Sea ice thickness distribution in the Arctic Ocean

Bourke, Robert H.; Garrett, Robert P.

doi:10.1016/0165-232x(87)90007-3

Cited by 338 publications

(210 citation statements)

References 9 publications

Supporting

Mentioning

170

Contrasting

Unclassified

Order By: Relevance

“…10). The ice is now thicker in the western sector of the Central Arctic, in closer agreement with observations (Bourke and Garrett, 1987;Laxon et al, 2003). However, as already stated the observed spatial pattern of ice thickness cannot be reproduced because of errors in the wind stress forcing.…”

Section: Optimised Evp Runsupporting

confidence: 76%

See 1 more Smart Citation

Results from the implementation of the Elastic Viscous Plastic sea ice rheology in HadCM3

2006

View full text Add to dashboard Cite

Abstract. We present results of an implementation of the Elastic Viscous Plastic (EVP) sea ice dynamics scheme into the Hadley Centre coupled ocean-atmosphere climate model HadCM3. Although the large-scale simulation of sea ice in HadCM3 is quite good with this model, the lack of a full dynamical model leads to errors in the detailed representation of sea ice and limits our confidence in its future predictions. We find that introducing the EVP scheme results in a worse initial simulation of the sea ice. This paper documents various enhancements made to improve the simulation, resulting in a sea ice simulation that is better than the original HadCM3 scheme overall. Importantly, it is more physically based and provides a more solid foundation for future development. We then consider the interannual variability of the sea ice in the new model and demonstrate improvements over the HadCM3 simulation.

show abstract

Section: Optimised Evp Runsupporting

confidence: 76%

“…However, the ice is now too thin in the western sector in HadCM3+EVP. The ice thickness is also too low in the Arctic compared with observations (Bourke and Garrett, 1987;Laxon et al, 2003). The observations show the thickest ice is banked up against the northern coasts of Greenland and the Canadian Archipelago.…”

Section: Evp In Hadcm3mentioning

confidence: 68%

Results from the implementation of the Elastic Viscous Plastic sea ice rheology in HadCM3

2006

View full text Add to dashboard Cite

show abstract

“…2a) similar to observed conditions in the 1960s-1970s (e.g. Bourke and Garrett 1987). In the second and third ensemble sets, with 23 and 20 members, respectively, the initial ice and ocean state were chosen to reflect conditions similar to those of the recent historical record with a thinner mean ice pack (Fig.…”

Section: Climate Model Integrationsmentioning

confidence: 99%

Inherent sea ice predictability in the rapidly changing Arctic environment of the Community Climate System Model, version 3

2010

View full text Add to dashboard Cite

Seasonal predictions of Arctic sea ice have typically been based on statistical regression models or on results from ensemble ice model forecasts driven by historical atmospheric forcing. However, in the rapidly changing Arctic environment, the predictability characteristics of summer ice cover could undergo important transformations. Here global coupled climate model simulations are used to assess the inherent predictability of Arctic sea ice conditions on seasonal to interannual timescales within the Community Climate System Model, version 3. The role of preconditioning of the ice cover versus intrinsic variations in determining sea ice conditions is examined using ensemble experiments initialized in January with identical ice-ocean-terrestrial conditions. Assessing the divergence among the ensemble members reveals that sea ice area exhibits potential predictability during the first summer and for winter conditions after a year. The ice area exhibits little potential predictability during the spring transition season. Comparing experiments initialized with different mean ice conditions indicates that ice area in a thicker sea ice regime generally exhibits higher potential predictability for a longer period of time. In a thinner sea ice regime, winter ice conditions provide little ice area predictive capability after approximately 1 year. In all regimes, ice thickness has high potential predictability for at least 2 years.

show abstract

“…The ocean model component uses the Geophysical Fluid Dynamic Laboratory's Modular Ocean Model, version 2 (MOM2) [Pacanowski, 1995] Bourke and Garret [1987]. This results in a larger seasonal cycle in the ice area than is observed (Figure 1).…”

Section: Model Descriptionmentioning

confidence: 99%

The influence of sea ice physics on simulations of climate change

Holland¹,

Bitz²,

Weaver³

2001

J. Geophys. Res.

View full text Add to dashboard Cite

Abstract.In this study, we examine the influence of ice dynamics and the sub-grid-scale ice thickness distribution on present-day and climate change simulations in a global coupled ice-ocean-atmosphere model of intermediate complexity. Under present-day conditions the sea-ice physics modifies both the annual mean and seasonal variation of ice-ocean-atmosphere conditions. In models with motionless sea ice, the ice volume increases and undergoes a smaller seasonal cycle. Resolving the ice thickness distribution also increases the ice thickness, but enhances the seasonal cycle. The response of the system to increased atmospheric CO2 forcing is also dependent on the sea ice physics. Simulating ice dynamics and the ice thickness distribution enhances the ice area response. However, the ice volume response is diminished when ice dynamics is included and enhanced when the ice thickness distribution is resolved. The oceanic thermohaiine circulation and regional air temperature response to global warming is also dependent on the sea ice parameterizations. Additional simulations were peribrined to quantify the influence of the albedo feedback mechanism on climate change simulations. When the albedo i•edback was inactive, amplified warming was still present (although reduced) at high latitudes due to the poleward retreat of the ice cover and larger oceanatmosphere heat exchange. In these simulations, the albedo feedback accounted for 17% of the global air temperature increase and over 30% of the Northern Hemisphere ice area and volume decrease.

show abstract

Sea ice thickness distribution in the Arctic Ocean

Cited by 338 publications

References 9 publications

Results from the implementation of the Elastic Viscous Plastic sea ice rheology in HadCM3

Results from the implementation of the Elastic Viscous Plastic sea ice rheology in HadCM3

Inherent sea ice predictability in the rapidly changing Arctic environment of the Community Climate System Model, version 3

The influence of sea ice physics on simulations of climate change

Contact Info

Product

Resources

About