-ocean-albedo feedback was further supported in modeling studies by Ogura (2004) and Ohshima and Nihashi (2005), who also found that including divergent wind effects improved their results.…”

Section: Ice-ocean-albedo Feedbackmentioning

confidence: 71%

Understanding the Seasonal Cycle of Antarctic Sea Ice Extent in the Context of Longer‐Term Variability

Eayrs

Holland

Francis

et al. 2019

Reviews of Geophysics

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Over the 40‐year satellite record, there has been a slight increasing trend in total annual mean Antarctic sea ice extent of approximately 1.5% per decade that is made up of the sum of significantly larger opposing regional trends. However, record increases in total Antarctic sea ice extent were observed during 2012–2014, followed by record lows (for the satellite era) through 2018. There is still no consensus on the main drivers of these trends, but it is generally believed that the atmosphere plays a significant role and that seasonal time scales and regional scale processes are important. Despite considerable yearly and regional variability, the mean seasonal cycle of growth and melt of Antarctic sea ice is strikingly consistent, with a slow growth but fast melt season. If we are to project trends in Antarctic sea ice and understand changes on longer time scales, we need to understand the mechanisms related to the seasonal cycle separately from those that drive variability. Twice‐yearly changes in the position and intensity of the zonal winds circling Antarctica are thought to drive the system by working with or against the evolving sea ice edge to slow the autumn advance and hasten the spring melt. Open water regions, created by divergence associated with the zonal winds, amplify the spring melt through increased warming of the upper ocean. Climate models fail to accurately reproduce mean Antarctic sea ice extent and overestimate its year‐to‐year variability, but they tend to capture the pattern and timing of the Antarctic seasonal cycle.

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Section: Ice-ocean-albedo Feedbackmentioning

confidence: 71%

Understanding the Seasonal Cycle of Antarctic Sea Ice Extent in the Context of Longer‐Term Variability

Eayrs

Holland

Francis

et al. 2019

Reviews of Geophysics

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“…While substantial progress has been made with such models (e.g., Randall et al 2007;Holland and Raphael 2006;Bitz et al 2005;Ogura et al 2004;Jungclaus et al 2005), they are unsuitable for studies of the long-term thermohaline circulation. The reason is essentially due to the failures described above: basically, the high-latitude near-surface conditions in such models are too unrealistic to properly simulate deep-and bottom-water formation rates and consequently the long-term global deep-ocean properties.…”

Section: Discussion and Summarymentioning

confidence: 98%

“…This applies to coupled atmosphere-ice-ocean GCMs (e.g., Holland and Raphael 2006;Bitz et al 2005;Ogura et al 2004;Jungclaus et al 2005) as much as to iceocean GCMs that are forced by atmospheric variables (e.g., Goosse and Fichefet 1999;Timmermann et al 2005;Marsland et al 2004;Stössel et al 2002).…”

Section: Introductionmentioning

confidence: 97%

Employing Satellite-Derived Sea Ice Concentration to Constrain Upper-Ocean Temperature in a Global Ocean GCM

Stössel

2008

Journal of Climate

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The quality of Southern Ocean sea ice simulations in a global ocean general circulation model (GCM) depends decisively on the simulated upper-ocean temperature. This is confirmed by assimilating satellitederived sea ice concentration to constrain the upper-layer temperature of a sea ice-ocean GCM. The resolution of the model's sea ice component is about 22 km and thus comparable to the pixel resolution of the satellite data. The ocean component is coarse resolution to afford long-term integrations for investigations of the deep-ocean equilibrium response. Besides improving the sea ice simulation considerably, the simulations with constrained upper-ocean temperature yield much more realistic global deep-ocean properties, in particular when combined with glacial freshwater input. Both outcomes are relatively insensitive to the passive-microwave algorithm used to retrieve the ice concentration being assimilated. The sensitivity of the long-term global deep-ocean properties and circulation to the possible freshwater input from ice shelves and to the parameterization of vertical mixing in the Southern Ocean is reevaluated under the new constraint.

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“…Accordingly, seasonal differences are more important than spatial differences in the Arctic, and a column model such as the model by Eisenman (2007) or our ITD conceptual model is appropriate to describe the evolution of ice area in this region. In contrast, sea ice in the Southern Hemisphere is formed near the coast due to the very cold winds from the Antarctic continent and is then exported toward the open ocean where it gradually melts (Fichefet and Morales Maqueda 1997;Ogura et al 2004). This occurs in summer and winter, with a much larger sea ice extent in winter than summer.…”

Section: Discussionmentioning

confidence: 99%

On the Potential for Abrupt Arctic Winter Sea Ice Loss

et al. 2016

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The authors examine the transition from a seasonally ice-covered Arctic to an Arctic Ocean that is sea ice free all year round under increasing atmospheric CO 2 levels. It is shown that in comprehensive climate models, such loss of Arctic winter sea ice area is faster than the preceding loss of summer sea ice area for the same rate of warming. In two of the models, several million square kilometers of winter sea ice are lost within only one decade. It is shown that neither surface albedo nor cloud feedbacks can explain the rapid winter ice loss in the climate model MPI-ESM by suppressing both feedbacks in the model. The authors argue that the large sensitivity of winter sea ice area in the models is caused by the asymmetry between melting and freezing: an ice-free summer requires the complete melt of even the thickest sea ice, which is why the perennial ice coverage decreases only gradually as more and more of the thinner ice melts away. In winter, however, sea ice areal coverage remains high as long as sea ice still forms, and then drops to zero wherever the ocean warms sufficiently to no longer form ice during winter. The loss of basinwide Arctic winter sea ice area, however, is still gradual in most models since the threshold mechanism proposed here is reversible and not associated with the existence of multiple steady states. As this occurs in every model analyzed here and is independent of any specific parameterization, it is likely to be relevant in the real world.

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Effects of sea ice dynamics on the Antarctic sea ice distribution in a coupled ocean atmosphere model

Cited by 9 publications

References 36 publications

Understanding the Seasonal Cycle of Antarctic Sea Ice Extent in the Context of Longer‐Term Variability

Understanding the Seasonal Cycle of Antarctic Sea Ice Extent in the Context of Longer‐Term Variability

Employing Satellite-Derived Sea Ice Concentration to Constrain Upper-Ocean Temperature in a Global Ocean GCM

On the Potential for Abrupt Arctic Winter Sea Ice Loss

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